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</script></head><body><div id="package-header"><ul class="links" id="page-menu"><li><a href="index.html">Contents</a></li><li><a href="doc-index.html">Index</a></li></ul><p class="caption">tensorflow-core-ops-0.1.0.0: Haskell wrappers for Core Tensorflow Ops.</p></div><div id="content"><div id="module-header"><table class="info"><tr><th>Safe Haskell</th><td>None</td></tr><tr><th>Language</th><td>Haskell2010</td></tr></table><p class="caption">TensorFlow.GenOps.Core</p></div><div id="synopsis"><p id="control.syn" class="caption expander" onclick="toggleSection('syn')">Synopsis</p><ul id="section.syn" class="hide" onclick="toggleSection('syn')"><li class="src short"><a href="#v:abort">abort</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:abort-39-">abort'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:abs">abs</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:abs-39-">abs'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:accumulatorApplyGradient">accumulatorApplyGradient</a> :: <span class="keyword">forall</span> v'2 v'3 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 dtype -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:accumulatorApplyGradient-39-">accumulatorApplyGradient'</a> :: <span class="keyword">forall</span> v'2 v'3 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 dtype -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:accumulatorNumAccumulated">accumulatorNumAccumulated</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:accumulatorNumAccumulated-39-">accumulatorNumAccumulated'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:accumulatorSetGlobalStep">accumulatorSetGlobalStep</a> :: <span class="keyword">forall</span> v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:accumulatorSetGlobalStep-39-">accumulatorSetGlobalStep'</a> :: <span class="keyword">forall</span> v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:accumulatorTakeGradient">accumulatorTakeGradient</a> :: <span class="keyword">forall</span> v'2 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:accumulatorTakeGradient-39-">accumulatorTakeGradient'</a> :: <span class="keyword">forall</span> v'2 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:acos">acos</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:acos-39-">acos'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:add">add</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:add-39-">add'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:addManySparseToTensorsMap">addManySparseToTensorsMap</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:addManySparseToTensorsMap-39-">addManySparseToTensorsMap'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:addN">addN</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:addN-39-">addN'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:addSparseToTensorsMap">addSparseToTensorsMap</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:addSparseToTensorsMap-39-">addSparseToTensorsMap'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:adjustContrast">adjustContrast</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:adjustContrast-39-">adjustContrast'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:adjustContrastv2">adjustContrastv2</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:adjustContrastv2-39-">adjustContrastv2'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:adjustHue">adjustHue</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:adjustHue-39-">adjustHue'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:adjustSaturation">adjustSaturation</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:adjustSaturation-39-">adjustSaturation'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:all">all</a> :: <span class="keyword">forall</span> v'1 v'2 tidx. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:all-39-">all'</a> :: <span class="keyword">forall</span> v'1 v'2 tidx. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:allCandidateSampler">allCandidateSampler</a> :: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:allCandidateSampler-39-">allCandidateSampler'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:any">any</a> :: <span class="keyword">forall</span> v'1 v'2 tidx. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:any-39-">any'</a> :: <span class="keyword">forall</span> v'1 v'2 tidx. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:applyAdadelta">applyAdadelta</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyAdadelta-39-">applyAdadelta'</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyAdagrad">applyAdagrad</a> :: <span class="keyword">forall</span> v'3 v'4 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyAdagrad-39-">applyAdagrad'</a> :: <span class="keyword">forall</span> v'3 v'4 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyAdagradDA">applyAdagradDA</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyAdagradDA-39-">applyAdagradDA'</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyAdam">applyAdam</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 v'9 v'10 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyAdam-39-">applyAdam'</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 v'9 v'10 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyCenteredRMSProp">applyCenteredRMSProp</a> :: <span class="keyword">forall</span> v'5 v'6 v'7 v'8 v'9 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyCenteredRMSProp-39-">applyCenteredRMSProp'</a> :: <span class="keyword">forall</span> v'5 v'6 v'7 v'8 v'9 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyFtrl">applyFtrl</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyFtrl-39-">applyFtrl'</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyGradientDescent">applyGradientDescent</a> :: <span class="keyword">forall</span> v'2 v'3 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyGradientDescent-39-">applyGradientDescent'</a> :: <span class="keyword">forall</span> v'2 v'3 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyMomentum">applyMomentum</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyMomentum-39-">applyMomentum'</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyProximalAdagrad">applyProximalAdagrad</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 v'6 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyProximalAdagrad-39-">applyProximalAdagrad'</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 v'6 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyProximalGradientDescent">applyProximalGradientDescent</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 v'5 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyProximalGradientDescent-39-">applyProximalGradientDescent'</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 v'5 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyRMSProp">applyRMSProp</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:applyRMSProp-39-">applyRMSProp'</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:argMax">argMax</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></li><li class="src short"><a href="#v:argMax-39-">argMax'</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></li><li class="src short"><a href="#v:argMin">argMin</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></li><li class="src short"><a href="#v:argMin-39-">argMin'</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></li><li class="src short"><a href="#v:asString">asString</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:asString-39-">asString'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:asin">asin</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:asin-39-">asin'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:assert">assert</a> :: <span class="keyword">forall</span> v'1 v'2 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:assert-39-">assert'</a> :: <span class="keyword">forall</span> v'1 v'2 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:assign">assign</a> :: <span class="keyword">forall</span> v'2 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:assign-39-">assign'</a> :: <span class="keyword">forall</span> v'2 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:assignAdd">assignAdd</a> :: <span class="keyword">forall</span> v'2 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:assignAdd-39-">assignAdd'</a> :: <span class="keyword">forall</span> v'2 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:assignAddVariableOp">assignAddVariableOp</a> :: <span class="keyword">forall</span> v'2 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 dtype -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:assignAddVariableOp-39-">assignAddVariableOp'</a> :: <span class="keyword">forall</span> v'2 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 dtype -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:assignSub">assignSub</a> :: <span class="keyword">forall</span> v'2 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:assignSub-39-">assignSub'</a> :: <span class="keyword">forall</span> v'2 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:assignVariableOp">assignVariableOp</a> :: <span class="keyword">forall</span> v'2 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 dtype -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:assignVariableOp-39-">assignVariableOp'</a> :: <span class="keyword">forall</span> v'2 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 dtype -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:atan">atan</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:atan-39-">atan'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:audioSummary">audioSummary</a> :: <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:audioSummary-39-">audioSummary'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:audioSummaryV2">audioSummaryV2</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:audioSummaryV2-39-">audioSummaryV2'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:avgPool">avgPool</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:avgPool-39-">avgPool'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:avgPool3D">avgPool3D</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:avgPool3D-39-">avgPool3D'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:avgPool3DGrad">avgPool3DGrad</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:avgPool3DGrad-39-">avgPool3DGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:avgPoolGrad">avgPoolGrad</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:avgPoolGrad-39-">avgPoolGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:barrier">barrier</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>] -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:barrier-39-">barrier'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>] -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:barrierClose">barrierClose</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:barrierClose-39-">barrierClose'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:barrierIncompleteSize">barrierIncompleteSize</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:barrierIncompleteSize-39-">barrierIncompleteSize'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:barrierInsertMany">barrierInsertMany</a> :: <span class="keyword">forall</span> v'2 v'3 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:barrierInsertMany-39-">barrierInsertMany'</a> :: <span class="keyword">forall</span> v'2 v'3 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:barrierReadySize">barrierReadySize</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:barrierReadySize-39-">barrierReadySize'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:barrierTakeMany">barrierTakeMany</a> :: <span class="keyword">forall</span> v'2 component_types m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</li><li class="src short"><a href="#v:barrierTakeMany-39-">barrierTakeMany'</a> :: <span class="keyword">forall</span> v'2 component_types m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</li><li class="src short"><a href="#v:batchCholesky">batchCholesky</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchCholesky-39-">batchCholesky'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchCholeskyGrad">batchCholeskyGrad</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchCholeskyGrad-39-">batchCholeskyGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchFFT">batchFFT</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:batchFFT-39-">batchFFT'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:batchFFT2D">batchFFT2D</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:batchFFT2D-39-">batchFFT2D'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:batchFFT3D">batchFFT3D</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:batchFFT3D-39-">batchFFT3D'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:batchIFFT">batchIFFT</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:batchIFFT-39-">batchIFFT'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:batchIFFT2D">batchIFFT2D</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:batchIFFT2D-39-">batchIFFT2D'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:batchIFFT3D">batchIFFT3D</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:batchIFFT3D-39-">batchIFFT3D'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:batchMatMul">batchMatMul</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatMul-39-">batchMatMul'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatrixBandPart">batchMatrixBandPart</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatrixBandPart-39-">batchMatrixBandPart'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatrixDeterminant">batchMatrixDeterminant</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatrixDeterminant-39-">batchMatrixDeterminant'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatrixDiag">batchMatrixDiag</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatrixDiag-39-">batchMatrixDiag'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatrixDiagPart">batchMatrixDiagPart</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatrixDiagPart-39-">batchMatrixDiagPart'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatrixInverse">batchMatrixInverse</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatrixInverse-39-">batchMatrixInverse'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatrixSetDiag">batchMatrixSetDiag</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatrixSetDiag-39-">batchMatrixSetDiag'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatrixSolve">batchMatrixSolve</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatrixSolve-39-">batchMatrixSolve'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatrixSolveLs">batchMatrixSolveLs</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatrixSolveLs-39-">batchMatrixSolveLs'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatrixTriangularSolve">batchMatrixTriangularSolve</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchMatrixTriangularSolve-39-">batchMatrixTriangularSolve'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchNormWithGlobalNormalization">batchNormWithGlobalNormalization</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchNormWithGlobalNormalization-39-">batchNormWithGlobalNormalization'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchNormWithGlobalNormalizationGrad">batchNormWithGlobalNormalizationGrad</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:batchNormWithGlobalNormalizationGrad-39-">batchNormWithGlobalNormalizationGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:batchSelfAdjointEig">batchSelfAdjointEig</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchSelfAdjointEig-39-">batchSelfAdjointEig'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchSelfAdjointEigV2">batchSelfAdjointEigV2</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:batchSelfAdjointEigV2-39-">batchSelfAdjointEigV2'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:batchSvd">batchSvd</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:batchSvd-39-">batchSvd'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:batchToSpace">batchToSpace</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchToSpace-39-">batchToSpace'</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchToSpaceND">batchToSpaceND</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t tblock_shape tcrops. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tblock_shape, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tcrops) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tblock_shape -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tcrops -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:batchToSpaceND-39-">batchToSpaceND'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t tblock_shape tcrops. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tblock_shape, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tcrops) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tblock_shape -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tcrops -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:betainc">betainc</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:betainc-39-">betainc'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:biasAdd">biasAdd</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:biasAdd-39-">biasAdd'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:biasAddGrad">biasAddGrad</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:biasAddGrad-39-">biasAddGrad'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:biasAddV1">biasAddV1</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:biasAddV1-39-">biasAddV1'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:bitcast">bitcast</a> :: <span class="keyword">forall</span> v'1 t type'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` type') => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> type'</li><li class="src short"><a href="#v:bitcast-39-">bitcast'</a> :: <span class="keyword">forall</span> v'1 t type'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` type') => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> type'</li><li class="src short"><a href="#v:broadcastArgs">broadcastArgs</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:broadcastArgs-39-">broadcastArgs'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:broadcastGradientArgs">broadcastGradientArgs</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:broadcastGradientArgs-39-">broadcastGradientArgs'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:cTCBeamSearchDecoder">cTCBeamSearchDecoder</a> :: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> ([<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:cTCBeamSearchDecoder-39-">cTCBeamSearchDecoder'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> ([<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:cTCGreedyDecoder">cTCGreedyDecoder</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:cTCGreedyDecoder-39-">cTCGreedyDecoder'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:cTCLoss">cTCLoss</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:cTCLoss-39-">cTCLoss'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:cast">cast</a> :: <span class="keyword">forall</span> v'1 srcT dstT. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> srcT, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dstT) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 srcT -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dstT</li><li class="src short"><a href="#v:cast-39-">cast'</a> :: <span class="keyword">forall</span> v'1 srcT dstT. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> srcT, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dstT) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 srcT -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dstT</li><li class="src short"><a href="#v:ceil">ceil</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:ceil-39-">ceil'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:checkNumerics">checkNumerics</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:checkNumerics-39-">checkNumerics'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:cholesky">cholesky</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:cholesky-39-">cholesky'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:choleskyGrad">choleskyGrad</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:choleskyGrad-39-">choleskyGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:complex">complex</a> :: <span class="keyword">forall</span> v'1 v'2 t tout. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tout) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tout</li><li class="src short"><a href="#v:complex-39-">complex'</a> :: <span class="keyword">forall</span> v'1 v'2 t tout. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tout) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tout</li><li class="src short"><a href="#v:complexAbs">complexAbs</a> :: <span class="keyword">forall</span> v'1 t tout. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tout) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tout</li><li class="src short"><a href="#v:complexAbs-39-">complexAbs'</a> :: <span class="keyword">forall</span> v'1 t tout. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tout) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tout</li><li class="src short"><a href="#v:computeAccidentalHits">computeAccidentalHits</a> :: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:computeAccidentalHits-39-">computeAccidentalHits'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:concat">concat</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:concat-39-">concat'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:concatOffset">concatOffset</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>]</li><li class="src short"><a href="#v:concatOffset-39-">concatOffset'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>]</li><li class="src short"><a href="#v:concatV2">concatV2</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:concatV2-39-">concatV2'</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:conditionalAccumulator">conditionalAccumulator</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:conditionalAccumulator-39-">conditionalAccumulator'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:conj">conj</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:conj-39-">conj'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:const">const</a> :: <span class="keyword">forall</span> dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</li><li class="src short"><a href="#v:const-39-">const'</a> :: <span class="keyword">forall</span> dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</li><li class="src short"><a href="#v:controlTrigger">controlTrigger</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:controlTrigger-39-">controlTrigger'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:conv2D">conv2D</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:conv2D-39-">conv2D'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:conv2DBackpropFilter">conv2DBackpropFilter</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:conv2DBackpropFilter-39-">conv2DBackpropFilter'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:conv2DBackpropInput">conv2DBackpropInput</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:conv2DBackpropInput-39-">conv2DBackpropInput'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:conv3D">conv3D</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:conv3D-39-">conv3D'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:conv3DBackpropFilter">conv3DBackpropFilter</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:conv3DBackpropFilter-39-">conv3DBackpropFilter'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:conv3DBackpropFilterV2">conv3DBackpropFilterV2</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:conv3DBackpropFilterV2-39-">conv3DBackpropFilterV2'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:conv3DBackpropInput">conv3DBackpropInput</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:conv3DBackpropInput-39-">conv3DBackpropInput'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:conv3DBackpropInputV2">conv3DBackpropInputV2</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:conv3DBackpropInputV2-39-">conv3DBackpropInputV2'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:copy">copy</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:copy-39-">copy'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:copyHost">copyHost</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:copyHost-39-">copyHost'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:cos">cos</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:cos-39-">cos'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:countUpTo">countUpTo</a> :: <span class="keyword">forall</span> t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t) => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</li><li class="src short"><a href="#v:countUpTo-39-">countUpTo'</a> :: <span class="keyword">forall</span> t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</li><li class="src short"><a href="#v:cropAndResize">cropAndResize</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:cropAndResize-39-">cropAndResize'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:cropAndResizeGradBoxes">cropAndResizeGradBoxes</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:cropAndResizeGradBoxes-39-">cropAndResizeGradBoxes'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:cropAndResizeGradImage">cropAndResizeGradImage</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:cropAndResizeGradImage-39-">cropAndResizeGradImage'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:cross">cross</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:cross-39-">cross'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:cumprod">cumprod</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:cumprod-39-">cumprod'</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:cumsum">cumsum</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:cumsum-39-">cumsum'</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:debugIdentity">debugIdentity</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:debugIdentity-39-">debugIdentity'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:debugNanCount">debugNanCount</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></li><li class="src short"><a href="#v:debugNanCount-39-">debugNanCount'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></li><li class="src short"><a href="#v:debugNumericSummary">debugNumericSummary</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a></li><li class="src short"><a href="#v:debugNumericSummary-39-">debugNumericSummary'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a></li><li class="src short"><a href="#v:decodeBase64">decodeBase64</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:decodeBase64-39-">decodeBase64'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:decodeCSV">decodeCSV</a> :: <span class="keyword">forall</span> v'1 v'2 oUT_TYPE. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` oUT_TYPE => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 oUT_TYPE -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> oUT_TYPE</li><li class="src short"><a href="#v:decodeCSV-39-">decodeCSV'</a> :: <span class="keyword">forall</span> v'1 v'2 oUT_TYPE. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` oUT_TYPE => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 oUT_TYPE -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> oUT_TYPE</li><li class="src short"><a href="#v:decodeGif">decodeGif</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a></li><li class="src short"><a href="#v:decodeGif-39-">decodeGif'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a></li><li class="src short"><a href="#v:decodeJSONExample">decodeJSONExample</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:decodeJSONExample-39-">decodeJSONExample'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:decodeJpeg">decodeJpeg</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a></li><li class="src short"><a href="#v:decodeJpeg-39-">decodeJpeg'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a></li><li class="src short"><a href="#v:decodePng">decodePng</a> :: <span class="keyword">forall</span> v'1 dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</li><li class="src short"><a href="#v:decodePng-39-">decodePng'</a> :: <span class="keyword">forall</span> v'1 dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</li><li class="src short"><a href="#v:decodeRaw">decodeRaw</a> :: <span class="keyword">forall</span> v'1 out_type. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` out_type => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</li><li class="src short"><a href="#v:decodeRaw-39-">decodeRaw'</a> :: <span class="keyword">forall</span> v'1 out_type. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` out_type => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</li><li class="src short"><a href="#v:deleteSessionTensor">deleteSessionTensor</a> :: <span class="keyword">forall</span> v'1 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:deleteSessionTensor-39-">deleteSessionTensor'</a> :: <span class="keyword">forall</span> v'1 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:denseToDenseSetOperation">denseToDenseSetOperation</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:denseToDenseSetOperation-39-">denseToDenseSetOperation'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:denseToSparseSetOperation">denseToSparseSetOperation</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:denseToSparseSetOperation-39-">denseToSparseSetOperation'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:depthToSpace">depthToSpace</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:depthToSpace-39-">depthToSpace'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:depthwiseConv2dNative">depthwiseConv2dNative</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:depthwiseConv2dNative-39-">depthwiseConv2dNative'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:depthwiseConv2dNativeBackpropFilter">depthwiseConv2dNativeBackpropFilter</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:depthwiseConv2dNativeBackpropFilter-39-">depthwiseConv2dNativeBackpropFilter'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:depthwiseConv2dNativeBackpropInput">depthwiseConv2dNativeBackpropInput</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:depthwiseConv2dNativeBackpropInput-39-">depthwiseConv2dNativeBackpropInput'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:dequantize">dequantize</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:dequantize-39-">dequantize'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:deserializeManySparse">deserializeManySparse</a> :: <span class="keyword">forall</span> v'1 dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:deserializeManySparse-39-">deserializeManySparse'</a> :: <span class="keyword">forall</span> v'1 dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:destroyTemporaryVariable">destroyTemporaryVariable</a> :: <span class="keyword">forall</span> t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</li><li class="src short"><a href="#v:destroyTemporaryVariable-39-">destroyTemporaryVariable'</a> :: <span class="keyword">forall</span> t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</li><li class="src short"><a href="#v:diag">diag</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:diag-39-">diag'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:diagPart">diagPart</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:diagPart-39-">diagPart'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:digamma">digamma</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:digamma-39-">digamma'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:dilation2D">dilation2D</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:dilation2D-39-">dilation2D'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:dilation2DBackpropFilter">dilation2DBackpropFilter</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:dilation2DBackpropFilter-39-">dilation2DBackpropFilter'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:dilation2DBackpropInput">dilation2DBackpropInput</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:dilation2DBackpropInput-39-">dilation2DBackpropInput'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:div">div</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:div-39-">div'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:drawBoundingBoxes">drawBoundingBoxes</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:drawBoundingBoxes-39-">drawBoundingBoxes'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:dynamicPartition">dynamicPartition</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</li><li class="src short"><a href="#v:dynamicPartition-39-">dynamicPartition'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</li><li class="src short"><a href="#v:dynamicStitch">dynamicStitch</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:dynamicStitch-39-">dynamicStitch'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:editDistance">editDistance</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:editDistance-39-">editDistance'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:elu">elu</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:elu-39-">elu'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:eluGrad">eluGrad</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:eluGrad-39-">eluGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:encodeBase64">encodeBase64</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:encodeBase64-39-">encodeBase64'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:encodeJpeg">encodeJpeg</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:encodeJpeg-39-">encodeJpeg'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:encodePng">encodePng</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:encodePng-39-">encodePng'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:enter">enter</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:enter-39-">enter'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:equal">equal</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:equal-39-">equal'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:erf">erf</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:erf-39-">erf'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:erfc">erfc</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:erfc-39-">erfc'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:exit">exit</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:exit-39-">exit'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:exp">exp</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:exp-39-">exp'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:expandDims">expandDims</a> :: <span class="keyword">forall</span> v'1 v'2 t tdim. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tdim) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tdim -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:expandDims-39-">expandDims'</a> :: <span class="keyword">forall</span> v'1 v'2 t tdim. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tdim) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tdim -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:expm1">expm1</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:expm1-39-">expm1'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:extractGlimpse">extractGlimpse</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:extractGlimpse-39-">extractGlimpse'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:extractImagePatches">extractImagePatches</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:extractImagePatches-39-">extractImagePatches'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:fFT">fFT</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:fFT-39-">fFT'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:fFT2D">fFT2D</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:fFT2D-39-">fFT2D'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:fFT3D">fFT3D</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:fFT3D-39-">fFT3D'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:fIFOQueue">fIFOQueue</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>] -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:fIFOQueue-39-">fIFOQueue'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>] -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:fIFOQueueV2">fIFOQueueV2</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>] -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:fIFOQueueV2-39-">fIFOQueueV2'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>] -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:fact">fact</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:fact-39-">fact'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:fakeQuantWithMinMaxArgs">fakeQuantWithMinMaxArgs</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:fakeQuantWithMinMaxArgs-39-">fakeQuantWithMinMaxArgs'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:fakeQuantWithMinMaxArgsGradient">fakeQuantWithMinMaxArgsGradient</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:fakeQuantWithMinMaxArgsGradient-39-">fakeQuantWithMinMaxArgsGradient'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:fakeQuantWithMinMaxVars">fakeQuantWithMinMaxVars</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:fakeQuantWithMinMaxVars-39-">fakeQuantWithMinMaxVars'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:fakeQuantWithMinMaxVarsGradient">fakeQuantWithMinMaxVarsGradient</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:fakeQuantWithMinMaxVarsGradient-39-">fakeQuantWithMinMaxVarsGradient'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:fakeQuantWithMinMaxVarsPerChannel">fakeQuantWithMinMaxVarsPerChannel</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:fakeQuantWithMinMaxVarsPerChannel-39-">fakeQuantWithMinMaxVarsPerChannel'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:fakeQuantWithMinMaxVarsPerChannelGradient">fakeQuantWithMinMaxVarsPerChannelGradient</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:fakeQuantWithMinMaxVarsPerChannelGradient-39-">fakeQuantWithMinMaxVarsPerChannelGradient'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:fakeQueue">fakeQueue</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:fakeQueue-39-">fakeQueue'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:fill">fill</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:fill-39-">fill'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:fixedLengthRecordReader">fixedLengthRecordReader</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:fixedLengthRecordReader-39-">fixedLengthRecordReader'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:fixedLengthRecordReaderV2">fixedLengthRecordReaderV2</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:fixedLengthRecordReaderV2-39-">fixedLengthRecordReaderV2'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:fixedUnigramCandidateSampler">fixedUnigramCandidateSampler</a> :: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:fixedUnigramCandidateSampler-39-">fixedUnigramCandidateSampler'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:floor">floor</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:floor-39-">floor'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:floorDiv">floorDiv</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:floorDiv-39-">floorDiv'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:floorMod">floorMod</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:floorMod-39-">floorMod'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:fractionalAvgPool">fractionalAvgPool</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:fractionalAvgPool-39-">fractionalAvgPool'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:fractionalAvgPoolGrad">fractionalAvgPoolGrad</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:fractionalAvgPoolGrad-39-">fractionalAvgPoolGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:fractionalMaxPool">fractionalMaxPool</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:fractionalMaxPool-39-">fractionalMaxPool'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:fractionalMaxPoolGrad">fractionalMaxPoolGrad</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:fractionalMaxPoolGrad-39-">fractionalMaxPoolGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:fusedBatchNorm">fusedBatchNorm</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:fusedBatchNorm-39-">fusedBatchNorm'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:fusedBatchNormGrad">fusedBatchNormGrad</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:fusedBatchNormGrad-39-">fusedBatchNormGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:fusedPadConv2D">fusedPadConv2D</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:fusedPadConv2D-39-">fusedPadConv2D'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:fusedResizeAndPadConv2D">fusedResizeAndPadConv2D</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:fusedResizeAndPadConv2D-39-">fusedResizeAndPadConv2D'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:gather">gather</a> :: <span class="keyword">forall</span> v'1 v'2 tparams tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tparams, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tparams -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tparams</li><li class="src short"><a href="#v:gather-39-">gather'</a> :: <span class="keyword">forall</span> v'1 v'2 tparams tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tparams, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tparams -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tparams</li><li class="src short"><a href="#v:gatherNd">gatherNd</a> :: <span class="keyword">forall</span> v'1 v'2 tparams tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tparams, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tparams -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tparams</li><li class="src short"><a href="#v:gatherNd-39-">gatherNd'</a> :: <span class="keyword">forall</span> v'1 v'2 tparams tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tparams, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tparams -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tparams</li><li class="src short"><a href="#v:getSessionHandle">getSessionHandle</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:getSessionHandle-39-">getSessionHandle'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:getSessionTensor">getSessionTensor</a> :: <span class="keyword">forall</span> v'1 dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</li><li class="src short"><a href="#v:getSessionTensor-39-">getSessionTensor'</a> :: <span class="keyword">forall</span> v'1 dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</li><li class="src short"><a href="#v:greater">greater</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:greater-39-">greater'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:greaterEqual">greaterEqual</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:greaterEqual-39-">greaterEqual'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:hSVToRGB">hSVToRGB</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:hSVToRGB-39-">hSVToRGB'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:hashTable">hashTable</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:hashTable-39-">hashTable'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:histogramSummary">histogramSummary</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:histogramSummary-39-">histogramSummary'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:iFFT">iFFT</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:iFFT-39-">iFFT'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:iFFT2D">iFFT2D</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:iFFT2D-39-">iFFT2D'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:iFFT3D">iFFT3D</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:iFFT3D-39-">iFFT3D'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>) -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:identity">identity</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:identity-39-">identity'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:identityReader">identityReader</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:identityReader-39-">identityReader'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:identityReaderV2">identityReaderV2</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:identityReaderV2-39-">identityReaderV2'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:igamma">igamma</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:igamma-39-">igamma'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:igammac">igammac</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:igammac-39-">igammac'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:imag">imag</a> :: <span class="keyword">forall</span> v'1 t tout. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tout) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tout</li><li class="src short"><a href="#v:imag-39-">imag'</a> :: <span class="keyword">forall</span> v'1 t tout. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tout) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tout</li><li class="src short"><a href="#v:imageSummary">imageSummary</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:imageSummary-39-">imageSummary'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:immutableConst">immutableConst</a> :: <span class="keyword">forall</span> dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</li><li class="src short"><a href="#v:immutableConst-39-">immutableConst'</a> :: <span class="keyword">forall</span> dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</li><li class="src short"><a href="#v:inTopK">inTopK</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:inTopK-39-">inTopK'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:initializeTable">initializeTable</a> :: <span class="keyword">forall</span> v'2 v'3 tkey tval m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tkey, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tval) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tkey -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tval -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:initializeTable-39-">initializeTable'</a> :: <span class="keyword">forall</span> v'2 v'3 tkey tval m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tkey, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tval) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tkey -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tval -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:initializeTableFromTextFile">initializeTableFromTextFile</a> :: <span class="keyword">forall</span> v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:initializeTableFromTextFile-39-">initializeTableFromTextFile'</a> :: <span class="keyword">forall</span> v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:inv">inv</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:inv-39-">inv'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:invGrad">invGrad</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:invGrad-39-">invGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:invertPermutation">invertPermutation</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:invertPermutation-39-">invertPermutation'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:isFinite">isFinite</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:isFinite-39-">isFinite'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:isInf">isInf</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:isInf-39-">isInf'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:isNan">isNan</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:isNan-39-">isNan'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:isVariableInitialized">isVariableInitialized</a> :: <span class="keyword">forall</span> dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> dtype -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>)</li><li class="src short"><a href="#v:isVariableInitialized-39-">isVariableInitialized'</a> :: <span class="keyword">forall</span> dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> dtype -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>)</li><li class="src short"><a href="#v:l2Loss">l2Loss</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:l2Loss-39-">l2Loss'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:lRN">lRN</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:lRN-39-">lRN'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:lRNGrad">lRNGrad</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:lRNGrad-39-">lRNGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:learnedUnigramCandidateSampler">learnedUnigramCandidateSampler</a> :: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:learnedUnigramCandidateSampler-39-">learnedUnigramCandidateSampler'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:less">less</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:less-39-">less'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:lessEqual">lessEqual</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:lessEqual-39-">lessEqual'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:lgamma">lgamma</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:lgamma-39-">lgamma'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:linSpace">linSpace</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:linSpace-39-">linSpace'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:listDiff">listDiff</a> :: <span class="keyword">forall</span> v'1 v'2 t out_idx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_idx) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_idx)</li><li class="src short"><a href="#v:listDiff-39-">listDiff'</a> :: <span class="keyword">forall</span> v'1 v'2 t out_idx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_idx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_idx)</li><li class="src short"><a href="#v:log">log</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:log-39-">log'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:log1p">log1p</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:log1p-39-">log1p'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:logSoftmax">logSoftmax</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:logSoftmax-39-">logSoftmax'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:logUniformCandidateSampler">logUniformCandidateSampler</a> :: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:logUniformCandidateSampler-39-">logUniformCandidateSampler'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:logicalAnd">logicalAnd</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:logicalAnd-39-">logicalAnd'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:logicalNot">logicalNot</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:logicalNot-39-">logicalNot'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:logicalOr">logicalOr</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:logicalOr-39-">logicalOr'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:lookupTableExport">lookupTableExport</a> :: <span class="keyword">forall</span> tkeys tvalues m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tkeys, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tvalues) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tkeys, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tvalues)</li><li class="src short"><a href="#v:lookupTableExport-39-">lookupTableExport'</a> :: <span class="keyword">forall</span> tkeys tvalues m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tkeys, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tvalues) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tkeys, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tvalues)</li><li class="src short"><a href="#v:lookupTableFind">lookupTableFind</a> :: <span class="keyword">forall</span> v'2 v'3 tin tout m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tin, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tout) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tin -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tout -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tout)</li><li class="src short"><a href="#v:lookupTableFind-39-">lookupTableFind'</a> :: <span class="keyword">forall</span> v'2 v'3 tin tout m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tin, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tout) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tin -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tout -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tout)</li><li class="src short"><a href="#v:lookupTableImport">lookupTableImport</a> :: <span class="keyword">forall</span> v'2 v'3 tin tout m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tin, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tout) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tin -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tout -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:lookupTableImport-39-">lookupTableImport'</a> :: <span class="keyword">forall</span> v'2 v'3 tin tout m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tin, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tout) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tin -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tout -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:lookupTableInsert">lookupTableInsert</a> :: <span class="keyword">forall</span> v'2 v'3 tin tout m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tin, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tout) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tin -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tout -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:lookupTableInsert-39-">lookupTableInsert'</a> :: <span class="keyword">forall</span> v'2 v'3 tin tout m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tin, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tout) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tin -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tout -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:lookupTableSize">lookupTableSize</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:lookupTableSize-39-">lookupTableSize'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:loopCond">loopCond</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:loopCond-39-">loopCond'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:matMul">matMul</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matMul-39-">matMul'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matchingFiles">matchingFiles</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:matchingFiles-39-">matchingFiles'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:matrixBandPart">matrixBandPart</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matrixBandPart-39-">matrixBandPart'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matrixDeterminant">matrixDeterminant</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matrixDeterminant-39-">matrixDeterminant'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matrixDiag">matrixDiag</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matrixDiag-39-">matrixDiag'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matrixDiagPart">matrixDiagPart</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matrixDiagPart-39-">matrixDiagPart'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matrixInverse">matrixInverse</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matrixInverse-39-">matrixInverse'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matrixSetDiag">matrixSetDiag</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matrixSetDiag-39-">matrixSetDiag'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matrixSolve">matrixSolve</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matrixSolve-39-">matrixSolve'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matrixSolveLs">matrixSolveLs</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matrixSolveLs-39-">matrixSolveLs'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matrixTriangularSolve">matrixTriangularSolve</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:matrixTriangularSolve-39-">matrixTriangularSolve'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:max">max</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:max-39-">max'</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:maxPool">maxPool</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:maxPool-39-">maxPool'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:maxPool3D">maxPool3D</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:maxPool3D-39-">maxPool3D'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:maxPool3DGrad">maxPool3DGrad</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:maxPool3DGrad-39-">maxPool3DGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:maxPoolGrad">maxPoolGrad</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:maxPoolGrad-39-">maxPoolGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:maxPoolGradWithArgmax">maxPoolGradWithArgmax</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 targmax t. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` targmax, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 targmax -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:maxPoolGradWithArgmax-39-">maxPoolGradWithArgmax'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 targmax t. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` targmax, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 targmax -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:maxPoolWithArgmax">maxPoolWithArgmax</a> :: <span class="keyword">forall</span> v'1 targmax t. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` targmax, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> targmax)</li><li class="src short"><a href="#v:maxPoolWithArgmax-39-">maxPoolWithArgmax'</a> :: <span class="keyword">forall</span> v'1 targmax t. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` targmax, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> targmax)</li><li class="src short"><a href="#v:maximum">maximum</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:maximum-39-">maximum'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:mean">mean</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:mean-39-">mean'</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:merge">merge</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t] -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:merge-39-">merge'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t] -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:mergeSummary">mergeSummary</a> :: [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:mergeSummary-39-">mergeSummary'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:mergeV2Checkpoints">mergeV2Checkpoints</a> :: <span class="keyword">forall</span> v'1 v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:mergeV2Checkpoints-39-">mergeV2Checkpoints'</a> :: <span class="keyword">forall</span> v'1 v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:min">min</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:min-39-">min'</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:minimum">minimum</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:minimum-39-">minimum'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:mirrorPad">mirrorPad</a> :: <span class="keyword">forall</span> v'1 v'2 t tpaddings. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tpaddings -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:mirrorPad-39-">mirrorPad'</a> :: <span class="keyword">forall</span> v'1 v'2 t tpaddings. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tpaddings -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:mirrorPadGrad">mirrorPadGrad</a> :: <span class="keyword">forall</span> v'1 v'2 t tpaddings. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tpaddings -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:mirrorPadGrad-39-">mirrorPadGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 t tpaddings. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tpaddings -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:mod">mod</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:mod-39-">mod'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:mul">mul</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:mul-39-">mul'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:multinomial">multinomial</a> :: <span class="keyword">forall</span> v'1 v'2 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:multinomial-39-">multinomial'</a> :: <span class="keyword">forall</span> v'1 v'2 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:mutableDenseHashTable">mutableDenseHashTable</a> :: <span class="keyword">forall</span> v'1 key_dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> key_dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 key_dtype -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:mutableDenseHashTable-39-">mutableDenseHashTable'</a> :: <span class="keyword">forall</span> v'1 key_dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> key_dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 key_dtype -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:mutableHashTable">mutableHashTable</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:mutableHashTable-39-">mutableHashTable'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:mutableHashTableOfTensors">mutableHashTableOfTensors</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:mutableHashTableOfTensors-39-">mutableHashTableOfTensors'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:neg">neg</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:neg-39-">neg'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:negTrain">negTrain</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:negTrain-39-">negTrain'</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:nextIteration">nextIteration</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:nextIteration-39-">nextIteration'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:noOp">noOp</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:noOp-39-">noOp'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:nonMaxSuppression">nonMaxSuppression</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></li><li class="src short"><a href="#v:nonMaxSuppression-39-">nonMaxSuppression'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></li><li class="src short"><a href="#v:notEqual">notEqual</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:notEqual-39-">notEqual'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></li><li class="src short"><a href="#v:oneHot">oneHot</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t tI. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tI) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tI -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:oneHot-39-">oneHot'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t tI. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tI) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tI -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:pack">pack</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:pack-39-">pack'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:pad">pad</a> :: <span class="keyword">forall</span> v'1 v'2 t tpaddings. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tpaddings -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:pad-39-">pad'</a> :: <span class="keyword">forall</span> v'1 v'2 t tpaddings. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tpaddings -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:paddingFIFOQueue">paddingFIFOQueue</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>] -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:paddingFIFOQueue-39-">paddingFIFOQueue'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>] -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:paddingFIFOQueueV2">paddingFIFOQueueV2</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>] -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:paddingFIFOQueueV2-39-">paddingFIFOQueueV2'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>] -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:parallelConcat">parallelConcat</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:parallelConcat-39-">parallelConcat'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:parameterizedTruncatedNormal">parameterizedTruncatedNormal</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 dtype t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 dtype -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 dtype -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 dtype -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 dtype -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:parameterizedTruncatedNormal-39-">parameterizedTruncatedNormal'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 dtype t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 dtype -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 dtype -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 dtype -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 dtype -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:parseExample">parseExample</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 sparse_types tdense. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` sparse_types, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tdense) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'5 tdense -> ([<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> sparse_types, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tdense)</li><li class="src short"><a href="#v:parseExample-39-">parseExample'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 sparse_types tdense. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` sparse_types, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tdense) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'5 tdense -> ([<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> sparse_types, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tdense)</li><li class="src short"><a href="#v:parseSingleSequenceExample">parseSingleSequenceExample</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 v'7 v'8 context_sparse_types tcontext_dense feature_list_dense_types feature_list_sparse_types. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` context_sparse_types, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tcontext_dense, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` feature_list_dense_types, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` feature_list_sparse_types) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'7 tcontext_dense -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> ([<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> context_sparse_types, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tcontext_dense, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> feature_list_sparse_types, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> feature_list_dense_types)</li><li class="src short"><a href="#v:parseSingleSequenceExample-39-">parseSingleSequenceExample'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 v'7 v'8 context_sparse_types tcontext_dense feature_list_dense_types feature_list_sparse_types. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` context_sparse_types, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tcontext_dense, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` feature_list_dense_types, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` feature_list_sparse_types) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'7 tcontext_dense -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> ([<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> context_sparse_types, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tcontext_dense, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> feature_list_sparse_types, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> feature_list_dense_types)</li><li class="src short"><a href="#v:parseTensor">parseTensor</a> :: <span class="keyword">forall</span> v'1 out_type. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> out_type => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</li><li class="src short"><a href="#v:parseTensor-39-">parseTensor'</a> :: <span class="keyword">forall</span> v'1 out_type. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> out_type => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</li><li class="src short"><a href="#v:placeholder">placeholder</a> :: <span class="keyword">forall</span> dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</li><li class="src short"><a href="#v:placeholder-39-">placeholder'</a> :: <span class="keyword">forall</span> dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</li><li class="src short"><a href="#v:placeholderV2">placeholderV2</a> :: <span class="keyword">forall</span> dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</li><li class="src short"><a href="#v:placeholderV2-39-">placeholderV2'</a> :: <span class="keyword">forall</span> dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</li><li class="src short"><a href="#v:placeholderWithDefault">placeholderWithDefault</a> :: <span class="keyword">forall</span> v'1 dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 dtype -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</li><li class="src short"><a href="#v:placeholderWithDefault-39-">placeholderWithDefault'</a> :: <span class="keyword">forall</span> v'1 dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 dtype -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</li><li class="src short"><a href="#v:polygamma">polygamma</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:polygamma-39-">polygamma'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:pow">pow</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:pow-39-">pow'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:preventGradient">preventGradient</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:preventGradient-39-">preventGradient'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:print">print</a> :: <span class="keyword">forall</span> v'1 v'2 t u m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> u) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 u -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</li><li class="src short"><a href="#v:print-39-">print'</a> :: <span class="keyword">forall</span> v'1 v'2 t u m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> u) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 u -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</li><li class="src short"><a href="#v:priorityQueue">priorityQueue</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:priorityQueue-39-">priorityQueue'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:priorityQueueV2">priorityQueueV2</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:priorityQueueV2-39-">priorityQueueV2'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:prod">prod</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:prod-39-">prod'</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:qr">qr</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:qr-39-">qr'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:quantizeAndDequantize">quantizeAndDequantize</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:quantizeAndDequantize-39-">quantizeAndDequantize'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:quantizeDownAndShrinkRange">quantizeDownAndShrinkRange</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 tinput out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizeDownAndShrinkRange-39-">quantizeDownAndShrinkRange'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 tinput out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizeV2">quantizeV2</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizeV2-39-">quantizeV2'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedAvgPool">quantizedAvgPool</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedAvgPool-39-">quantizedAvgPool'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedBatchNormWithGlobalNormalization">quantizedBatchNormWithGlobalNormalization</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 v'7 v'8 v'9 v'10 v'11 v'12 v'13 v'14 v'15 tinput out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type) => <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'11 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'12 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'13 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'14 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'15 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedBatchNormWithGlobalNormalization-39-">quantizedBatchNormWithGlobalNormalization'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 v'7 v'8 v'9 v'10 v'11 v'12 v'13 v'14 v'15 tinput out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'11 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'12 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'13 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'14 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'15 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedBiasAdd">quantizedBiasAdd</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 t1 t2 out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t1, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t2, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t1 -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t2 -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedBiasAdd-39-">quantizedBiasAdd'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 t1 t2 out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t1, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t2, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t1 -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t2 -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedConcat">quantizedConcat</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>] -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedConcat-39-">quantizedConcat'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>] -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedConv2D">quantizedConv2D</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 tinput tfilter out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tfilter, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tfilter -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedConv2D-39-">quantizedConv2D'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 tinput tfilter out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tfilter, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tfilter -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedInstanceNorm">quantizedInstanceNorm</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedInstanceNorm-39-">quantizedInstanceNorm'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedMatMul">quantizedMatMul</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 t1 t2 toutput. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t1, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t2, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` toutput) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t1 -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t2 -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> toutput, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedMatMul-39-">quantizedMatMul'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 t1 t2 toutput. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t1, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t2, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` toutput) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t1 -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t2 -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> toutput, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedMaxPool">quantizedMaxPool</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedMaxPool-39-">quantizedMaxPool'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedRelu">quantizedRelu</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 tinput out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedRelu-39-">quantizedRelu'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 tinput out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedRelu6">quantizedRelu6</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 tinput out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedRelu6-39-">quantizedRelu6'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 tinput out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedReluX">quantizedReluX</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 tinput out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedReluX-39-">quantizedReluX'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 tinput out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedReshape">quantizedReshape</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t tshape. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tshape) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tshape -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:quantizedReshape-39-">quantizedReshape'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t tshape. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tshape) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tshape -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:queueClose">queueClose</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:queueClose-39-">queueClose'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:queueCloseV2">queueCloseV2</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:queueCloseV2-39-">queueCloseV2'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:queueDequeue">queueDequeue</a> :: <span class="keyword">forall</span> component_types m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</li><li class="src short"><a href="#v:queueDequeue-39-">queueDequeue'</a> :: <span class="keyword">forall</span> component_types m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</li><li class="src short"><a href="#v:queueDequeueMany">queueDequeueMany</a> :: <span class="keyword">forall</span> v'2 component_types m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</li><li class="src short"><a href="#v:queueDequeueMany-39-">queueDequeueMany'</a> :: <span class="keyword">forall</span> v'2 component_types m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</li><li class="src short"><a href="#v:queueDequeueManyV2">queueDequeueManyV2</a> :: <span class="keyword">forall</span> v'2 component_types m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</li><li class="src short"><a href="#v:queueDequeueManyV2-39-">queueDequeueManyV2'</a> :: <span class="keyword">forall</span> v'2 component_types m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</li><li class="src short"><a href="#v:queueDequeueUpTo">queueDequeueUpTo</a> :: <span class="keyword">forall</span> v'2 component_types m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</li><li class="src short"><a href="#v:queueDequeueUpTo-39-">queueDequeueUpTo'</a> :: <span class="keyword">forall</span> v'2 component_types m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</li><li class="src short"><a href="#v:queueDequeueUpToV2">queueDequeueUpToV2</a> :: <span class="keyword">forall</span> v'2 component_types m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</li><li class="src short"><a href="#v:queueDequeueUpToV2-39-">queueDequeueUpToV2'</a> :: <span class="keyword">forall</span> v'2 component_types m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</li><li class="src short"><a href="#v:queueDequeueV2">queueDequeueV2</a> :: <span class="keyword">forall</span> component_types m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</li><li class="src short"><a href="#v:queueDequeueV2-39-">queueDequeueV2'</a> :: <span class="keyword">forall</span> component_types m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</li><li class="src short"><a href="#v:queueEnqueue">queueEnqueue</a> :: <span class="keyword">forall</span> v'2 tcomponents m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tcomponents) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 tcomponents -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:queueEnqueue-39-">queueEnqueue'</a> :: <span class="keyword">forall</span> v'2 tcomponents m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tcomponents) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 tcomponents -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:queueEnqueueMany">queueEnqueueMany</a> :: <span class="keyword">forall</span> v'2 tcomponents m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tcomponents) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 tcomponents -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:queueEnqueueMany-39-">queueEnqueueMany'</a> :: <span class="keyword">forall</span> v'2 tcomponents m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tcomponents) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 tcomponents -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:queueEnqueueManyV2">queueEnqueueManyV2</a> :: <span class="keyword">forall</span> v'2 tcomponents m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tcomponents) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 tcomponents -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:queueEnqueueManyV2-39-">queueEnqueueManyV2'</a> :: <span class="keyword">forall</span> v'2 tcomponents m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tcomponents) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 tcomponents -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:queueEnqueueV2">queueEnqueueV2</a> :: <span class="keyword">forall</span> v'2 tcomponents m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tcomponents) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 tcomponents -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:queueEnqueueV2-39-">queueEnqueueV2'</a> :: <span class="keyword">forall</span> v'2 tcomponents m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tcomponents) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 tcomponents -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:queueSize">queueSize</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:queueSize-39-">queueSize'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:queueSizeV2">queueSizeV2</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:queueSizeV2-39-">queueSizeV2'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:rGBToHSV">rGBToHSV</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:rGBToHSV-39-">rGBToHSV'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:randomCrop">randomCrop</a> :: <span class="keyword">forall</span> v'1 v'2 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</li><li class="src short"><a href="#v:randomCrop-39-">randomCrop'</a> :: <span class="keyword">forall</span> v'1 v'2 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</li><li class="src short"><a href="#v:randomGamma">randomGamma</a> :: <span class="keyword">forall</span> v'1 v'2 s t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` s, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 s -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</li><li class="src short"><a href="#v:randomGamma-39-">randomGamma'</a> :: <span class="keyword">forall</span> v'1 v'2 s t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` s, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 s -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</li><li class="src short"><a href="#v:randomShuffle">randomShuffle</a> :: <span class="keyword">forall</span> v'1 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</li><li class="src short"><a href="#v:randomShuffle-39-">randomShuffle'</a> :: <span class="keyword">forall</span> v'1 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</li><li class="src short"><a href="#v:randomShuffleQueue">randomShuffleQueue</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>] -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:randomShuffleQueue-39-">randomShuffleQueue'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>] -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:randomShuffleQueueV2">randomShuffleQueueV2</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>] -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:randomShuffleQueueV2-39-">randomShuffleQueueV2'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>] -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:randomStandardNormal">randomStandardNormal</a> :: <span class="keyword">forall</span> v'1 dtype t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:randomStandardNormal-39-">randomStandardNormal'</a> :: <span class="keyword">forall</span> v'1 dtype t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:randomUniform">randomUniform</a> :: <span class="keyword">forall</span> v'1 dtype t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:randomUniform-39-">randomUniform'</a> :: <span class="keyword">forall</span> v'1 dtype t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:randomUniformInt">randomUniformInt</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 tout t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tout, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tout -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tout -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tout)</li><li class="src short"><a href="#v:randomUniformInt-39-">randomUniformInt'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 tout t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tout, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tout -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tout -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tout)</li><li class="src short"><a href="#v:range">range</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 tidx. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tidx => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tidx</li><li class="src short"><a href="#v:range-39-">range'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 tidx. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tidx => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tidx</li><li class="src short"><a href="#v:rank">rank</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></li><li class="src short"><a href="#v:rank-39-">rank'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></li><li class="src short"><a href="#v:readFile">readFile</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:readFile-39-">readFile'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:readVariableOp">readVariableOp</a> :: <span class="keyword">forall</span> dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:readVariableOp-39-">readVariableOp'</a> :: <span class="keyword">forall</span> dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:readerNumRecordsProduced">readerNumRecordsProduced</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:readerNumRecordsProduced-39-">readerNumRecordsProduced'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:readerNumRecordsProducedV2">readerNumRecordsProducedV2</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:readerNumRecordsProducedV2-39-">readerNumRecordsProducedV2'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:readerNumWorkUnitsCompleted">readerNumWorkUnitsCompleted</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:readerNumWorkUnitsCompleted-39-">readerNumWorkUnitsCompleted'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:readerNumWorkUnitsCompletedV2">readerNumWorkUnitsCompletedV2</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:readerNumWorkUnitsCompletedV2-39-">readerNumWorkUnitsCompletedV2'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:readerRead">readerRead</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:readerRead-39-">readerRead'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:readerReadUpTo">readerReadUpTo</a> :: <span class="keyword">forall</span> v'3 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:readerReadUpTo-39-">readerReadUpTo'</a> :: <span class="keyword">forall</span> v'3 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:readerReadUpToV2">readerReadUpToV2</a> :: <span class="keyword">forall</span> v'3 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:readerReadUpToV2-39-">readerReadUpToV2'</a> :: <span class="keyword">forall</span> v'3 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:readerReadV2">readerReadV2</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:readerReadV2-39-">readerReadV2'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:readerReset">readerReset</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:readerReset-39-">readerReset'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:readerResetV2">readerResetV2</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:readerResetV2-39-">readerResetV2'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:readerRestoreState">readerRestoreState</a> :: <span class="keyword">forall</span> v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:readerRestoreState-39-">readerRestoreState'</a> :: <span class="keyword">forall</span> v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:readerRestoreStateV2">readerRestoreStateV2</a> :: <span class="keyword">forall</span> v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:readerRestoreStateV2-39-">readerRestoreStateV2'</a> :: <span class="keyword">forall</span> v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:readerSerializeState">readerSerializeState</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:readerSerializeState-39-">readerSerializeState'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:readerSerializeStateV2">readerSerializeStateV2</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:readerSerializeStateV2-39-">readerSerializeStateV2'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:real">real</a> :: <span class="keyword">forall</span> v'1 t tout. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tout) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tout</li><li class="src short"><a href="#v:real-39-">real'</a> :: <span class="keyword">forall</span> v'1 t tout. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tout) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tout</li><li class="src short"><a href="#v:realDiv">realDiv</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:realDiv-39-">realDiv'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:reciprocal">reciprocal</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:reciprocal-39-">reciprocal'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:reciprocalGrad">reciprocalGrad</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:reciprocalGrad-39-">reciprocalGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:recordInput">recordInput</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:recordInput-39-">recordInput'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:reduceJoin">reduceJoin</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:reduceJoin-39-">reduceJoin'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:refEnter">refEnter</a> :: <span class="keyword">forall</span> t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:refEnter-39-">refEnter'</a> :: <span class="keyword">forall</span> t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:refExit">refExit</a> :: <span class="keyword">forall</span> t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:refExit-39-">refExit'</a> :: <span class="keyword">forall</span> t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:refIdentity">refIdentity</a> :: <span class="keyword">forall</span> t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:refIdentity-39-">refIdentity'</a> :: <span class="keyword">forall</span> t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:refMerge">refMerge</a> :: <span class="keyword">forall</span> t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t] -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:refMerge-39-">refMerge'</a> :: <span class="keyword">forall</span> t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t] -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:refNextIteration">refNextIteration</a> :: <span class="keyword">forall</span> t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:refNextIteration-39-">refNextIteration'</a> :: <span class="keyword">forall</span> t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:refSelect">refSelect</a> :: <span class="keyword">forall</span> v'1 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t] -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:refSelect-39-">refSelect'</a> :: <span class="keyword">forall</span> v'1 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t] -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:refSwitch">refSwitch</a> :: <span class="keyword">forall</span> v'2 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:refSwitch-39-">refSwitch'</a> :: <span class="keyword">forall</span> v'2 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:relu">relu</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:relu-39-">relu'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:relu6">relu6</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:relu6-39-">relu6'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:relu6Grad">relu6Grad</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:relu6Grad-39-">relu6Grad'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:reluGrad">reluGrad</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:reluGrad-39-">reluGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:requantizationRange">requantizationRange</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 tinput. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:requantizationRange-39-">requantizationRange'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 tinput. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:requantize">requantize</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 tinput out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:requantize-39-">requantize'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 tinput out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:reshape">reshape</a> :: <span class="keyword">forall</span> v'1 v'2 t tshape. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tshape) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tshape -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:reshape-39-">reshape'</a> :: <span class="keyword">forall</span> v'1 v'2 t tshape. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tshape) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tshape -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:resizeArea">resizeArea</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:resizeArea-39-">resizeArea'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:resizeBicubic">resizeBicubic</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:resizeBicubic-39-">resizeBicubic'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:resizeBilinear">resizeBilinear</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:resizeBilinear-39-">resizeBilinear'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:resizeBilinearGrad">resizeBilinearGrad</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:resizeBilinearGrad-39-">resizeBilinearGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:resizeNearestNeighbor">resizeNearestNeighbor</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:resizeNearestNeighbor-39-">resizeNearestNeighbor'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:resizeNearestNeighborGrad">resizeNearestNeighborGrad</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:resizeNearestNeighborGrad-39-">resizeNearestNeighborGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:resourceApplyAdadelta">resourceApplyAdadelta</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyAdadelta-39-">resourceApplyAdadelta'</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyAdagrad">resourceApplyAdagrad</a> :: <span class="keyword">forall</span> v'3 v'4 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyAdagrad-39-">resourceApplyAdagrad'</a> :: <span class="keyword">forall</span> v'3 v'4 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyAdagradDA">resourceApplyAdagradDA</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyAdagradDA-39-">resourceApplyAdagradDA'</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyAdam">resourceApplyAdam</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 v'9 v'10 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyAdam-39-">resourceApplyAdam'</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 v'9 v'10 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyCenteredRMSProp">resourceApplyCenteredRMSProp</a> :: <span class="keyword">forall</span> v'5 v'6 v'7 v'8 v'9 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyCenteredRMSProp-39-">resourceApplyCenteredRMSProp'</a> :: <span class="keyword">forall</span> v'5 v'6 v'7 v'8 v'9 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyFtrl">resourceApplyFtrl</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyFtrl-39-">resourceApplyFtrl'</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyGradientDescent">resourceApplyGradientDescent</a> :: <span class="keyword">forall</span> v'2 v'3 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyGradientDescent-39-">resourceApplyGradientDescent'</a> :: <span class="keyword">forall</span> v'2 v'3 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyMomentum">resourceApplyMomentum</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyMomentum-39-">resourceApplyMomentum'</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyProximalAdagrad">resourceApplyProximalAdagrad</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 v'6 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyProximalAdagrad-39-">resourceApplyProximalAdagrad'</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 v'6 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyProximalGradientDescent">resourceApplyProximalGradientDescent</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 v'5 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyProximalGradientDescent-39-">resourceApplyProximalGradientDescent'</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 v'5 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyRMSProp">resourceApplyRMSProp</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceApplyRMSProp-39-">resourceApplyRMSProp'</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceGather">resourceGather</a> :: <span class="keyword">forall</span> v'2 dtype tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:resourceGather-39-">resourceGather'</a> :: <span class="keyword">forall</span> v'2 dtype tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:resourceScatterAdd">resourceScatterAdd</a> :: <span class="keyword">forall</span> v'2 v'3 dtype tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 dtype -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceScatterAdd-39-">resourceScatterAdd'</a> :: <span class="keyword">forall</span> v'2 v'3 dtype tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 dtype -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceSparseApplyAdadelta">resourceSparseApplyAdadelta</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 tindices -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceSparseApplyAdadelta-39-">resourceSparseApplyAdadelta'</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 tindices -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceSparseApplyAdagrad">resourceSparseApplyAdagrad</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceSparseApplyAdagrad-39-">resourceSparseApplyAdagrad'</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceSparseApplyAdagradDA">resourceSparseApplyAdagradDA</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 v'9 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceSparseApplyAdagradDA-39-">resourceSparseApplyAdagradDA'</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 v'9 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceSparseApplyCenteredRMSProp">resourceSparseApplyCenteredRMSProp</a> :: <span class="keyword">forall</span> v'5 v'6 v'7 v'8 v'9 v'10 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 tindices -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceSparseApplyCenteredRMSProp-39-">resourceSparseApplyCenteredRMSProp'</a> :: <span class="keyword">forall</span> v'5 v'6 v'7 v'8 v'9 v'10 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 tindices -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceSparseApplyFtrl">resourceSparseApplyFtrl</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 v'9 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceSparseApplyFtrl-39-">resourceSparseApplyFtrl'</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 v'9 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceSparseApplyMomentum">resourceSparseApplyMomentum</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 v'6 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceSparseApplyMomentum-39-">resourceSparseApplyMomentum'</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 v'6 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceSparseApplyProximalAdagrad">resourceSparseApplyProximalAdagrad</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 v'6 v'7 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 tindices -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceSparseApplyProximalAdagrad-39-">resourceSparseApplyProximalAdagrad'</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 v'6 v'7 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 tindices -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceSparseApplyProximalGradientDescent">resourceSparseApplyProximalGradientDescent</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 v'5 v'6 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 tindices -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceSparseApplyProximalGradientDescent-39-">resourceSparseApplyProximalGradientDescent'</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 v'5 v'6 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 tindices -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceSparseApplyRMSProp">resourceSparseApplyRMSProp</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 v'9 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 tindices -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:resourceSparseApplyRMSProp-39-">resourceSparseApplyRMSProp'</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 v'9 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 tindices -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:restore">restore</a> :: <span class="keyword">forall</span> v'1 v'2 dt. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dt => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dt</li><li class="src short"><a href="#v:restore-39-">restore'</a> :: <span class="keyword">forall</span> v'1 v'2 dt. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dt => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dt</li><li class="src short"><a href="#v:restoreSlice">restoreSlice</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 dt. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dt => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dt</li><li class="src short"><a href="#v:restoreSlice-39-">restoreSlice'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 dt. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dt => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dt</li><li class="src short"><a href="#v:restoreV2">restoreV2</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 dtypes. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> dtypes => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtypes</li><li class="src short"><a href="#v:restoreV2-39-">restoreV2'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 dtypes. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> dtypes => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtypes</li><li class="src short"><a href="#v:reverse">reverse</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:reverse-39-">reverse'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:reverseSequence">reverseSequence</a> :: <span class="keyword">forall</span> v'1 v'2 t tlen. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tlen) => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tlen -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:reverseSequence-39-">reverseSequence'</a> :: <span class="keyword">forall</span> v'1 v'2 t tlen. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tlen) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tlen -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:reverseV2">reverseV2</a> :: <span class="keyword">forall</span> v'1 v'2 tidx t. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:reverseV2-39-">reverseV2'</a> :: <span class="keyword">forall</span> v'1 v'2 tidx t. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:rint">rint</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:rint-39-">rint'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:round">round</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:round-39-">round'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:rsqrt">rsqrt</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:rsqrt-39-">rsqrt'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:rsqrtGrad">rsqrtGrad</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:rsqrtGrad-39-">rsqrtGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sampleDistortedBoundingBox">sampleDistortedBoundingBox</a> :: <span class="keyword">forall</span> v'1 v'2 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:sampleDistortedBoundingBox-39-">sampleDistortedBoundingBox'</a> :: <span class="keyword">forall</span> v'1 v'2 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:save">save</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'3 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:save-39-">save'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'3 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:saveSlices">saveSlices</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'4 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:saveSlices-39-">saveSlices'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'4 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:saveV2">saveV2</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 dtypes m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> dtypes) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'4 dtypes -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:saveV2-39-">saveV2'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 dtypes m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> dtypes) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'4 dtypes -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:scalarSummary">scalarSummary</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:scalarSummary-39-">scalarSummary'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:scatterAdd">scatterAdd</a> :: <span class="keyword">forall</span> v'2 v'3 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:scatterAdd-39-">scatterAdd'</a> :: <span class="keyword">forall</span> v'2 v'3 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:scatterDiv">scatterDiv</a> :: <span class="keyword">forall</span> v'2 v'3 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:scatterDiv-39-">scatterDiv'</a> :: <span class="keyword">forall</span> v'2 v'3 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:scatterMul">scatterMul</a> :: <span class="keyword">forall</span> v'2 v'3 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:scatterMul-39-">scatterMul'</a> :: <span class="keyword">forall</span> v'2 v'3 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:scatterNd">scatterNd</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:scatterNd-39-">scatterNd'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:scatterNdAdd">scatterNdAdd</a> :: <span class="keyword">forall</span> v'2 v'3 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:scatterNdAdd-39-">scatterNdAdd'</a> :: <span class="keyword">forall</span> v'2 v'3 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:scatterNdSub">scatterNdSub</a> :: <span class="keyword">forall</span> v'2 v'3 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:scatterNdSub-39-">scatterNdSub'</a> :: <span class="keyword">forall</span> v'2 v'3 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:scatterNdUpdate">scatterNdUpdate</a> :: <span class="keyword">forall</span> v'2 v'3 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:scatterNdUpdate-39-">scatterNdUpdate'</a> :: <span class="keyword">forall</span> v'2 v'3 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:scatterSub">scatterSub</a> :: <span class="keyword">forall</span> v'2 v'3 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:scatterSub-39-">scatterSub'</a> :: <span class="keyword">forall</span> v'2 v'3 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:scatterUpdate">scatterUpdate</a> :: <span class="keyword">forall</span> v'2 v'3 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:scatterUpdate-39-">scatterUpdate'</a> :: <span class="keyword">forall</span> v'2 v'3 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sdcaFprint">sdcaFprint</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></li><li class="src short"><a href="#v:sdcaFprint-39-">sdcaFprint'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></li><li class="src short"><a href="#v:sdcaOptimizer">sdcaOptimizer</a> :: <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>])</li><li class="src short"><a href="#v:sdcaOptimizer-39-">sdcaOptimizer'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>])</li><li class="src short"><a href="#v:sdcaShrinkL1">sdcaShrinkL1</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>] -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:sdcaShrinkL1-39-">sdcaShrinkL1'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>] -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:segmentMax">segmentMax</a> :: <span class="keyword">forall</span> v'1 v'2 t tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:segmentMax-39-">segmentMax'</a> :: <span class="keyword">forall</span> v'1 v'2 t tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:segmentMean">segmentMean</a> :: <span class="keyword">forall</span> v'1 v'2 t tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:segmentMean-39-">segmentMean'</a> :: <span class="keyword">forall</span> v'1 v'2 t tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:segmentMin">segmentMin</a> :: <span class="keyword">forall</span> v'1 v'2 t tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:segmentMin-39-">segmentMin'</a> :: <span class="keyword">forall</span> v'1 v'2 t tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:segmentProd">segmentProd</a> :: <span class="keyword">forall</span> v'1 v'2 t tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:segmentProd-39-">segmentProd'</a> :: <span class="keyword">forall</span> v'1 v'2 t tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:segmentSum">segmentSum</a> :: <span class="keyword">forall</span> v'1 v'2 t tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:segmentSum-39-">segmentSum'</a> :: <span class="keyword">forall</span> v'1 v'2 t tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:select">select</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:select-39-">select'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:selfAdjointEig">selfAdjointEig</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:selfAdjointEig-39-">selfAdjointEig'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:selfAdjointEigV2">selfAdjointEigV2</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:selfAdjointEigV2-39-">selfAdjointEigV2'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:serializeManySparse">serializeManySparse</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:serializeManySparse-39-">serializeManySparse'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:serializeSparse">serializeSparse</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:serializeSparse-39-">serializeSparse'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:setSize">setSize</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></li><li class="src short"><a href="#v:setSize-39-">setSize'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></li><li class="src short"><a href="#v:shape">shape</a> :: <span class="keyword">forall</span> v'1 t out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</li><li class="src short"><a href="#v:shape-39-">shape'</a> :: <span class="keyword">forall</span> v'1 t out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</li><li class="src short"><a href="#v:shapeN">shapeN</a> :: <span class="keyword">forall</span> v'1 t out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_type) => [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type]</li><li class="src short"><a href="#v:shapeN-39-">shapeN'</a> :: <span class="keyword">forall</span> v'1 t out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type]</li><li class="src short"><a href="#v:shardedFilename">shardedFilename</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:shardedFilename-39-">shardedFilename'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:shardedFilespec">shardedFilespec</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:shardedFilespec-39-">shardedFilespec'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:sigmoid">sigmoid</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sigmoid-39-">sigmoid'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sigmoidGrad">sigmoidGrad</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sigmoidGrad-39-">sigmoidGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sign">sign</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sign-39-">sign'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sin">sin</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sin-39-">sin'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:size">size</a> :: <span class="keyword">forall</span> v'1 t out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</li><li class="src short"><a href="#v:size-39-">size'</a> :: <span class="keyword">forall</span> v'1 t out_type. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</li><li class="src short"><a href="#v:skipgram">skipgram</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:skipgram-39-">skipgram'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:slice">slice</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t index. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` index) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:slice-39-">slice'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t index. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` index) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:softmax">softmax</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:softmax-39-">softmax'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:softmaxCrossEntropyWithLogits">softmaxCrossEntropyWithLogits</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:softmaxCrossEntropyWithLogits-39-">softmaxCrossEntropyWithLogits'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:softplus">softplus</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:softplus-39-">softplus'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:softplusGrad">softplusGrad</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:softplusGrad-39-">softplusGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:softsign">softsign</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:softsign-39-">softsign'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:softsignGrad">softsignGrad</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:softsignGrad-39-">softsignGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:spaceToBatch">spaceToBatch</a> :: <span class="keyword">forall</span> v'1 v'2 t tpaddings. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings) => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tpaddings -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:spaceToBatch-39-">spaceToBatch'</a> :: <span class="keyword">forall</span> v'1 v'2 t tpaddings. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tpaddings -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:spaceToBatchND">spaceToBatchND</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t tblock_shape tpaddings. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tblock_shape, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tblock_shape -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tpaddings -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:spaceToBatchND-39-">spaceToBatchND'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t tblock_shape tpaddings. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tblock_shape, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tblock_shape -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tpaddings -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:spaceToDepth">spaceToDepth</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:spaceToDepth-39-">spaceToDepth'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseAccumulatorApplyGradient">sparseAccumulatorApplyGradient</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 v'5 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype) => <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 dtype -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:sparseAccumulatorApplyGradient-39-">sparseAccumulatorApplyGradient'</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 v'5 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 dtype -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:sparseAccumulatorTakeGradient">sparseAccumulatorTakeGradient</a> :: <span class="keyword">forall</span> v'2 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:sparseAccumulatorTakeGradient-39-">sparseAccumulatorTakeGradient'</a> :: <span class="keyword">forall</span> v'2 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:sparseAdd">sparseAdd</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 v'7 t treal. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` treal) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 treal -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:sparseAdd-39-">sparseAdd'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 v'7 t treal. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` treal) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 treal -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:sparseAddGrad">sparseAddGrad</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:sparseAddGrad-39-">sparseAddGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:sparseApplyAdadelta">sparseApplyAdadelta</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 tindices -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sparseApplyAdadelta-39-">sparseApplyAdadelta'</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 tindices -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sparseApplyAdagrad">sparseApplyAdagrad</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sparseApplyAdagrad-39-">sparseApplyAdagrad'</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sparseApplyAdagradDA">sparseApplyAdagradDA</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 v'9 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sparseApplyAdagradDA-39-">sparseApplyAdagradDA'</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 v'9 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sparseApplyCenteredRMSProp">sparseApplyCenteredRMSProp</a> :: <span class="keyword">forall</span> v'5 v'6 v'7 v'8 v'9 v'10 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 tindices -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sparseApplyCenteredRMSProp-39-">sparseApplyCenteredRMSProp'</a> :: <span class="keyword">forall</span> v'5 v'6 v'7 v'8 v'9 v'10 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 tindices -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sparseApplyFtrl">sparseApplyFtrl</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 v'9 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sparseApplyFtrl-39-">sparseApplyFtrl'</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 v'9 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sparseApplyMomentum">sparseApplyMomentum</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 v'6 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sparseApplyMomentum-39-">sparseApplyMomentum'</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 v'6 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sparseApplyProximalAdagrad">sparseApplyProximalAdagrad</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 v'6 v'7 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 tindices -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sparseApplyProximalAdagrad-39-">sparseApplyProximalAdagrad'</a> :: <span class="keyword">forall</span> v'3 v'4 v'5 v'6 v'7 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 tindices -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sparseApplyProximalGradientDescent">sparseApplyProximalGradientDescent</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 v'5 v'6 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 tindices -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sparseApplyProximalGradientDescent-39-">sparseApplyProximalGradientDescent'</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 v'5 v'6 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 tindices -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sparseApplyRMSProp">sparseApplyRMSProp</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 v'9 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 tindices -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sparseApplyRMSProp-39-">sparseApplyRMSProp'</a> :: <span class="keyword">forall</span> v'4 v'5 v'6 v'7 v'8 v'9 t tindices m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 tindices -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:sparseConcat">sparseConcat</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>] -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:sparseConcat-39-">sparseConcat'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t] -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>] -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:sparseConditionalAccumulator">sparseConditionalAccumulator</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:sparseConditionalAccumulator-39-">sparseConditionalAccumulator'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:sparseDenseCwiseAdd">sparseDenseCwiseAdd</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseDenseCwiseAdd-39-">sparseDenseCwiseAdd'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseDenseCwiseDiv">sparseDenseCwiseDiv</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseDenseCwiseDiv-39-">sparseDenseCwiseDiv'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseDenseCwiseMul">sparseDenseCwiseMul</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseDenseCwiseMul-39-">sparseDenseCwiseMul'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseMatMul">sparseMatMul</a> :: <span class="keyword">forall</span> v'1 v'2 ta tb. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` ta, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tb) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 ta -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tb -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:sparseMatMul-39-">sparseMatMul'</a> :: <span class="keyword">forall</span> v'1 v'2 ta tb. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` ta, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tb) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 ta -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tb -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:sparseReduceSum">sparseReduceSum</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseReduceSum-39-">sparseReduceSum'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseReduceSumSparse">sparseReduceSumSparse</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:sparseReduceSumSparse-39-">sparseReduceSumSparse'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:sparseReorder">sparseReorder</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:sparseReorder-39-">sparseReorder'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:sparseReshape">sparseReshape</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:sparseReshape-39-">sparseReshape'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:sparseSegmentMean">sparseSegmentMean</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseSegmentMean-39-">sparseSegmentMean'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseSegmentMeanGrad">sparseSegmentMeanGrad</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseSegmentMeanGrad-39-">sparseSegmentMeanGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseSegmentSqrtN">sparseSegmentSqrtN</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseSegmentSqrtN-39-">sparseSegmentSqrtN'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseSegmentSqrtNGrad">sparseSegmentSqrtNGrad</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseSegmentSqrtNGrad-39-">sparseSegmentSqrtNGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseSegmentSum">sparseSegmentSum</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseSegmentSum-39-">sparseSegmentSum'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseSoftmax">sparseSoftmax</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseSoftmax-39-">sparseSoftmax'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseSoftmaxCrossEntropyWithLogits">sparseSoftmaxCrossEntropyWithLogits</a> :: <span class="keyword">forall</span> v'1 v'2 t tlabels. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tlabels) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tlabels -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:sparseSoftmaxCrossEntropyWithLogits-39-">sparseSoftmaxCrossEntropyWithLogits'</a> :: <span class="keyword">forall</span> v'1 v'2 t tlabels. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tlabels) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tlabels -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:sparseSparseMaximum">sparseSparseMaximum</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:sparseSparseMaximum-39-">sparseSparseMaximum'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:sparseSparseMinimum">sparseSparseMinimum</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:sparseSparseMinimum-39-">sparseSparseMinimum'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:sparseSplit">sparseSplit</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> ([<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>])</li><li class="src short"><a href="#v:sparseSplit-39-">sparseSplit'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> ([<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>])</li><li class="src short"><a href="#v:sparseTensorDenseAdd">sparseTensorDenseAdd</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseTensorDenseAdd-39-">sparseTensorDenseAdd'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseTensorDenseMatMul">sparseTensorDenseMatMul</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseTensorDenseMatMul-39-">sparseTensorDenseMatMul'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseToDense">sparseToDense</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseToDense-39-">sparseToDense'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sparseToSparseSetOperation">sparseToSparseSetOperation</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:sparseToSparseSetOperation-39-">sparseToSparseSetOperation'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 v'6 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:split">split</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</li><li class="src short"><a href="#v:split-39-">split'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</li><li class="src short"><a href="#v:splitV">splitV</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t tlen. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tlen) => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tlen -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</li><li class="src short"><a href="#v:splitV-39-">splitV'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t tlen. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tlen) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tlen -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</li><li class="src short"><a href="#v:sqrt">sqrt</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sqrt-39-">sqrt'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sqrtGrad">sqrtGrad</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sqrtGrad-39-">sqrtGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:square">square</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:square-39-">square'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:squaredDifference">squaredDifference</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:squaredDifference-39-">squaredDifference'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:squeeze">squeeze</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:squeeze-39-">squeeze'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:stack">stack</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:stack-39-">stack'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:stackClose">stackClose</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:stackClose-39-">stackClose'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:stackPop">stackPop</a> :: <span class="keyword">forall</span> elem_type m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> elem_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> elem_type)</li><li class="src short"><a href="#v:stackPop-39-">stackPop'</a> :: <span class="keyword">forall</span> elem_type m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> elem_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> elem_type)</li><li class="src short"><a href="#v:stackPush">stackPush</a> :: <span class="keyword">forall</span> v'2 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</li><li class="src short"><a href="#v:stackPush-39-">stackPush'</a> :: <span class="keyword">forall</span> v'2 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</li><li class="src short"><a href="#v:stage">stage</a> :: <span class="keyword">forall</span> v'1 dtypes m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> dtypes) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'1 dtypes -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:stage-39-">stage'</a> :: <span class="keyword">forall</span> v'1 dtypes m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> dtypes) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'1 dtypes -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:stopGradient">stopGradient</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:stopGradient-39-">stopGradient'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:stridedSlice">stridedSlice</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t index. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` index) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:stridedSlice-39-">stridedSlice'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t index. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` index) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:stridedSliceAssign">stridedSliceAssign</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 v'5 t index m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` index) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:stridedSliceAssign-39-">stridedSliceAssign'</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 v'5 t index m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` index) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</li><li class="src short"><a href="#v:stridedSliceGrad">stridedSliceGrad</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 t index. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` index) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:stridedSliceGrad-39-">stridedSliceGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 v'5 t index. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` index) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 index -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:stringJoin">stringJoin</a> :: [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:stringJoin-39-">stringJoin'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:stringSplit">stringSplit</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:stringSplit-39-">stringSplit'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:stringToHashBucket">stringToHashBucket</a> :: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></li><li class="src short"><a href="#v:stringToHashBucket-39-">stringToHashBucket'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></li><li class="src short"><a href="#v:stringToHashBucketFast">stringToHashBucketFast</a> :: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></li><li class="src short"><a href="#v:stringToHashBucketFast-39-">stringToHashBucketFast'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></li><li class="src short"><a href="#v:stringToHashBucketStrong">stringToHashBucketStrong</a> :: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></li><li class="src short"><a href="#v:stringToHashBucketStrong-39-">stringToHashBucketStrong'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></li><li class="src short"><a href="#v:stringToNumber">stringToNumber</a> :: <span class="keyword">forall</span> v'1 out_type. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` out_type => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</li><li class="src short"><a href="#v:stringToNumber-39-">stringToNumber'</a> :: <span class="keyword">forall</span> v'1 out_type. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` out_type => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</li><li class="src short"><a href="#v:sub">sub</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sub-39-">sub'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:substr">substr</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:substr-39-">substr'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:sum">sum</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:sum-39-">sum'</a> :: <span class="keyword">forall</span> v'1 v'2 t tidx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:svd">svd</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:svd-39-">svd'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:switch">switch</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:switch-39-">switch'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</li><li class="src short"><a href="#v:tFRecordReader">tFRecordReader</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:tFRecordReader-39-">tFRecordReader'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:tFRecordReaderV2">tFRecordReaderV2</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:tFRecordReaderV2-39-">tFRecordReaderV2'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:takeManySparseFromTensorsMap">takeManySparseFromTensorsMap</a> :: <span class="keyword">forall</span> v'1 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:takeManySparseFromTensorsMap-39-">takeManySparseFromTensorsMap'</a> :: <span class="keyword">forall</span> v'1 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:tan">tan</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:tan-39-">tan'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:tanh">tanh</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:tanh-39-">tanh'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:tanhGrad">tanhGrad</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:tanhGrad-39-">tanhGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:temporaryVariable">temporaryVariable</a> :: <span class="keyword">forall</span> dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> dtype)</li><li class="src short"><a href="#v:temporaryVariable-39-">temporaryVariable'</a> :: <span class="keyword">forall</span> dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> dtype)</li><li class="src short"><a href="#v:tensorArray">tensorArray</a> :: <span class="keyword">forall</span> v'1 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:tensorArray-39-">tensorArray'</a> :: <span class="keyword">forall</span> v'1 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:tensorArrayClose">tensorArrayClose</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:tensorArrayClose-39-">tensorArrayClose'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:tensorArrayCloseV2">tensorArrayCloseV2</a> :: <span class="keyword">forall</span> v'1 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:tensorArrayCloseV2-39-">tensorArrayCloseV2'</a> :: <span class="keyword">forall</span> v'1 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:tensorArrayCloseV3">tensorArrayCloseV3</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:tensorArrayCloseV3-39-">tensorArrayCloseV3'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:tensorArrayConcat">tensorArrayConcat</a> :: <span class="keyword">forall</span> v'2 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:tensorArrayConcat-39-">tensorArrayConcat'</a> :: <span class="keyword">forall</span> v'2 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:tensorArrayConcatV2">tensorArrayConcatV2</a> :: <span class="keyword">forall</span> v'1 v'2 dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:tensorArrayConcatV2-39-">tensorArrayConcatV2'</a> :: <span class="keyword">forall</span> v'1 v'2 dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:tensorArrayConcatV3">tensorArrayConcatV3</a> :: <span class="keyword">forall</span> v'2 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:tensorArrayConcatV3-39-">tensorArrayConcatV3'</a> :: <span class="keyword">forall</span> v'2 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</li><li class="src short"><a href="#v:tensorArrayGather">tensorArrayGather</a> :: <span class="keyword">forall</span> v'2 v'3 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:tensorArrayGather-39-">tensorArrayGather'</a> :: <span class="keyword">forall</span> v'2 v'3 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:tensorArrayGatherV2">tensorArrayGatherV2</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</li><li class="src short"><a href="#v:tensorArrayGatherV2-39-">tensorArrayGatherV2'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</li><li class="src short"><a href="#v:tensorArrayGatherV3">tensorArrayGatherV3</a> :: <span class="keyword">forall</span> v'2 v'3 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:tensorArrayGatherV3-39-">tensorArrayGatherV3'</a> :: <span class="keyword">forall</span> v'2 v'3 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:tensorArrayGrad">tensorArrayGrad</a> :: <span class="keyword">forall</span> v'1 v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:tensorArrayGrad-39-">tensorArrayGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:tensorArrayGradV2">tensorArrayGradV2</a> :: <span class="keyword">forall</span> v'1 v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:tensorArrayGradV2-39-">tensorArrayGradV2'</a> :: <span class="keyword">forall</span> v'1 v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:tensorArrayGradV3">tensorArrayGradV3</a> :: <span class="keyword">forall</span> v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tensorArrayGradV3-39-">tensorArrayGradV3'</a> :: <span class="keyword">forall</span> v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tensorArrayPack">tensorArrayPack</a> :: <span class="keyword">forall</span> v'2 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:tensorArrayPack-39-">tensorArrayPack'</a> :: <span class="keyword">forall</span> v'2 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:tensorArrayRead">tensorArrayRead</a> :: <span class="keyword">forall</span> v'2 v'3 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:tensorArrayRead-39-">tensorArrayRead'</a> :: <span class="keyword">forall</span> v'2 v'3 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:tensorArrayReadV2">tensorArrayReadV2</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</li><li class="src short"><a href="#v:tensorArrayReadV2-39-">tensorArrayReadV2'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 dtype. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</li><li class="src short"><a href="#v:tensorArrayReadV3">tensorArrayReadV3</a> :: <span class="keyword">forall</span> v'2 v'3 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:tensorArrayReadV3-39-">tensorArrayReadV3'</a> :: <span class="keyword">forall</span> v'2 v'3 dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:tensorArrayScatter">tensorArrayScatter</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tensorArrayScatter-39-">tensorArrayScatter'</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tensorArrayScatterV2">tensorArrayScatterV2</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:tensorArrayScatterV2-39-">tensorArrayScatterV2'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:tensorArrayScatterV3">tensorArrayScatterV3</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tensorArrayScatterV3-39-">tensorArrayScatterV3'</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tensorArraySize">tensorArraySize</a> :: <span class="keyword">forall</span> v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:tensorArraySize-39-">tensorArraySize'</a> :: <span class="keyword">forall</span> v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:tensorArraySizeV2">tensorArraySizeV2</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></li><li class="src short"><a href="#v:tensorArraySizeV2-39-">tensorArraySizeV2'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></li><li class="src short"><a href="#v:tensorArraySizeV3">tensorArraySizeV3</a> :: <span class="keyword">forall</span> v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:tensorArraySizeV3-39-">tensorArraySizeV3'</a> :: <span class="keyword">forall</span> v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:tensorArraySplit">tensorArraySplit</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tensorArraySplit-39-">tensorArraySplit'</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tensorArraySplitV2">tensorArraySplitV2</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:tensorArraySplitV2-39-">tensorArraySplitV2'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:tensorArraySplitV3">tensorArraySplitV3</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tensorArraySplitV3-39-">tensorArraySplitV3'</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tensorArrayUnpack">tensorArrayUnpack</a> :: <span class="keyword">forall</span> v'2 v'3 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tensorArrayUnpack-39-">tensorArrayUnpack'</a> :: <span class="keyword">forall</span> v'2 v'3 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tensorArrayV2">tensorArrayV2</a> :: <span class="keyword">forall</span> v'1 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:tensorArrayV2-39-">tensorArrayV2'</a> :: <span class="keyword">forall</span> v'1 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:tensorArrayV3">tensorArrayV3</a> :: <span class="keyword">forall</span> v'1 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tensorArrayV3-39-">tensorArrayV3'</a> :: <span class="keyword">forall</span> v'1 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tensorArrayWrite">tensorArrayWrite</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tensorArrayWrite-39-">tensorArrayWrite'</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tensorArrayWriteV2">tensorArrayWriteV2</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:tensorArrayWriteV2-39-">tensorArrayWriteV2'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 v'4 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></li><li class="src short"><a href="#v:tensorArrayWriteV3">tensorArrayWriteV3</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tensorArrayWriteV3-39-">tensorArrayWriteV3'</a> :: <span class="keyword">forall</span> v'2 v'3 v'4 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tensorSummary">tensorSummary</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:tensorSummary-39-">tensorSummary'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></li><li class="src short"><a href="#v:textLineReader">textLineReader</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:textLineReader-39-">textLineReader'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:textLineReaderV2">textLineReaderV2</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:textLineReaderV2-39-">textLineReaderV2'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:threadUnsafeUnigramCandidateSampler">threadUnsafeUnigramCandidateSampler</a> :: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:threadUnsafeUnigramCandidateSampler-39-">threadUnsafeUnigramCandidateSampler'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:tile">tile</a> :: <span class="keyword">forall</span> v'1 v'2 t tmultiples. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tmultiples) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tmultiples -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:tile-39-">tile'</a> :: <span class="keyword">forall</span> v'1 v'2 t tmultiples. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tmultiples) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tmultiples -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:tileGrad">tileGrad</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:tileGrad-39-">tileGrad'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:topK">topK</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:topK-39-">topK'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:topKV2">topKV2</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:topKV2-39-">topKV2'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</li><li class="src short"><a href="#v:transpose">transpose</a> :: <span class="keyword">forall</span> v'1 v'2 t tperm. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tperm) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tperm -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:transpose-39-">transpose'</a> :: <span class="keyword">forall</span> v'1 v'2 t tperm. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tperm) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tperm -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:truncateDiv">truncateDiv</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:truncateDiv-39-">truncateDiv'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:truncateMod">truncateMod</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:truncateMod-39-">truncateMod'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:truncatedNormal">truncatedNormal</a> :: <span class="keyword">forall</span> v'1 dtype t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:truncatedNormal-39-">truncatedNormal'</a> :: <span class="keyword">forall</span> v'1 dtype t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:uniformCandidateSampler">uniformCandidateSampler</a> :: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:uniformCandidateSampler-39-">uniformCandidateSampler'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</li><li class="src short"><a href="#v:unique">unique</a> :: <span class="keyword">forall</span> v'1 t out_idx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_idx) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_idx)</li><li class="src short"><a href="#v:unique-39-">unique'</a> :: <span class="keyword">forall</span> v'1 t out_idx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_idx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_idx)</li><li class="src short"><a href="#v:uniqueWithCounts">uniqueWithCounts</a> :: <span class="keyword">forall</span> v'1 t out_idx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_idx) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_idx, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_idx)</li><li class="src short"><a href="#v:uniqueWithCounts-39-">uniqueWithCounts'</a> :: <span class="keyword">forall</span> v'1 t out_idx. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_idx) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_idx, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_idx)</li><li class="src short"><a href="#v:unpack">unpack</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</li><li class="src short"><a href="#v:unpack-39-">unpack'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</li><li class="src short"><a href="#v:unsortedSegmentSum">unsortedSegmentSum</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:unsortedSegmentSum-39-">unsortedSegmentSum'</a> :: <span class="keyword">forall</span> v'1 v'2 v'3 t tindices. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:unstage">unstage</a> :: <span class="keyword">forall</span> dtypes m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> dtypes) => m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtypes)</li><li class="src short"><a href="#v:unstage-39-">unstage'</a> :: <span class="keyword">forall</span> dtypes m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> dtypes) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtypes)</li><li class="src short"><a href="#v:varHandleOp">varHandleOp</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:varHandleOp-39-">varHandleOp'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:varIsInitializedOp">varIsInitializedOp</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>)</li><li class="src short"><a href="#v:varIsInitializedOp-39-">varIsInitializedOp'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>)</li><li class="src short"><a href="#v:variable">variable</a> :: <span class="keyword">forall</span> dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> dtype)</li><li class="src short"><a href="#v:variable-39-">variable'</a> :: <span class="keyword">forall</span> dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> dtype)</li><li class="src short"><a href="#v:variableV2">variableV2</a> :: <span class="keyword">forall</span> dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> dtype)</li><li class="src short"><a href="#v:variableV2-39-">variableV2'</a> :: <span class="keyword">forall</span> dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> dtype)</li><li class="src short"><a href="#v:where-39-">where'</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></li><li class="src short"><a href="#v:where-39--39-">where''</a> :: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></li><li class="src short"><a href="#v:wholeFileReader">wholeFileReader</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:wholeFileReader-39-">wholeFileReader'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</li><li class="src short"><a href="#v:wholeFileReaderV2">wholeFileReaderV2</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:wholeFileReaderV2-39-">wholeFileReaderV2'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></li><li class="src short"><a href="#v:writeFile">writeFile</a> :: <span class="keyword">forall</span> v'1 v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:writeFile-39-">writeFile'</a> :: <span class="keyword">forall</span> v'1 v'2 m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:zerosLike">zerosLike</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:zerosLike-39-">zerosLike'</a> :: <span class="keyword">forall</span> v'1 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:zeta">zeta</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:zeta-39-">zeta'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:_Arg">_Arg</a> :: <span class="keyword">forall</span> t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</li><li class="src short"><a href="#v:_Arg-39-">_Arg'</a> :: <span class="keyword">forall</span> t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</li><li class="src short"><a href="#v:_ArrayToList">_ArrayToList</a> :: <span class="keyword">forall</span> v'1 t out_types. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> out_types) => [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_types</li><li class="src short"><a href="#v:_ArrayToList-39-">_ArrayToList'</a> :: <span class="keyword">forall</span> v'1 t out_types. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> out_types) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t] -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_types</li><li class="src short"><a href="#v:_HostCast">_HostCast</a> :: <span class="keyword">forall</span> v'1 srcT dstT. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> srcT, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dstT) => <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 srcT -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dstT</li><li class="src short"><a href="#v:_HostCast-39-">_HostCast'</a> :: <span class="keyword">forall</span> v'1 srcT dstT. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> srcT, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dstT) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 srcT -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dstT</li><li class="src short"><a href="#v:_HostRecv">_HostRecv</a> :: <span class="keyword">forall</span> tensor_type m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tensor_type) => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tensor_type)</li><li class="src short"><a href="#v:_HostRecv-39-">_HostRecv'</a> :: <span class="keyword">forall</span> tensor_type m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tensor_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tensor_type)</li><li class="src short"><a href="#v:_HostSend">_HostSend</a> :: <span class="keyword">forall</span> v'1 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:_HostSend-39-">_HostSend'</a> :: <span class="keyword">forall</span> v'1 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:_ListToArray">_ListToArray</a> :: <span class="keyword">forall</span> v'1 tin t. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tin, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'1 tin -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</li><li class="src short"><a href="#v:_ListToArray-39-">_ListToArray'</a> :: <span class="keyword">forall</span> v'1 tin t. (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tin, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'1 tin -> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</li><li class="src short"><a href="#v:_ParallelConcatStart">_ParallelConcatStart</a> :: <span class="keyword">forall</span> dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:_ParallelConcatStart-39-">_ParallelConcatStart'</a> :: <span class="keyword">forall</span> dtype m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</li><li class="src short"><a href="#v:_ParallelConcatUpdate">_ParallelConcatUpdate</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:_ParallelConcatUpdate-39-">_ParallelConcatUpdate'</a> :: <span class="keyword">forall</span> v'1 v'2 t. <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</li><li class="src short"><a href="#v:_Recv">_Recv</a> :: <span class="keyword">forall</span> tensor_type m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tensor_type) => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tensor_type)</li><li class="src short"><a href="#v:_Recv-39-">_Recv'</a> :: <span class="keyword">forall</span> tensor_type m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tensor_type) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tensor_type)</li><li class="src short"><a href="#v:_Retval">_Retval</a> :: <span class="keyword">forall</span> v'1 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:_Retval-39-">_Retval'</a> :: <span class="keyword">forall</span> v'1 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:_Send">_Send</a> :: <span class="keyword">forall</span> v'1 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li><li class="src short"><a href="#v:_Send-39-">_Send'</a> :: <span class="keyword">forall</span> v'1 t m'. (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t) => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a> -> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></li></ul></div><div id="interface"><h1>Documentation</h1><div class="top"><p class="src"><a name="v:abort" class="def">abort</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></p><div class="doc"><p>Raise a exception to abort the process when called. If exit_without_error is true, the process will exit normally, otherwise it will exit with a SIGABORT signal.</p><p>Returns nothing but an exception.</p></div></div><div class="top"><p class="src"><a name="v:abort-39-" class="def">abort'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></p></div><div class="top"><p class="src"><a name="v:abs" class="def">abs</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes the absolute value of a tensor.</p><p>Given a tensor <code>x</code>, this operation returns a tensor containing the absolute
|
|
value of each element in <code>x</code>. For example, if x is an input element and y is
|
|
an output element, this operation computes \(y = |x|\).</p></div></div><div class="top"><p class="src"><a name="v:abs-39-" class="def">abs'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:accumulatorApplyGradient" class="def">accumulatorApplyGradient</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a accumulator.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>local_step</strong>: The local_step value at which the gradient was computed.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 dtype</td><td class="doc"><p><strong>gradient</strong>: A tensor of the gradient to be accumulated.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Applies a gradient to a given accumulator. Does not add if local_step is lesser</p><p>than the accumulator's global_step.</p></div></div><div class="top"><p class="src"><a name="v:accumulatorApplyGradient-39-" class="def">accumulatorApplyGradient'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a accumulator.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>local_step</strong>: The local_step value at which the gradient was computed.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 dtype</td><td class="doc"><p><strong>gradient</strong>: A tensor of the gradient to be accumulated.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:accumulatorNumAccumulated" class="def">accumulatorNumAccumulated</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to an accumulator.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p><strong>num_accumulated</strong>: The number of gradients aggregated in the given accumulator.</p></td></tr></table></div><div class="doc"><p>Returns the number of gradients aggregated in the given accumulators.</p></div></div><div class="top"><p class="src"><a name="v:accumulatorNumAccumulated-39-" class="def">accumulatorNumAccumulated'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to an accumulator.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p><strong>num_accumulated</strong>: The number of gradients aggregated in the given accumulator.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:accumulatorSetGlobalStep" class="def">accumulatorSetGlobalStep</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to an accumulator.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>new_global_step</strong>: The new global_step value to set.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Updates the accumulator with a new value for global_step. Logs warning if the</p><p>accumulator's value is already higher than new_global_step.</p></div></div><div class="top"><p class="src"><a name="v:accumulatorSetGlobalStep-39-" class="def">accumulatorSetGlobalStep'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to an accumulator.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>new_global_step</strong>: The new global_step value to set.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:accumulatorTakeGradient" class="def">accumulatorTakeGradient</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to an accumulator.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>num_required</strong>: Number of gradients required before we return an aggregate.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>average</strong>: The average of the accumulated gradients.</p></td></tr></table></div><div class="doc"><p>Extracts the average gradient in the given ConditionalAccumulator, provided</p><p>that sufficient (i.e., more than num_required) gradients have been accumulated.
|
|
The op blocks until sufficient gradients have been accumulated.
|
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If the accumulator has already aggregated more than num_required gradients, it
|
|
returns the average of the accumulated gradients.
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Also automatically increments the recorded global_step in the accumulator by 1,
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|
and resets the aggregate to 0.</p></div></div><div class="top"><p class="src"><a name="v:accumulatorTakeGradient-39-" class="def">accumulatorTakeGradient'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to an accumulator.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>num_required</strong>: Number of gradients required before we return an aggregate.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>average</strong>: The average of the accumulated gradients.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:acos" class="def">acos</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes acos of x element-wise.</p></div></div><div class="top"><p class="src"><a name="v:acos-39-" class="def">acos'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:add" class="def">add</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns x + y element-wise.</p><ul><li>NOTE*: <code>Add</code> supports broadcasting. <code>AddN</code> does not. More about broadcasting
|
|
<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:add-39-" class="def">add'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:addManySparseToTensorsMap" class="def">addManySparseToTensorsMap</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sparse_indices</strong>: 2-D. The <code>indices</code> of the minibatch <code>SparseTensor</code>.
|
|
`sparse_indices[:, 0]` must be ordered values in `[0, N)`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>sparse_values</strong>: 1-D. The <code>values</code> of the minibatch <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sparse_shape</strong>: 1-D. The <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> of the minibatch <code>SparseTensor</code>.
|
|
The minibatch size `N == sparse_shape[0]`.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p><strong>sparse_handles</strong>: 1-D. The handles of the <code>SparseTensor</code> now stored in the
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|
<code>SparseTensorsMap</code>. Shape: `[N]`.</p></td></tr></table></div><div class="doc"><p>Add an <code>N</code>-minibatch <code>SparseTensor</code> to a <code>SparseTensorsMap</code>, return <code>N</code> handles.</p><p>A <code>SparseTensor</code> of rank <code>R</code> is represented by three tensors: <code>sparse_indices</code>,
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<code>sparse_values</code>, and <code>sparse_shape</code>, where</p><p>```sparse_indices.shape[1] == sparse_shape.shape[0] == R```</p><p>An <code>N</code>-minibatch of <code>SparseTensor</code> objects is represented as a <code>SparseTensor</code>
|
|
having a first <code>sparse_indices</code> column taking values between `[0, N)`, where
|
|
the minibatch size `N == sparse_shape[0]`.</p><p>The input <code>SparseTensor</code> must have rank <code>R</code> greater than 1, and the first
|
|
dimension is treated as the minibatch dimension. Elements of the <code>SparseTensor</code>
|
|
must be sorted in increasing order of this first dimension. The stored
|
|
<code>SparseTensor</code> objects pointed to by each row of the output <code>sparse_handles</code>
|
|
will have rank `R-1`.</p><p>The <code>SparseTensor</code> values can then be read out as part of a minibatch by passing
|
|
the given keys as vector elements to <code>TakeManySparseFromTensorsMap</code>. To ensure
|
|
the correct <code>SparseTensorsMap</code> is accessed, ensure that the same
|
|
<code>container</code> and <code>shared_name</code> are passed to that Op. If no <code>shared_name</code>
|
|
is provided here, instead use the *name* of the Operation created by calling
|
|
<code>AddManySparseToTensorsMap</code> as the <code>shared_name</code> passed to
|
|
<code>TakeManySparseFromTensorsMap</code>. Ensure the Operations are colocated.</p></div></div><div class="top"><p class="src"><a name="v:addManySparseToTensorsMap-39-" class="def">addManySparseToTensorsMap'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sparse_indices</strong>: 2-D. The <code>indices</code> of the minibatch <code>SparseTensor</code>.
|
|
`sparse_indices[:, 0]` must be ordered values in `[0, N)`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>sparse_values</strong>: 1-D. The <code>values</code> of the minibatch <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sparse_shape</strong>: 1-D. The <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> of the minibatch <code>SparseTensor</code>.
|
|
The minibatch size `N == sparse_shape[0]`.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p><strong>sparse_handles</strong>: 1-D. The handles of the <code>SparseTensor</code> now stored in the
|
|
<code>SparseTensorsMap</code>. Shape: `[N]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:addN" class="def">addN</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t]</td><td class="doc"><p><strong>inputs</strong>: Must all be the same size and shape.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>sum</strong></p></td></tr></table></div><div class="doc"><p>Add all input tensors element wise.</p></div></div><div class="top"><p class="src"><a name="v:addN-39-" class="def">addN'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t]</td><td class="doc"><p><strong>inputs</strong>: Must all be the same size and shape.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>sum</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:addSparseToTensorsMap" class="def">addSparseToTensorsMap</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sparse_indices</strong>: 2-D. The <code>indices</code> of the <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>sparse_values</strong>: 1-D. The <code>values</code> of the <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sparse_shape</strong>: 1-D. The <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> of the <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p><strong>sparse_handle</strong>: 0-D. The handle of the <code>SparseTensor</code> now stored in the
|
|
<code>SparseTensorsMap</code>.</p></td></tr></table></div><div class="doc"><p>Add a <code>SparseTensor</code> to a <code>SparseTensorsMap</code> return its handle.</p><p>A <code>SparseTensor</code> is represented by three tensors: <code>sparse_indices</code>,
|
|
<code>sparse_values</code>, and <code>sparse_shape</code>.</p><p>This operator takes the given <code>SparseTensor</code> and adds it to a container
|
|
object (a <code>SparseTensorsMap</code>). A unique key within this container is generated
|
|
in the form of an <code>int64</code>, and this is the value that is returned.</p><p>The <code>SparseTensor</code> can then be read out as part of a minibatch by passing
|
|
the key as a vector element to <code>TakeManySparseFromTensorsMap</code>. To ensure
|
|
the correct <code>SparseTensorsMap</code> is accessed, ensure that the same
|
|
<code>container</code> and <code>shared_name</code> are passed to that Op. If no <code>shared_name</code>
|
|
is provided here, instead use the *name* of the Operation created by calling
|
|
<code>AddSparseToTensorsMap</code> as the <code>shared_name</code> passed to
|
|
<code>TakeManySparseFromTensorsMap</code>. Ensure the Operations are colocated.</p></div></div><div class="top"><p class="src"><a name="v:addSparseToTensorsMap-39-" class="def">addSparseToTensorsMap'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sparse_indices</strong>: 2-D. The <code>indices</code> of the <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>sparse_values</strong>: 1-D. The <code>values</code> of the <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sparse_shape</strong>: 1-D. The <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> of the <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p><strong>sparse_handle</strong>: 0-D. The handle of the <code>SparseTensor</code> now stored in the
|
|
<code>SparseTensorsMap</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:adjustContrast" class="def">adjustContrast</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>images</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>contrast_factor</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Deprecated. Disallowed in GraphDef version >= 2.</p></div></div><div class="top"><p class="src"><a name="v:adjustContrast-39-" class="def">adjustContrast'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>images</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>contrast_factor</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:adjustContrastv2" class="def">adjustContrastv2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>images</strong>: Images to adjust. At least 3-D.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>contrast_factor</strong>: A float multiplier for adjusting contrast.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>output</strong>: The contrast-adjusted image or images.</p></td></tr></table></div><div class="doc"><p>Adjust the contrast of one or more images.</p><p><code>images</code> is a tensor of at least 3 dimensions. The last 3 dimensions are
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|
interpreted as `[height, width, channels]`. The other dimensions only
|
|
represent a collection of images, such as `[batch, height, width, channels].`</p><p>Contrast is adjusted independently for each channel of each image.</p><p>For each channel, the Op first computes the mean of the image pixels in the
|
|
channel and then adjusts each component of each pixel to
|
|
`(x - mean) * contrast_factor + mean`.</p></div></div><div class="top"><p class="src"><a name="v:adjustContrastv2-39-" class="def">adjustContrastv2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>images</strong>: Images to adjust. At least 3-D.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>contrast_factor</strong>: A float multiplier for adjusting contrast.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>output</strong>: The contrast-adjusted image or images.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:adjustHue" class="def">adjustHue</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>images</strong>: Images to adjust. At least 3-D.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>delta</strong>: A float delta to add to the hue.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>output</strong>: The hue-adjusted image or images.</p></td></tr></table></div><div class="doc"><p>Adjust the hue of one or more images.</p><p><code>images</code> is a tensor of at least 3 dimensions. The last dimension is
|
|
interpretted as channels, and must be three.</p><p>The input image is considered in the RGB colorspace. Conceptually, the RGB
|
|
colors are first mapped into HSV. A delta is then applied all the hue values,
|
|
and then remapped back to RGB colorspace.</p></div></div><div class="top"><p class="src"><a name="v:adjustHue-39-" class="def">adjustHue'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>images</strong>: Images to adjust. At least 3-D.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>delta</strong>: A float delta to add to the hue.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>output</strong>: The hue-adjusted image or images.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:adjustSaturation" class="def">adjustSaturation</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>images</strong>: Images to adjust. At least 3-D.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>scale</strong>: A float scale to add to the saturation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>output</strong>: The hue-adjusted image or images.</p></td></tr></table></div><div class="doc"><p>Adjust the saturation of one or more images.</p><p><code>images</code> is a tensor of at least 3 dimensions. The last dimension is
|
|
interpretted as channels, and must be three.</p><p>The input image is considered in the RGB colorspace. Conceptually, the RGB
|
|
colors are first mapped into HSV. A scale is then applied all the saturation
|
|
values, and then remapped back to RGB colorspace.</p></div></div><div class="top"><p class="src"><a name="v:adjustSaturation-39-" class="def">adjustSaturation'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>images</strong>: Images to adjust. At least 3-D.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>scale</strong>: A float scale to add to the saturation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>output</strong>: The hue-adjusted image or images.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:all" class="def">all</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>input</strong>: The tensor to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>reduction_indices</strong>: The dimensions to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>output</strong>: The reduced tensor.</p></td></tr></table></div><div class="doc"><p>Computes the "logical and" of elements across dimensions of a tensor.</p><p>Reduces <code>input</code> along the dimensions given in <code>reduction_indices</code>. Unless
|
|
<code>keep_dims</code> is true, the rank of the tensor is reduced by 1 for each entry in
|
|
<code>reduction_indices</code>. If <code>keep_dims</code> is true, the reduced dimensions are
|
|
retained with length 1.</p></div></div><div class="top"><p class="src"><a name="v:all-39-" class="def">all'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>input</strong>: The tensor to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>reduction_indices</strong>: The dimensions to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>output</strong>: The reduced tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:allCandidateSampler" class="def">allCandidateSampler</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_sampled</strong>: Number of candidates to produce per batch.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_true</strong>: Number of true labels per context.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>unique</strong>: If unique is true, we sample with rejection, so that all sampled
|
|
candidates in a batch are unique. This requires some approximation to
|
|
estimate the post-rejection sampling probabilities.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>true_classes</strong>: A batch_size * num_true matrix, in which each row contains the
|
|
IDs of the num_true target_classes in the corresponding original label.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>sampled_candidates</strong>, <strong>true_expected_count</strong>, <strong>sampled_expected_count</strong>)</p><ul><li><strong>sampled_candidates</strong>: A vector of length num_sampled, in which each element is
|
|
the ID of a sampled candidate.</li><li><strong>true_expected_count</strong>: A batch_size * num_true matrix, representing
|
|
the number of times each candidate is expected to occur in a batch
|
|
of sampled candidates. If unique=true, then this is a probability.</li><li><strong>sampled_expected_count</strong>: A vector of length num_sampled, for each sampled
|
|
candidate representing the number of times the candidate is expected
|
|
to occur in a batch of sampled candidates. If unique=true, then this is a
|
|
probability.</li></ul></td></tr></table></div><div class="doc"><p>Generates labels for candidate sampling with a learned unigram distribution.</p><p>See explanations of candidate sampling and the data formats at
|
|
go/candidate-sampling.</p><p>For each batch, this op picks a single set of sampled candidate labels.</p><p>The advantages of sampling candidates per-batch are simplicity and the
|
|
possibility of efficient dense matrix multiplication. The disadvantage is that
|
|
the sampled candidates must be chosen independently of the context and of the
|
|
true labels.</p></div></div><div class="top"><p class="src"><a name="v:allCandidateSampler-39-" class="def">allCandidateSampler'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_sampled</strong>: Number of candidates to produce per batch.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_true</strong>: Number of true labels per context.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>unique</strong>: If unique is true, we sample with rejection, so that all sampled
|
|
candidates in a batch are unique. This requires some approximation to
|
|
estimate the post-rejection sampling probabilities.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>true_classes</strong>: A batch_size * num_true matrix, in which each row contains the
|
|
IDs of the num_true target_classes in the corresponding original label.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>sampled_candidates</strong>, <strong>true_expected_count</strong>, <strong>sampled_expected_count</strong>)</p><ul><li><strong>sampled_candidates</strong>: A vector of length num_sampled, in which each element is
|
|
the ID of a sampled candidate.</li><li><strong>true_expected_count</strong>: A batch_size * num_true matrix, representing
|
|
the number of times each candidate is expected to occur in a batch
|
|
of sampled candidates. If unique=true, then this is a probability.</li><li><strong>sampled_expected_count</strong>: A vector of length num_sampled, for each sampled
|
|
candidate representing the number of times the candidate is expected
|
|
to occur in a batch of sampled candidates. If unique=true, then this is a
|
|
probability.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:any" class="def">any</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>input</strong>: The tensor to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>reduction_indices</strong>: The dimensions to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>output</strong>: The reduced tensor.</p></td></tr></table></div><div class="doc"><p>Computes the "logical or" of elements across dimensions of a tensor.</p><p>Reduces <code>input</code> along the dimensions given in <code>reduction_indices</code>. Unless
|
|
<code>keep_dims</code> is true, the rank of the tensor is reduced by 1 for each entry in
|
|
<code>reduction_indices</code>. If <code>keep_dims</code> is true, the reduced dimensions are
|
|
retained with length 1.</p></div></div><div class="top"><p class="src"><a name="v:any-39-" class="def">any'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>input</strong>: The tensor to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>reduction_indices</strong>: The dimensions to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>output</strong>: The reduced tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:applyAdadelta" class="def">applyAdadelta</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum_update</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>rho</strong>: Decay factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>epsilon</strong>: Constant factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Update '*var' according to the adadelta scheme.</p><p>accum = rho() * accum + (1 - rho()) * grad.square();
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update = (update_accum + epsilon).sqrt() * (accum + epsilon()).rsqrt() * grad;
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update_accum = rho() * update_accum + (1 - rho()) * update.square();
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var -= update;</p></div></div><div class="top"><p class="src"><a name="v:applyAdadelta-39-" class="def">applyAdadelta'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum_update</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>rho</strong>: Decay factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>epsilon</strong>: Constant factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:applyAdagrad" class="def">applyAdagrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Update '*var' according to the adagrad scheme.</p><p>accum += grad * grad
|
|
var -= lr * grad * (1 / sqrt(accum))</p></div></div><div class="top"><p class="src"><a name="v:applyAdagrad-39-" class="def">applyAdagrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:applyAdagradDA" class="def">applyAdagradDA</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>gradient_accumulator</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>gradient_squared_accumulator</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>global_step</strong>: Training step number. Must be a scalar.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Update '*var' according to the proximal adagrad scheme.</p></div></div><div class="top"><p class="src"><a name="v:applyAdagradDA-39-" class="def">applyAdagradDA'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>gradient_accumulator</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>gradient_squared_accumulator</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>global_step</strong>: Training step number. Must be a scalar.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:applyAdam" class="def">applyAdam</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>m</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>v</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>beta1_power</strong>: Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>beta2_power</strong>: Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>beta1</strong>: Momentum factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>beta2</strong>: Momentum factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Update '*var' according to the Adam algorithm.</p><p>lr_t <- learning_rate * sqrt(1 - beta2^t) / (1 - beta1^t)
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m_t <- beta1 * m_{t-1} + (1 - beta1) * g_t
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v_t <- beta2 * v_{t-1} + (1 - beta2) * g_t * g_t
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|
variable <- variable - lr_t * m_t / (sqrt(v_t) + epsilon)</p></div></div><div class="top"><p class="src"><a name="v:applyAdam-39-" class="def">applyAdam'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>m</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>v</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>beta1_power</strong>: Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>beta2_power</strong>: Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>beta1</strong>: Momentum factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>beta2</strong>: Momentum factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:applyCenteredRMSProp" class="def">applyCenteredRMSProp</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>mg</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ms</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>mom</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>rho</strong>: Decay rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>momentum</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Update '*var' according to the centered RMSProp algorithm.</p><p>The centered RMSProp algorithm uses an estimate of the centered second moment
|
|
(i.e., the variance) for normalization, as opposed to regular RMSProp, which
|
|
uses the (uncentered) second moment. This often helps with training, but is
|
|
slightly more expensive in terms of computation and memory.</p><p>Note that in dense implementation of this algorithm, mg, ms, and mom will
|
|
update even if the grad is zero, but in this sparse implementation, mg, ms,
|
|
and mom will not update in iterations during which the grad is zero.</p><p>mean_square = decay * mean_square + (1-decay) * gradient ** 2
|
|
mean_grad = decay * mean_grad + (1-decay) * gradient</p><p>Delta = learning_rate * gradient / sqrt(mean_square + epsilon - mean_grad ** 2)</p><p>mg <- rho * mg_{t-1} + (1-rho) * grad
|
|
ms <- rho * ms_{t-1} + (1-rho) * grad * grad
|
|
mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms - mg * mg + epsilon)
|
|
var <- var - mom</p></div></div><div class="top"><p class="src"><a name="v:applyCenteredRMSProp-39-" class="def">applyCenteredRMSProp'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>mg</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ms</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>mom</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>rho</strong>: Decay rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>momentum</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:applyFtrl" class="def">applyFtrl</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>linear</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>l1</strong>: L1 regulariation. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>l2</strong>: L2 regulariation. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>lr_power</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Update '*var' according to the Ftrl-proximal scheme.</p><p>accum_new = accum + grad * grad
|
|
linear += grad + (accum_new^(-lr_power) - accum^(-lr_power)) / lr * var
|
|
quadratic = 1.0 / (accum_new^(lr_power) * lr) + 2 * l2
|
|
var = (sign(linear) * l1 - linear) / quadratic if |linear| > l1 else 0.0
|
|
accum = accum_new</p></div></div><div class="top"><p class="src"><a name="v:applyFtrl-39-" class="def">applyFtrl'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>linear</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>l1</strong>: L1 regulariation. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>l2</strong>: L2 regulariation. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>lr_power</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:applyGradientDescent" class="def">applyGradientDescent</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>alpha</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>delta</strong>: The change.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Update '*var' by subtracting <code>alpha</code> * <code>delta</code> from it.</p></div></div><div class="top"><p class="src"><a name="v:applyGradientDescent-39-" class="def">applyGradientDescent'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>alpha</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>delta</strong>: The change.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:applyMomentum" class="def">applyMomentum</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>momentum</strong>: Momentum. Must be a scalar.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Update '*var' according to the momentum scheme. Set use_nesterov = True if you</p><p>want to use Nesterov momentum.</p><p>accum = accum * momentum + grad
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var -= lr * accum</p></div></div><div class="top"><p class="src"><a name="v:applyMomentum-39-" class="def">applyMomentum'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>momentum</strong>: Momentum. Must be a scalar.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:applyProximalAdagrad" class="def">applyProximalAdagrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Update '*var' and '*accum' according to FOBOS with Adagrad learning rate.</p><p>accum += grad * grad
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prox_v = var - lr * grad * (1 / sqrt(accum))
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var = sign(prox_v)/(1+lr*l2) * max{|prox_v|-lr*l1,0}</p></div></div><div class="top"><p class="src"><a name="v:applyProximalAdagrad-39-" class="def">applyProximalAdagrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:applyProximalGradientDescent" class="def">applyProximalGradientDescent</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>alpha</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>delta</strong>: The change.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Update '*var' as FOBOS algorithm with fixed learning rate.</p><p>prox_v = var - alpha * delta
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var = sign(prox_v)/(1+alpha*l2) * max{|prox_v|-alpha*l1,0}</p></div></div><div class="top"><p class="src"><a name="v:applyProximalGradientDescent-39-" class="def">applyProximalGradientDescent'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>alpha</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>delta</strong>: The change.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:applyRMSProp" class="def">applyRMSProp</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ms</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>mom</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>rho</strong>: Decay rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>momentum</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Update '*var' according to the RMSProp algorithm.</p><p>Note that in dense implementation of this algorithm, ms and mom will
|
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update even if the grad is zero, but in this sparse implementation, ms
|
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and mom will not update in iterations during which the grad is zero.</p><p>mean_square = decay * mean_square + (1-decay) * gradient ** 2
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Delta = learning_rate * gradient / sqrt(mean_square + epsilon)</p><p>ms <- rho * ms_{t-1} + (1-rho) * grad * grad
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mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon)
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var <- var - mom</p></div></div><div class="top"><p class="src"><a name="v:applyRMSProp-39-" class="def">applyRMSProp'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ms</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>mom</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>rho</strong>: Decay rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>momentum</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:argMax" class="def">argMax</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>dimension</strong>: int32, 0 <= dimension < rank(input). Describes which dimension
|
|
of the input Tensor to reduce across. For vectors, use dimension = 0.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Returns the index with the largest value across dimensions of a tensor.</p></div></div><div class="top"><p class="src"><a name="v:argMax-39-" class="def">argMax'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>dimension</strong>: int32, 0 <= dimension < rank(input). Describes which dimension
|
|
of the input Tensor to reduce across. For vectors, use dimension = 0.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:argMin" class="def">argMin</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>dimension</strong>: int32, 0 <= dimension < rank(input). Describes which dimension
|
|
of the input Tensor to reduce across. For vectors, use dimension = 0.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Returns the index with the smallest value across dimensions of a tensor.</p></div></div><div class="top"><p class="src"><a name="v:argMin-39-" class="def">argMin'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>dimension</strong>: int32, 0 <= dimension < rank(input). Describes which dimension
|
|
of the input Tensor to reduce across. For vectors, use dimension = 0.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:asString" class="def">asString</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Converts each entry in the given tensor to strings. Supports many numeric</p><p>types and boolean.</p></div></div><div class="top"><p class="src"><a name="v:asString-39-" class="def">asString'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:asin" class="def">asin</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes asin of x element-wise.</p></div></div><div class="top"><p class="src"><a name="v:asin-39-" class="def">asin'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:assert" class="def">assert</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>condition</strong>: The condition to evaluate.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 t</td><td class="doc"><p><strong>data</strong>: The tensors to print out when condition is false.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Asserts that the given condition is true.</p><p>If <code>condition</code> evaluates to false, print the list of tensors in `data`.
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<code>summarize</code> determines how many entries of the tensors to print.</p></div></div><div class="top"><p class="src"><a name="v:assert-39-" class="def">assert'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>condition</strong>: The condition to evaluate.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 t</td><td class="doc"><p><strong>data</strong>: The tensors to print out when condition is false.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:assign" class="def">assign</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: Should be from a <code>Variable</code> node. May be uninitialized.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>value</strong>: The value to be assigned to the variable.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: = Same as "ref". Returned as a convenience for operations that want
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to use the new value after the variable has been reset.</p></td></tr></table></div><div class="doc"><p>Update <code>ref</code> by assigning <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> to it.</p><p>This operation outputs "ref" after the assignment is done.
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This makes it easier to chain operations that need to use the reset value.</p></div></div><div class="top"><p class="src"><a name="v:assign-39-" class="def">assign'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: Should be from a <code>Variable</code> node. May be uninitialized.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>value</strong>: The value to be assigned to the variable.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: = Same as "ref". Returned as a convenience for operations that want
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to use the new value after the variable has been reset.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:assignAdd" class="def">assignAdd</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: Should be from a <code>Variable</code> node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>value</strong>: The value to be added to the variable.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: = Same as "ref". Returned as a convenience for operations that want
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to use the new value after the variable has been updated.</p></td></tr></table></div><div class="doc"><p>Update <code>ref</code> by adding <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> to it.</p><p>This operation outputs "ref" after the update is done.
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This makes it easier to chain operations that need to use the reset value.</p></div></div><div class="top"><p class="src"><a name="v:assignAdd-39-" class="def">assignAdd'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: Should be from a <code>Variable</code> node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>value</strong>: The value to be added to the variable.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: = Same as "ref". Returned as a convenience for operations that want
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to use the new value after the variable has been updated.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:assignAddVariableOp" class="def">assignAddVariableOp</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>resource</strong>: handle to the resource in which to store the variable.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 dtype</td><td class="doc"><p><strong>value</strong>: the value by which the variable will be incremented.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Adds a value to the current value of a variable.</p><p>Any ReadVariableOp which depends directly or indirectly on this assign is
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guaranteed to see the incremented value or a subsequent newer one.</p><p>Outputs the incremented value, which can be used to totally order the
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increments to this variable.</p></div></div><div class="top"><p class="src"><a name="v:assignAddVariableOp-39-" class="def">assignAddVariableOp'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>resource</strong>: handle to the resource in which to store the variable.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 dtype</td><td class="doc"><p><strong>value</strong>: the value by which the variable will be incremented.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:assignSub" class="def">assignSub</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: Should be from a <code>Variable</code> node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>value</strong>: The value to be subtracted to the variable.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: = Same as "ref". Returned as a convenience for operations that want
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to use the new value after the variable has been updated.</p></td></tr></table></div><div class="doc"><p>Update <code>ref</code> by subtracting <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> from it.</p><p>This operation outputs "ref" after the update is done.
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This makes it easier to chain operations that need to use the reset value.</p></div></div><div class="top"><p class="src"><a name="v:assignSub-39-" class="def">assignSub'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: Should be from a <code>Variable</code> node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>value</strong>: The value to be subtracted to the variable.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: = Same as "ref". Returned as a convenience for operations that want
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to use the new value after the variable has been updated.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:assignVariableOp" class="def">assignVariableOp</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>resource</strong>: handle to the resource in which to store the variable.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 dtype</td><td class="doc"><p><strong>value</strong>: the value to set the new tensor to use.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Assigns a new value to a variable.</p><p>Any ReadVariableOp with a control dependency on this op is guaranteed to return
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this value or a subsequent newer value of the variable.</p></div></div><div class="top"><p class="src"><a name="v:assignVariableOp-39-" class="def">assignVariableOp'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>resource</strong>: handle to the resource in which to store the variable.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 dtype</td><td class="doc"><p><strong>value</strong>: the value to set the new tensor to use.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:atan" class="def">atan</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes atan of x element-wise.</p></div></div><div class="top"><p class="src"><a name="v:atan-39-" class="def">atan'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:audioSummary" class="def">audioSummary</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>sample_rate</strong>: The sample rate of the signal in hertz.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tag</strong>: Scalar. Used to build the <code>tag</code> attribute of the summary values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>tensor</strong>: 2-D of shape `[batch_size, frames]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>summary</strong>: Scalar. Serialized <code>Summary</code> protocol buffer.</p></td></tr></table></div><div class="doc"><p>Outputs a <code>Summary</code> protocol buffer with audio.</p><p>The summary has up to <code>max_outputs</code> summary values containing audio. The
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audio is built from <code>tensor</code> which must be 3-D with shape `[batch_size,
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|
frames, channels]` or 2-D with shape `[batch_size, frames]`. The values are
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|
assumed to be in the range of `[-1.0, 1.0]` with a sample rate of <code>sample_rate</code>.</p><p>The <code>tag</code> argument is a scalar <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> of type <code>string</code>. It is used to
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build the <code>tag</code> of the summary values:</p><ul><li>If <code>max_outputs</code> is 1, the summary value tag is '*tag*/audio'.</li><li>If <code>max_outputs</code> is greater than 1, the summary value tags are
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generated sequentially as '*tag*/audio/0', '*tag*/audio/1', etc.</li></ul></div></div><div class="top"><p class="src"><a name="v:audioSummary-39-" class="def">audioSummary'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>sample_rate</strong>: The sample rate of the signal in hertz.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tag</strong>: Scalar. Used to build the <code>tag</code> attribute of the summary values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>tensor</strong>: 2-D of shape `[batch_size, frames]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>summary</strong>: Scalar. Serialized <code>Summary</code> protocol buffer.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:audioSummaryV2" class="def">audioSummaryV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tag</strong>: Scalar. Used to build the <code>tag</code> attribute of the summary values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>tensor</strong>: 2-D of shape `[batch_size, frames]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>sample_rate</strong>: The sample rate of the signal in hertz.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>summary</strong>: Scalar. Serialized <code>Summary</code> protocol buffer.</p></td></tr></table></div><div class="doc"><p>Outputs a <code>Summary</code> protocol buffer with audio.</p><p>The summary has up to <code>max_outputs</code> summary values containing audio. The
|
|
audio is built from <code>tensor</code> which must be 3-D with shape `[batch_size,
|
|
frames, channels]` or 2-D with shape `[batch_size, frames]`. The values are
|
|
assumed to be in the range of `[-1.0, 1.0]` with a sample rate of <code>sample_rate</code>.</p><p>The <code>tag</code> argument is a scalar <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> of type <code>string</code>. It is used to
|
|
build the <code>tag</code> of the summary values:</p><ul><li>If <code>max_outputs</code> is 1, the summary value tag is '*tag*/audio'.</li><li>If <code>max_outputs</code> is greater than 1, the summary value tags are
|
|
generated sequentially as '*tag*/audio/0', '*tag*/audio/1', etc.</li></ul></div></div><div class="top"><p class="src"><a name="v:audioSummaryV2-39-" class="def">audioSummaryV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tag</strong>: Scalar. Used to build the <code>tag</code> attribute of the summary values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>tensor</strong>: 2-D of shape `[batch_size, frames]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>sample_rate</strong>: The sample rate of the signal in hertz.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>summary</strong>: Scalar. Serialized <code>Summary</code> protocol buffer.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:avgPool" class="def">avgPool</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The average pooled output tensor.</p></td></tr></table></div><div class="doc"><p>Performs average pooling on the input.</p><p>Each entry in <code>output</code> is the mean of the corresponding size <code>ksize</code>
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window in <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>.</p></div></div><div class="top"><p class="src"><a name="v:avgPool-39-" class="def">avgPool'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The average pooled output tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:avgPool3D" class="def">avgPool3D</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape `[batch, depth, rows, cols, channels]` tensor to pool over.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The average pooled output tensor.</p></td></tr></table></div><div class="doc"><p>Performs 3D average pooling on the input.</p></div></div><div class="top"><p class="src"><a name="v:avgPool3D-39-" class="def">avgPool3D'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape `[batch, depth, rows, cols, channels]` tensor to pool over.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The average pooled output tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:avgPool3DGrad" class="def">avgPool3DGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>orig_input_shape</strong>: The original input dimensions.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>grad</strong>: Output backprop of shape `[batch, depth, rows, cols, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The backprop for input.</p></td></tr></table></div><div class="doc"><p>Computes gradients of average pooling function.</p></div></div><div class="top"><p class="src"><a name="v:avgPool3DGrad-39-" class="def">avgPool3DGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>orig_input_shape</strong>: The original input dimensions.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>grad</strong>: Output backprop of shape `[batch, depth, rows, cols, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The backprop for input.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:avgPoolGrad" class="def">avgPoolGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>orig_input_shape</strong>: 1-D. Shape of the original input to <code>avg_pool</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>grad</strong>: 4-D with shape `[batch, height, width, channels]`. Gradients w.r.t.
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|
the output of <code>avg_pool</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D. Gradients w.r.t. the input of <code>avg_pool</code>.</p></td></tr></table></div><div class="doc"><p>Computes gradients of the average pooling function.</p></div></div><div class="top"><p class="src"><a name="v:avgPoolGrad-39-" class="def">avgPoolGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>orig_input_shape</strong>: 1-D. Shape of the original input to <code>avg_pool</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>grad</strong>: 4-D with shape `[batch, height, width, channels]`. Gradients w.r.t.
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the output of <code>avg_pool</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D. Gradients w.r.t. the input of <code>avg_pool</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:barrier" class="def">barrier</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>]</td><td class="doc"><p><strong>component_types</strong>: The type of each component in a value.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong>: The handle to the barrier.</p></td></tr></table></div><div class="doc"><p>Defines a barrier that persists across different graph executions.</p><p>A barrier represents a key-value map, where each key is a string, and
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each value is a tuple of tensors.</p><p>At runtime, the barrier contains <code>complete</code> and <code>incomplete</code>
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elements. A complete element has defined tensors for all components of
|
|
its value tuple, and may be accessed using BarrierTakeMany. An
|
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incomplete element has some undefined components in its value tuple,
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|
and may be updated using BarrierInsertMany.</p></div></div><div class="top"><p class="src"><a name="v:barrier-39-" class="def">barrier'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>]</td><td class="doc"><p><strong>component_types</strong>: The type of each component in a value.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong>: The handle to the barrier.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:barrierClose" class="def">barrierClose</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a barrier.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Closes the given barrier.</p><p>This operation signals that no more new elements will be inserted in the
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given barrier. Subsequent InsertMany that try to introduce a new key will fail.
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Subsequent InsertMany operations that just add missing components to already
|
|
existing elements will continue to succeed. Subsequent TakeMany operations will
|
|
continue to succeed if sufficient completed elements remain in the barrier.
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|
Subsequent TakeMany operations that would block will fail immediately.</p></div></div><div class="top"><p class="src"><a name="v:barrierClose-39-" class="def">barrierClose'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a barrier.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:barrierIncompleteSize" class="def">barrierIncompleteSize</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a barrier.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p><strong>size</strong>: The number of incomplete elements (i.e. those with some of their value
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|
components not set) in the barrier.</p></td></tr></table></div><div class="doc"><p>Computes the number of incomplete elements in the given barrier.</p></div></div><div class="top"><p class="src"><a name="v:barrierIncompleteSize-39-" class="def">barrierIncompleteSize'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a barrier.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p><strong>size</strong>: The number of incomplete elements (i.e. those with some of their value
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|
components not set) in the barrier.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:barrierInsertMany" class="def">barrierInsertMany</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>component_index</strong>: The component of the barrier elements that is being assigned.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a barrier.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>keys</strong>: A one-dimensional tensor of keys, with length n.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>values</strong>: An any-dimensional tensor of values, which are associated with the
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respective keys. The 0th dimension must have length n.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>For each key, assigns the respective value to the specified component.</p><p>If a key is not found in the barrier, this operation will create a new
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|
incomplete element. If a key is found in the barrier, and the element
|
|
already has a value at component_index, this operation will fail with
|
|
INVALID_ARGUMENT, and leave the barrier in an undefined state.</p></div></div><div class="top"><p class="src"><a name="v:barrierInsertMany-39-" class="def">barrierInsertMany'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>component_index</strong>: The component of the barrier elements that is being assigned.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a barrier.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>keys</strong>: A one-dimensional tensor of keys, with length n.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>values</strong>: An any-dimensional tensor of values, which are associated with the
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|
respective keys. The 0th dimension must have length n.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:barrierReadySize" class="def">barrierReadySize</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a barrier.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p><strong>size</strong>: The number of complete elements (i.e. those with all of their value
|
|
components set) in the barrier.</p></td></tr></table></div><div class="doc"><p>Computes the number of complete elements in the given barrier.</p></div></div><div class="top"><p class="src"><a name="v:barrierReadySize-39-" class="def">barrierReadySize'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a barrier.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p><strong>size</strong>: The number of complete elements (i.e. those with all of their value
|
|
components set) in the barrier.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:barrierTakeMany" class="def">barrierTakeMany</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a barrier.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>num_elements</strong>: A single-element tensor containing the number of elements to
|
|
take.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</td><td class="doc"><p>(<strong>indices</strong>, <strong>keys</strong>, <strong>values</strong>)</p><ul><li><strong>indices</strong>: A one-dimensional tensor of indices, with length num_elems.
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|
These indices refer to the batch in which the values were placed into the
|
|
barrier (starting with MIN_LONG and increasing with each BarrierInsertMany).</li><li><strong>keys</strong>: A one-dimensional tensor of keys, with length num_elements.</li><li><strong>values</strong>: One any-dimensional tensor per component in a barrier element. All
|
|
values have length num_elements in the 0th dimension.</li></ul></td></tr></table></div><div class="doc"><p>Takes the given number of completed elements from a barrier.</p><p>This operation concatenates completed-element component tensors along
|
|
the 0th dimension to make a single component tensor.</p><p>Elements come out of the barrier when they are complete, and in the order
|
|
in which they were placed into the barrier. The indices output provides
|
|
information about the batch in which each element was originally inserted
|
|
into the barrier.</p></div></div><div class="top"><p class="src"><a name="v:barrierTakeMany-39-" class="def">barrierTakeMany'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a barrier.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>num_elements</strong>: A single-element tensor containing the number of elements to
|
|
take.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</td><td class="doc"><p>(<strong>indices</strong>, <strong>keys</strong>, <strong>values</strong>)</p><ul><li><strong>indices</strong>: A one-dimensional tensor of indices, with length num_elems.
|
|
These indices refer to the batch in which the values were placed into the
|
|
barrier (starting with MIN_LONG and increasing with each BarrierInsertMany).</li><li><strong>keys</strong>: A one-dimensional tensor of keys, with length num_elements.</li><li><strong>values</strong>: One any-dimensional tensor per component in a barrier element. All
|
|
values have length num_elements in the 0th dimension.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchCholesky" class="def">batchCholesky</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchCholesky-39-" class="def">batchCholesky'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchCholeskyGrad" class="def">batchCholeskyGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>l</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>grad</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchCholeskyGrad-39-" class="def">batchCholeskyGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>l</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>grad</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchFFT" class="def">batchFFT</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchFFT-39-" class="def">batchFFT'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchFFT2D" class="def">batchFFT2D</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchFFT2D-39-" class="def">batchFFT2D'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchFFT3D" class="def">batchFFT3D</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchFFT3D-39-" class="def">batchFFT3D'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchIFFT" class="def">batchIFFT</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchIFFT-39-" class="def">batchIFFT'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchIFFT2D" class="def">batchIFFT2D</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchIFFT2D-39-" class="def">batchIFFT2D'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchIFFT3D" class="def">batchIFFT3D</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchIFFT3D-39-" class="def">batchIFFT3D'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatMul" class="def">batchMatMul</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong>: 3-D or higher with shape `[..., r_x, c_x]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong>: 3-D or higher with shape `[..., r_y, c_y]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 3-D or higher with shape `[..., r_o, c_o]`</p></td></tr></table></div><div class="doc"><p>Multiplies slices of two tensors in batches.</p><p>Multiplies all slices of <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> <code>x</code> and <code>y</code> (each slice can be
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viewed as an element of a batch), and arranges the individual results
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in a single output tensor of the same batch size. Each of the
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individual slices can optionally be adjointed (to adjoint a matrix
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means to transpose and conjugate it) before multiplication by setting
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the <code>adj_x</code> or <code>adj_y</code> flag to <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code>, which are by default <code><a href="../base-4.8.2.0/Data-Bool.html#v:False">False</a></code>.</p><p>The input tensors <code>x</code> and <code>y</code> are 3-D or higher with shape `[..., r_x, c_x]`
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and `[..., r_y, c_y]`.</p><p>The output tensor is 3-D or higher with shape `[..., r_o, c_o]`, where:</p><p>r_o = c_x if adj_x else r_x
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c_o = r_y if adj_y else c_y</p><p>It is computed as:</p><p>output[..., :, :] = matrix(x[..., :, :]) * matrix(y[..., :, :])</p></div></div><div class="top"><p class="src"><a name="v:batchMatMul-39-" class="def">batchMatMul'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong>: 3-D or higher with shape `[..., r_x, c_x]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong>: 3-D or higher with shape `[..., r_y, c_y]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 3-D or higher with shape `[..., r_o, c_o]`</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatrixBandPart" class="def">batchMatrixBandPart</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_lower</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_upper</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>band</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatrixBandPart-39-" class="def">batchMatrixBandPart'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_lower</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_upper</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>band</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatrixDeterminant" class="def">batchMatrixDeterminant</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatrixDeterminant-39-" class="def">batchMatrixDeterminant'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatrixDiag" class="def">batchMatrixDiag</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>diagonal</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatrixDiag-39-" class="def">batchMatrixDiag'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>diagonal</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatrixDiagPart" class="def">batchMatrixDiagPart</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>diagonal</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatrixDiagPart-39-" class="def">batchMatrixDiagPart'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>diagonal</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatrixInverse" class="def">batchMatrixInverse</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatrixInverse-39-" class="def">batchMatrixInverse'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatrixSetDiag" class="def">batchMatrixSetDiag</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>diagonal</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatrixSetDiag-39-" class="def">batchMatrixSetDiag'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>diagonal</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatrixSolve" class="def">batchMatrixSolve</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>matrix</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>rhs</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatrixSolve-39-" class="def">batchMatrixSolve'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>matrix</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>rhs</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatrixSolveLs" class="def">batchMatrixSolveLs</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>matrix</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>rhs</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a></td><td class="doc"><p><strong>l2_regularizer</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatrixSolveLs-39-" class="def">batchMatrixSolveLs'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>matrix</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>rhs</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a></td><td class="doc"><p><strong>l2_regularizer</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatrixTriangularSolve" class="def">batchMatrixTriangularSolve</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>matrix</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>rhs</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchMatrixTriangularSolve-39-" class="def">batchMatrixTriangularSolve'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>matrix</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>rhs</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchNormWithGlobalNormalization" class="def">batchNormWithGlobalNormalization</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>scale_after_normalization</strong>: A bool indicating whether the resulted tensor
|
|
needs to be multiplied with gamma.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>variance_epsilon</strong>: A small float number to avoid dividing by 0.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>t</strong>: A 4D input Tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>m</strong>: A 1D mean Tensor with size matching the last dimension of t.
|
|
This is the first output from tf.nn.moments,
|
|
or a saved moving average thereof.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>v</strong>: A 1D variance Tensor with size matching the last dimension of t.
|
|
This is the second output from tf.nn.moments,
|
|
or a saved moving average thereof.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>beta</strong>: A 1D beta Tensor with size matching the last dimension of t.
|
|
An offset to be added to the normalized tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>gamma</strong>: A 1D gamma Tensor with size matching the last dimension of t.
|
|
If "scale_after_normalization" is true, this tensor will be multiplied
|
|
with the normalized tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>result</strong></p></td></tr></table></div><div class="doc"><p>Batch normalization.</p><p>This op is deprecated. Prefer `tf.nn.batch_normalization`.</p></div></div><div class="top"><p class="src"><a name="v:batchNormWithGlobalNormalization-39-" class="def">batchNormWithGlobalNormalization'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>scale_after_normalization</strong>: A bool indicating whether the resulted tensor
|
|
needs to be multiplied with gamma.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>variance_epsilon</strong>: A small float number to avoid dividing by 0.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>t</strong>: A 4D input Tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>m</strong>: A 1D mean Tensor with size matching the last dimension of t.
|
|
This is the first output from tf.nn.moments,
|
|
or a saved moving average thereof.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>v</strong>: A 1D variance Tensor with size matching the last dimension of t.
|
|
This is the second output from tf.nn.moments,
|
|
or a saved moving average thereof.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>beta</strong>: A 1D beta Tensor with size matching the last dimension of t.
|
|
An offset to be added to the normalized tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>gamma</strong>: A 1D gamma Tensor with size matching the last dimension of t.
|
|
If "scale_after_normalization" is true, this tensor will be multiplied
|
|
with the normalized tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>result</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchNormWithGlobalNormalizationGrad" class="def">batchNormWithGlobalNormalizationGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>scale_after_normalization</strong>: A bool indicating whether the resulted tensor
|
|
needs to be multiplied with gamma.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>variance_epsilon</strong>: A small float number to avoid dividing by 0.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>t</strong>: A 4D input Tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>m</strong>: A 1D mean Tensor with size matching the last dimension of t.
|
|
This is the first output from tf.nn.moments,
|
|
or a saved moving average thereof.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>v</strong>: A 1D variance Tensor with size matching the last dimension of t.
|
|
This is the second output from tf.nn.moments,
|
|
or a saved moving average thereof.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>gamma</strong>: A 1D gamma Tensor with size matching the last dimension of t.
|
|
If "scale_after_normalization" is true, this Tensor will be multiplied
|
|
with the normalized Tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>backprop</strong>: 4D backprop Tensor.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>dx</strong>, <strong>dm</strong>, <strong>dv</strong>, <strong>db</strong>, <strong>dg</strong>)</p><ul><li><strong>dx</strong>: 4D backprop tensor for input.</li><li><strong>dm</strong>: 1D backprop tensor for mean.</li><li><strong>dv</strong>: 1D backprop tensor for variance.</li><li><strong>db</strong>: 1D backprop tensor for beta.</li><li><strong>dg</strong>: 1D backprop tensor for gamma.</li></ul></td></tr></table></div><div class="doc"><p>Gradients for batch normalization.</p><p>This op is deprecated. See `tf.nn.batch_normalization`.</p></div></div><div class="top"><p class="src"><a name="v:batchNormWithGlobalNormalizationGrad-39-" class="def">batchNormWithGlobalNormalizationGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>scale_after_normalization</strong>: A bool indicating whether the resulted tensor
|
|
needs to be multiplied with gamma.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>variance_epsilon</strong>: A small float number to avoid dividing by 0.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>t</strong>: A 4D input Tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>m</strong>: A 1D mean Tensor with size matching the last dimension of t.
|
|
This is the first output from tf.nn.moments,
|
|
or a saved moving average thereof.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>v</strong>: A 1D variance Tensor with size matching the last dimension of t.
|
|
This is the second output from tf.nn.moments,
|
|
or a saved moving average thereof.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>gamma</strong>: A 1D gamma Tensor with size matching the last dimension of t.
|
|
If "scale_after_normalization" is true, this Tensor will be multiplied
|
|
with the normalized Tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>backprop</strong>: 4D backprop Tensor.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>dx</strong>, <strong>dm</strong>, <strong>dv</strong>, <strong>db</strong>, <strong>dg</strong>)</p><ul><li><strong>dx</strong>: 4D backprop tensor for input.</li><li><strong>dm</strong>: 1D backprop tensor for mean.</li><li><strong>dv</strong>: 1D backprop tensor for variance.</li><li><strong>db</strong>: 1D backprop tensor for beta.</li><li><strong>dg</strong>: 1D backprop tensor for gamma.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchSelfAdjointEig" class="def">batchSelfAdjointEig</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchSelfAdjointEig-39-" class="def">batchSelfAdjointEig'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchSelfAdjointEigV2" class="def">batchSelfAdjointEigV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>e</strong>, <strong>v</strong>)</p><ul><li><strong>e</strong></li><li><strong>v</strong></li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchSelfAdjointEigV2-39-" class="def">batchSelfAdjointEigV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>e</strong>, <strong>v</strong>)</p><ul><li><strong>e</strong></li><li><strong>v</strong></li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchSvd" class="def">batchSvd</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>s</strong>, <strong>u</strong>, <strong>v</strong>)</p><ul><li><strong>s</strong></li><li><strong>u</strong></li><li><strong>v</strong></li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchSvd-39-" class="def">batchSvd'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>s</strong>, <strong>u</strong>, <strong>v</strong>)</p><ul><li><strong>s</strong></li><li><strong>u</strong></li><li><strong>v</strong></li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchToSpace" class="def">batchToSpace</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>block_size</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D tensor with shape
|
|
`[batch*block_size*block_size, height_pad<em>block_size, width_pad</em>block_size,
|
|
depth]`. Note that the batch size of the input tensor must be divisible by
|
|
`block_size * block_size`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>crops</strong>: 2-D tensor of non-negative integers with shape `[2, 2]`. It specifies
|
|
how many elements to crop from the intermediate result across the spatial
|
|
dimensions as follows:</p><p>crops = [[crop_top, crop_bottom], [crop_left, crop_right]]</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D with shape `[batch, height, width, depth]`, where:</p><p>height = height_pad - crop_top - crop_bottom
|
|
width = width_pad - crop_left - crop_right</p><p>The attr <code>block_size</code> must be greater than one. It indicates the block size.</p><p>Some examples:</p><ol><li>For the following input of shape `[4, 1, 1, 1]` and block_size of 2:</li></ol><p>```prettyprint
|
|
[[[[1]]], [[[2]]], [[[3]]], [[[4]]]]
|
|
```</p><p>The output tensor has shape `[1, 2, 2, 1]` and value:</p><p>```prettyprint
|
|
x = [[[[1], [2]], [[3], [4]]]]
|
|
```</p><ol><li>For the following input of shape `[4, 1, 1, 3]` and block_size of 2:</li></ol><p>```prettyprint
|
|
[[[1, 2, 3]], [[4, 5, 6]], [[7, 8, 9]], [[10, 11, 12]]]
|
|
```</p><p>The output tensor has shape `[1, 2, 2, 3]` and value:</p><p>```prettyprint
|
|
x = [[[[1, 2, 3], [4, 5, 6]],
|
|
[[7, 8, 9], [10, 11, 12]]]]
|
|
```</p><ol><li>For the following input of shape `[4, 2, 2, 1]` and block_size of 2:</li></ol><p>```prettyprint
|
|
x = [[[[1], [3]], [[5], [7]]],
|
|
[[[2], [4]], [[10], [12]]],
|
|
[[[5], [7]], [[13], [15]]],
|
|
[[[6], [8]], [[14], [16]]]]
|
|
```</p><p>The output tensor has shape `[1, 4, 4, 1]` and value:</p><p>```prettyprint
|
|
x = [[[1], [2], [3], [4]],
|
|
[[5], [6], [7], [8]],
|
|
[[9], [10], [11], [12]],
|
|
[[13], [14], [15], [16]]]
|
|
```</p><ol><li>For the following input of shape `[8, 1, 2, 1]` and block_size of 2:</li></ol><p>```prettyprint
|
|
x = [[[[1], [3]]], [[[9], [11]]], [[[2], [4]]], [[[10], [12]]],
|
|
[[[5], [7]]], [[[13], [15]]], [[[6], [8]]], [[[14], [16]]]]
|
|
```</p><p>The output tensor has shape `[2, 2, 4, 1]` and value:</p><p>```prettyprint
|
|
x = [[[[1], [3]], [[5], [7]]],
|
|
[[[2], [4]], [[10], [12]]],
|
|
[[[5], [7]], [[13], [15]]],
|
|
[[[6], [8]], [[14], [16]]]]
|
|
```</p></td></tr></table></div><div class="doc"><p>BatchToSpace for 4-D tensors of type T.</p><p>This is a legacy version of the more general BatchToSpaceND.</p><p>Rearranges (permutes) data from batch into blocks of spatial data, followed by
|
|
cropping. This is the reverse transformation of SpaceToBatch. More specifically,
|
|
this op outputs a copy of the input tensor where values from the <code>batch</code>
|
|
dimension are moved in spatial blocks to the <code>height</code> and <code>width</code> dimensions,
|
|
followed by cropping along the <code>height</code> and <code>width</code> dimensions.</p></div></div><div class="top"><p class="src"><a name="v:batchToSpace-39-" class="def">batchToSpace'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>block_size</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D tensor with shape
|
|
`[batch*block_size*block_size, height_pad<em>block_size, width_pad</em>block_size,
|
|
depth]`. Note that the batch size of the input tensor must be divisible by
|
|
`block_size * block_size`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>crops</strong>: 2-D tensor of non-negative integers with shape `[2, 2]`. It specifies
|
|
how many elements to crop from the intermediate result across the spatial
|
|
dimensions as follows:</p><p>crops = [[crop_top, crop_bottom], [crop_left, crop_right]]</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D with shape `[batch, height, width, depth]`, where:</p><p>height = height_pad - crop_top - crop_bottom
|
|
width = width_pad - crop_left - crop_right</p><p>The attr <code>block_size</code> must be greater than one. It indicates the block size.</p><p>Some examples:</p><ol><li>For the following input of shape `[4, 1, 1, 1]` and block_size of 2:</li></ol><p>```prettyprint
|
|
[[[[1]]], [[[2]]], [[[3]]], [[[4]]]]
|
|
```</p><p>The output tensor has shape `[1, 2, 2, 1]` and value:</p><p>```prettyprint
|
|
x = [[[[1], [2]], [[3], [4]]]]
|
|
```</p><ol><li>For the following input of shape `[4, 1, 1, 3]` and block_size of 2:</li></ol><p>```prettyprint
|
|
[[[1, 2, 3]], [[4, 5, 6]], [[7, 8, 9]], [[10, 11, 12]]]
|
|
```</p><p>The output tensor has shape `[1, 2, 2, 3]` and value:</p><p>```prettyprint
|
|
x = [[[[1, 2, 3], [4, 5, 6]],
|
|
[[7, 8, 9], [10, 11, 12]]]]
|
|
```</p><ol><li>For the following input of shape `[4, 2, 2, 1]` and block_size of 2:</li></ol><p>```prettyprint
|
|
x = [[[[1], [3]], [[5], [7]]],
|
|
[[[2], [4]], [[10], [12]]],
|
|
[[[5], [7]], [[13], [15]]],
|
|
[[[6], [8]], [[14], [16]]]]
|
|
```</p><p>The output tensor has shape `[1, 4, 4, 1]` and value:</p><p>```prettyprint
|
|
x = [[[1], [2], [3], [4]],
|
|
[[5], [6], [7], [8]],
|
|
[[9], [10], [11], [12]],
|
|
[[13], [14], [15], [16]]]
|
|
```</p><ol><li>For the following input of shape `[8, 1, 2, 1]` and block_size of 2:</li></ol><p>```prettyprint
|
|
x = [[[[1], [3]]], [[[9], [11]]], [[[2], [4]]], [[[10], [12]]],
|
|
[[[5], [7]]], [[[13], [15]]], [[[6], [8]]], [[[14], [16]]]]
|
|
```</p><p>The output tensor has shape `[2, 2, 4, 1]` and value:</p><p>```prettyprint
|
|
x = [[[[1], [3]], [[5], [7]]],
|
|
[[[2], [4]], [[10], [12]]],
|
|
[[[5], [7]], [[13], [15]]],
|
|
[[[6], [8]], [[14], [16]]]]
|
|
```</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:batchToSpaceND" class="def">batchToSpaceND</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tblock_shape, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tcrops)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: N-D with shape `input_shape = [batch] + spatial_shape + remaining_shape`,
|
|
where spatial_shape has M dimensions.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tblock_shape</td><td class="doc"><p><strong>block_shape</strong>: 1-D with shape `[M]`, all values must be >= 1.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tcrops</td><td class="doc"><p><strong>crops</strong>: 2-D with shape `[M, 2]`, all values must be >= 0.
|
|
`crops[i] = [crop_start, crop_end]` specifies the amount to crop from input
|
|
dimension `i + 1`, which corresponds to spatial dimension <code>i</code>. It is
|
|
required that
|
|
`crop_start[i] + crop_end[i] <= block_shape[i] * input_shape[i + 1]`.</p><p>This operation is equivalent to the following steps:</p><ol><li>Reshape <code>input</code> to <code>reshaped</code> of shape:
|
|
[block_shape[0], ..., block_shape[M-1],
|
|
batch / prod(block_shape),
|
|
input_shape[1], ..., input_shape[N-1]]</li><li>Permute dimensions of <code>reshaped</code> to produce <code>permuted</code> of shape
|
|
[batch / prod(block_shape),</li></ol><p>input_shape[1], block_shape[0],
|
|
...,
|
|
input_shape[M], block_shape[M-1],</p><p>input_shape[M+1], ..., input_shape[N-1]]</p><ol><li>Reshape <code>permuted</code> to produce <code>reshaped_permuted</code> of shape
|
|
[batch / prod(block_shape),</li></ol><p>input_shape[1] * block_shape[0],
|
|
...,
|
|
input_shape[M] * block_shape[M-1],</p><p>input_shape[M+1],
|
|
...,
|
|
input_shape[N-1]]</p><ol><li>Crop the start and end of dimensions `[1, ..., M]` of
|
|
<code>reshaped_permuted</code> according to <code>crops</code> to produce the output of shape:
|
|
[batch / prod(block_shape),</li></ol><p>input_shape[1] * block_shape[0] - crops[0,0] - crops[0,1],
|
|
...,
|
|
input_shape[M] * block_shape[M-1] - crops[M-1,0] - crops[M-1,1],</p><p>input_shape[M+1], ..., input_shape[N-1]]</p><p>Some examples:</p><ol><li>For the following input of shape `[4, 1, 1, 1]`, `block_shape = [2, 2]`, and
|
|
`crops = [[0, 0], [0, 0]]`:</li></ol><p>```prettyprint
|
|
[[[[1]]], [[[2]]], [[[3]]], [[[4]]]]
|
|
```</p><p>The output tensor has shape `[1, 2, 2, 1]` and value:</p><p>```prettyprint
|
|
x = [[[[1], [2]], [[3], [4]]]]
|
|
```</p><ol><li>For the following input of shape `[4, 1, 1, 3]`, `block_shape = [2, 2]`, and
|
|
`crops = [[0, 0], [0, 0]]`:</li></ol><p>```prettyprint
|
|
[[[1, 2, 3]], [[4, 5, 6]], [[7, 8, 9]], [[10, 11, 12]]]
|
|
```</p><p>The output tensor has shape `[1, 2, 2, 3]` and value:</p><p>```prettyprint
|
|
x = [[[[1, 2, 3], [4, 5, 6]],
|
|
[[7, 8, 9], [10, 11, 12]]]]
|
|
```</p><ol><li>For the following input of shape `[4, 2, 2, 1]`, `block_shape = [2, 2]`, and
|
|
`crops = [[0, 0], [0, 0]]`:</li></ol><p>```prettyprint
|
|
x = [[[[1], [3]], [[5], [7]]],
|
|
[[[2], [4]], [[10], [12]]],
|
|
[[[5], [7]], [[13], [15]]],
|
|
[[[6], [8]], [[14], [16]]]]
|
|
```</p><p>The output tensor has shape `[1, 4, 4, 1]` and value:</p><p>```prettyprint
|
|
x = [[[1], [2], [3], [4]],
|
|
[[5], [6], [7], [8]],
|
|
[[9], [10], [11], [12]],
|
|
[[13], [14], [15], [16]]]
|
|
```</p><ol><li>For the following input of shape `[8, 1, 3, 1]`, `block_shape = [2, 2]`, and
|
|
`crops = [[0, 0], [2, 0]]`:</li></ol><p>```prettyprint
|
|
x = [[[[0], [1], [3]]], [[[0], [9], [11]]],
|
|
[[[0], [2], [4]]], [[[0], [10], [12]]],
|
|
[[[0], [5], [7]]], [[[0], [13], [15]]],
|
|
[[[0], [6], [8]]], [[[0], [14], [16]]]]
|
|
```</p><p>The output tensor has shape `[2, 2, 4, 1]` and value:</p><p>```prettyprint
|
|
x = [[[[1], [2], [3], [4]],
|
|
[[5], [6], [7], [8]]],
|
|
[[[9], [10], [11], [12]],
|
|
[[13], [14], [15], [16]]]]
|
|
```</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>BatchToSpace for N-D tensors of type T.</p><p>This operation reshapes the "batch" dimension 0 into `M + 1` dimensions of shape
|
|
`block_shape + [batch]`, interleaves these blocks back into the grid defined by
|
|
the spatial dimensions `[1, ..., M]`, to obtain a result with the same rank as
|
|
the input. The spatial dimensions of this intermediate result are then
|
|
optionally cropped according to <code>crops</code> to produce the output. This is the
|
|
reverse of SpaceToBatch. See below for a precise description.</p></div></div><div class="top"><p class="src"><a name="v:batchToSpaceND-39-" class="def">batchToSpaceND'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tblock_shape, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tcrops)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: N-D with shape `input_shape = [batch] + spatial_shape + remaining_shape`,
|
|
where spatial_shape has M dimensions.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tblock_shape</td><td class="doc"><p><strong>block_shape</strong>: 1-D with shape `[M]`, all values must be >= 1.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tcrops</td><td class="doc"><p><strong>crops</strong>: 2-D with shape `[M, 2]`, all values must be >= 0.
|
|
`crops[i] = [crop_start, crop_end]` specifies the amount to crop from input
|
|
dimension `i + 1`, which corresponds to spatial dimension <code>i</code>. It is
|
|
required that
|
|
`crop_start[i] + crop_end[i] <= block_shape[i] * input_shape[i + 1]`.</p><p>This operation is equivalent to the following steps:</p><ol><li>Reshape <code>input</code> to <code>reshaped</code> of shape:
|
|
[block_shape[0], ..., block_shape[M-1],
|
|
batch / prod(block_shape),
|
|
input_shape[1], ..., input_shape[N-1]]</li><li>Permute dimensions of <code>reshaped</code> to produce <code>permuted</code> of shape
|
|
[batch / prod(block_shape),</li></ol><p>input_shape[1], block_shape[0],
|
|
...,
|
|
input_shape[M], block_shape[M-1],</p><p>input_shape[M+1], ..., input_shape[N-1]]</p><ol><li>Reshape <code>permuted</code> to produce <code>reshaped_permuted</code> of shape
|
|
[batch / prod(block_shape),</li></ol><p>input_shape[1] * block_shape[0],
|
|
...,
|
|
input_shape[M] * block_shape[M-1],</p><p>input_shape[M+1],
|
|
...,
|
|
input_shape[N-1]]</p><ol><li>Crop the start and end of dimensions `[1, ..., M]` of
|
|
<code>reshaped_permuted</code> according to <code>crops</code> to produce the output of shape:
|
|
[batch / prod(block_shape),</li></ol><p>input_shape[1] * block_shape[0] - crops[0,0] - crops[0,1],
|
|
...,
|
|
input_shape[M] * block_shape[M-1] - crops[M-1,0] - crops[M-1,1],</p><p>input_shape[M+1], ..., input_shape[N-1]]</p><p>Some examples:</p><ol><li>For the following input of shape `[4, 1, 1, 1]`, `block_shape = [2, 2]`, and
|
|
`crops = [[0, 0], [0, 0]]`:</li></ol><p>```prettyprint
|
|
[[[[1]]], [[[2]]], [[[3]]], [[[4]]]]
|
|
```</p><p>The output tensor has shape `[1, 2, 2, 1]` and value:</p><p>```prettyprint
|
|
x = [[[[1], [2]], [[3], [4]]]]
|
|
```</p><ol><li>For the following input of shape `[4, 1, 1, 3]`, `block_shape = [2, 2]`, and
|
|
`crops = [[0, 0], [0, 0]]`:</li></ol><p>```prettyprint
|
|
[[[1, 2, 3]], [[4, 5, 6]], [[7, 8, 9]], [[10, 11, 12]]]
|
|
```</p><p>The output tensor has shape `[1, 2, 2, 3]` and value:</p><p>```prettyprint
|
|
x = [[[[1, 2, 3], [4, 5, 6]],
|
|
[[7, 8, 9], [10, 11, 12]]]]
|
|
```</p><ol><li>For the following input of shape `[4, 2, 2, 1]`, `block_shape = [2, 2]`, and
|
|
`crops = [[0, 0], [0, 0]]`:</li></ol><p>```prettyprint
|
|
x = [[[[1], [3]], [[5], [7]]],
|
|
[[[2], [4]], [[10], [12]]],
|
|
[[[5], [7]], [[13], [15]]],
|
|
[[[6], [8]], [[14], [16]]]]
|
|
```</p><p>The output tensor has shape `[1, 4, 4, 1]` and value:</p><p>```prettyprint
|
|
x = [[[1], [2], [3], [4]],
|
|
[[5], [6], [7], [8]],
|
|
[[9], [10], [11], [12]],
|
|
[[13], [14], [15], [16]]]
|
|
```</p><ol><li>For the following input of shape `[8, 1, 3, 1]`, `block_shape = [2, 2]`, and
|
|
`crops = [[0, 0], [2, 0]]`:</li></ol><p>```prettyprint
|
|
x = [[[[0], [1], [3]]], [[[0], [9], [11]]],
|
|
[[[0], [2], [4]]], [[[0], [10], [12]]],
|
|
[[[0], [5], [7]]], [[[0], [13], [15]]],
|
|
[[[0], [6], [8]]], [[[0], [14], [16]]]]
|
|
```</p><p>The output tensor has shape `[2, 2, 4, 1]` and value:</p><p>```prettyprint
|
|
x = [[[[1], [2], [3], [4]],
|
|
[[5], [6], [7], [8]]],
|
|
[[[9], [10], [11], [12]],
|
|
[[13], [14], [15], [16]]]]
|
|
```</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:betainc" class="def">betainc</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>a</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>b</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Compute the regularized incomplete beta integral \(I_x(a, b)\).</p><p>The regularized incomplete beta integral is defined as:</p><p>```
|
|
I_x(a, b) = frac{B(x; a, b)}{B(a, b)}
|
|
```
|
|
where</p><p>```
|
|
B(x; a, b) = int_0^x t^{a-1} (1 - t)^{b-1} dt
|
|
```</p><p>is the incomplete beta function and \(B(a, b)\) is the *complete*
|
|
beta function.</p></div></div><div class="top"><p class="src"><a name="v:betainc-39-" class="def">betainc'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>a</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>b</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:biasAdd" class="def">biasAdd</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: Any number of dimensions.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>bias</strong>: 1-D with size the last dimension of <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Broadcasted sum of <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> and <code>bias</code>.</p></td></tr></table></div><div class="doc"><p>Adds <code>bias</code> to <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>.</p><p>This is a special case of `tf.add` where <code>bias</code> is restricted to be 1-D.
|
|
Broadcasting is supported, so <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> may have any number of dimensions.</p></div></div><div class="top"><p class="src"><a name="v:biasAdd-39-" class="def">biasAdd'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: Any number of dimensions.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>bias</strong>: 1-D with size the last dimension of <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Broadcasted sum of <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> and <code>bias</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:biasAddGrad" class="def">biasAddGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>out_backprop</strong>: Any number of dimensions.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 1-D with size the feature dimension of <code>out_backprop</code>.</p></td></tr></table></div><div class="doc"><p>The backward operation for <a href="BiasAdd.html">BiasAdd</a> on the "bias" tensor.</p><p>It accumulates all the values from out_backprop into the feature dimension.
|
|
For NHWC data format, the feature dimension is the last. For NCHW data format,
|
|
the feature dimension is the third-to-last.</p></div></div><div class="top"><p class="src"><a name="v:biasAddGrad-39-" class="def">biasAddGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>out_backprop</strong>: Any number of dimensions.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 1-D with size the feature dimension of <code>out_backprop</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:biasAddV1" class="def">biasAddV1</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: Any number of dimensions.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>bias</strong>: 1-D with size the last dimension of <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Broadcasted sum of <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> and <code>bias</code>.</p></td></tr></table></div><div class="doc"><p>Adds <code>bias</code> to <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>.</p><p>This is a deprecated version of BiasAdd and will be soon removed.</p><p>This is a special case of `tf.add` where <code>bias</code> is restricted to be 1-D.
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Broadcasting is supported, so <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> may have any number of dimensions.</p></div></div><div class="top"><p class="src"><a name="v:biasAddV1-39-" class="def">biasAddV1'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: Any number of dimensions.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>bias</strong>: 1-D with size the last dimension of <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Broadcasted sum of <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> and <code>bias</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:bitcast" class="def">bitcast</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` type')</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> type'</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Bitcasts a tensor from one type to another without copying data.</p><p>Given a tensor <code>input</code>, this operation returns a tensor that has the same buffer
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data as <code>input</code> with datatype `type`.</p><p>If the input datatype <code>T</code> is larger than the output datatype `type` then the
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shape changes from [...] to [..., sizeof(<code>T</code>)/sizeof(`type`)].</p><p>If <code>T</code> is smaller than `type`, the operator requires that the rightmost
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dimension be equal to sizeof(`type`)/sizeof(<code>T</code>). The shape then goes from
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[..., sizeof(`type`)/sizeof(<code>T</code>)] to [...].</p><ul><li>NOTE*: Bitcast is implemented as a low-level cast, so machines with different
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endian orderings will give different results.</li></ul></div></div><div class="top"><p class="src"><a name="v:bitcast-39-" class="def">bitcast'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` type')</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> type'</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:broadcastArgs" class="def">broadcastArgs</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>s0</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>s1</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>r0</strong></p></td></tr></table></div><div class="doc"><p>Return the shape of s0 op s1 with broadcast.</p><p>Given <code>s0</code> and <code>s1</code>, tensors that represent shapes, compute <code>r0</code>, the
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broadcasted shape. <code>s0</code>, <code>s1</code> and <code>r0</code> are all integer vectors.</p></div></div><div class="top"><p class="src"><a name="v:broadcastArgs-39-" class="def">broadcastArgs'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>s0</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>s1</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>r0</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:broadcastGradientArgs" class="def">broadcastGradientArgs</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>s0</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>s1</strong></p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>r0</strong>, <strong>r1</strong>)</p><ul><li><strong>r0</strong></li><li><strong>r1</strong></li></ul></td></tr></table></div><div class="doc"><p>Return the reduction indices for computing gradients of s0 op s1 with broadcast.</p><p>This is typically used by gradient computations for a broadcasting operation.</p></div></div><div class="top"><p class="src"><a name="v:broadcastGradientArgs-39-" class="def">broadcastGradientArgs'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>s0</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>s1</strong></p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>r0</strong>, <strong>r1</strong>)</p><ul><li><strong>r0</strong></li><li><strong>r1</strong></li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:cTCBeamSearchDecoder" class="def">cTCBeamSearchDecoder</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>beam_width</strong>: A scalar >= 0 (beam search beam width).</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>top_paths</strong>: A scalar >= 0, <= beam_width (controls output size).</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>inputs</strong>: 3-D, shape: `(max_time x batch_size x num_classes)`, the logits.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>sequence_length</strong>: A vector containing sequence lengths, size `(batch)`.</p></td></tr><tr><td class="src">-> ([<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>decoded_indices</strong>, <strong>decoded_values</strong>, <strong>decoded_shape</strong>, <strong>log_probability</strong>)</p><ul><li><strong>decoded_indices</strong>: A list (length: top_paths) of indices matrices. Matrix j,
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|
size `(total_decoded_outputs[j] x 2)`, has indices of a
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`SparseTensor<a href="int64,">2</a>`. The rows store: [batch, time].</li><li><strong>decoded_values</strong>: A list (length: top_paths) of values vectors. Vector j,
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|
size `(length total_decoded_outputs[j])`, has the values of a
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|
`SparseTensor<a href="int64,">2</a>`. The vector stores the decoded classes for beam j.</li><li><strong>decoded_shape</strong>: A list (length: top_paths) of shape vector. Vector j,
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|
size `(2)`, stores the shape of the decoded `SparseTensor[j]`.
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Its values are: `[batch_size, max_decoded_length[j]]`.</li><li><strong>log_probability</strong>: A matrix, shaped: `(batch_size x top_paths)`. The
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sequence log-probabilities.</li></ul></td></tr></table></div><div class="doc"><p>Performs beam search decoding on the logits given in input.</p><p>A note about the attribute merge_repeated: For the beam search decoder,
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this means that if consecutive entries in a beam are the same, only
|
|
the first of these is emitted. That is, when the top path is "A B B B B",
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"A B" is returned if merge_repeated = True but "A B B B B" is
|
|
returned if merge_repeated = False.</p></div></div><div class="top"><p class="src"><a name="v:cTCBeamSearchDecoder-39-" class="def">cTCBeamSearchDecoder'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>beam_width</strong>: A scalar >= 0 (beam search beam width).</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>top_paths</strong>: A scalar >= 0, <= beam_width (controls output size).</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>inputs</strong>: 3-D, shape: `(max_time x batch_size x num_classes)`, the logits.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>sequence_length</strong>: A vector containing sequence lengths, size `(batch)`.</p></td></tr><tr><td class="src">-> ([<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>decoded_indices</strong>, <strong>decoded_values</strong>, <strong>decoded_shape</strong>, <strong>log_probability</strong>)</p><ul><li><strong>decoded_indices</strong>: A list (length: top_paths) of indices matrices. Matrix j,
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|
size `(total_decoded_outputs[j] x 2)`, has indices of a
|
|
`SparseTensor<a href="int64,">2</a>`. The rows store: [batch, time].</li><li><strong>decoded_values</strong>: A list (length: top_paths) of values vectors. Vector j,
|
|
size `(length total_decoded_outputs[j])`, has the values of a
|
|
`SparseTensor<a href="int64,">2</a>`. The vector stores the decoded classes for beam j.</li><li><strong>decoded_shape</strong>: A list (length: top_paths) of shape vector. Vector j,
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|
size `(2)`, stores the shape of the decoded `SparseTensor[j]`.
|
|
Its values are: `[batch_size, max_decoded_length[j]]`.</li><li><strong>log_probability</strong>: A matrix, shaped: `(batch_size x top_paths)`. The
|
|
sequence log-probabilities.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:cTCGreedyDecoder" class="def">cTCGreedyDecoder</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>inputs</strong>: 3-D, shape: `(max_time x batch_size x num_classes)`, the logits.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>sequence_length</strong>: A vector containing sequence lengths, size `(batch_size)`.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>decoded_indices</strong>, <strong>decoded_values</strong>, <strong>decoded_shape</strong>, <strong>log_probability</strong>)</p><ul><li><strong>decoded_indices</strong>: Indices matrix, size `(total_decoded_outputs x 2)`,
|
|
of a `SparseTensor<a href="int64,">2</a>`. The rows store: [batch, time].</li><li><strong>decoded_values</strong>: Values vector, size: `(total_decoded_outputs)`,
|
|
of a `SparseTensor<a href="int64,">2</a>`. The vector stores the decoded classes.</li><li><strong>decoded_shape</strong>: Shape vector, size `(2)`, of the decoded SparseTensor.
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|
Values are: `[batch_size, max_decoded_length]`.</li><li><strong>log_probability</strong>: Matrix, size `(batch_size x 1)`, containing sequence
|
|
log-probabilities.</li></ul></td></tr></table></div><div class="doc"><p>Performs greedy decoding on the logits given in inputs.</p><p>A note about the attribute merge_repeated: if enabled, when
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|
consecutive logits' maximum indices are the same, only the first of
|
|
these is emitted. Labeling the blank <code><a href="../base-4.8.2.0/Prelude.html#v:-42-">*</a></code>, the sequence "A B B * B B"
|
|
becomes "A B" if merge_repeated = True and "A B B B B" if
|
|
merge_repeated = False.</p><p>Regardless of the value of merge_repeated, if the maximum index of a given
|
|
time and batch corresponds to the blank, index `(num_classes - 1)`, no new
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|
element is emitted.</p></div></div><div class="top"><p class="src"><a name="v:cTCGreedyDecoder-39-" class="def">cTCGreedyDecoder'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>inputs</strong>: 3-D, shape: `(max_time x batch_size x num_classes)`, the logits.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>sequence_length</strong>: A vector containing sequence lengths, size `(batch_size)`.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>decoded_indices</strong>, <strong>decoded_values</strong>, <strong>decoded_shape</strong>, <strong>log_probability</strong>)</p><ul><li><strong>decoded_indices</strong>: Indices matrix, size `(total_decoded_outputs x 2)`,
|
|
of a `SparseTensor<a href="int64,">2</a>`. The rows store: [batch, time].</li><li><strong>decoded_values</strong>: Values vector, size: `(total_decoded_outputs)`,
|
|
of a `SparseTensor<a href="int64,">2</a>`. The vector stores the decoded classes.</li><li><strong>decoded_shape</strong>: Shape vector, size `(2)`, of the decoded SparseTensor.
|
|
Values are: `[batch_size, max_decoded_length]`.</li><li><strong>log_probability</strong>: Matrix, size `(batch_size x 1)`, containing sequence
|
|
log-probabilities.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:cTCLoss" class="def">cTCLoss</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>inputs</strong>: 3-D, shape: `(max_time x batch_size x num_classes)`, the logits.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>labels_indices</strong>: The indices of a `SparseTensor<a href="int32,">2</a>`.
|
|
`labels_indices(i, :) == [b, t]` means `labels_values(i)` stores the id for
|
|
`(batch b, time t)`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>labels_values</strong>: The values (labels) associated with the given batch and time.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>sequence_length</strong>: A vector containing sequence lengths (batch).</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>loss</strong>, <strong>gradient</strong>)</p><ul><li><strong>loss</strong>: A vector (batch) containing log-probabilities.</li><li><strong>gradient</strong>: The gradient of <code>loss</code>. 3-D, shape:
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|
`(max_time x batch_size x num_classes)`.</li></ul></td></tr></table></div><div class="doc"><p>Calculates the CTC Loss (log probability) for each batch entry. Also calculates</p><p>the gradient. This class performs the softmax operation for you, so inputs
|
|
should be e.g. linear projections of outputs by an LSTM.</p></div></div><div class="top"><p class="src"><a name="v:cTCLoss-39-" class="def">cTCLoss'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>inputs</strong>: 3-D, shape: `(max_time x batch_size x num_classes)`, the logits.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>labels_indices</strong>: The indices of a `SparseTensor<a href="int32,">2</a>`.
|
|
`labels_indices(i, :) == [b, t]` means `labels_values(i)` stores the id for
|
|
`(batch b, time t)`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>labels_values</strong>: The values (labels) associated with the given batch and time.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>sequence_length</strong>: A vector containing sequence lengths (batch).</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>loss</strong>, <strong>gradient</strong>)</p><ul><li><strong>loss</strong>: A vector (batch) containing log-probabilities.</li><li><strong>gradient</strong>: The gradient of <code>loss</code>. 3-D, shape:
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|
`(max_time x batch_size x num_classes)`.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:cast" class="def">cast</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> srcT, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dstT)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 srcT</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dstT</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Cast x of type SrcT to y of DstT.</p></div></div><div class="top"><p class="src"><a name="v:cast-39-" class="def">cast'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> srcT, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dstT)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 srcT</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dstT</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:ceil" class="def">ceil</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Returns element-wise smallest integer in not less than x.</p></div></div><div class="top"><p class="src"><a name="v:ceil-39-" class="def">ceil'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:checkNumerics" class="def">checkNumerics</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>tensor</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Checks a tensor for NaN and Inf values.</p><p>When run, reports an <code>InvalidArgument</code> error if <code>tensor</code> has any values
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|
that are not a number (NaN) or infinity (Inf). Otherwise, passes <code>tensor</code> as-is.</p></div></div><div class="top"><p class="src"><a name="v:checkNumerics-39-" class="def">checkNumerics'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>tensor</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:cholesky" class="def">cholesky</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape is `[..., M, M]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Shape is `[..., M, M]`.</p></td></tr></table></div><div class="doc"><p>Computes the Cholesky decomposition of one or more square matrices.</p><p>The input is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions
|
|
form square matrices, with the same constraints as the single matrix Cholesky
|
|
decomposition above. The output is a tensor of the same shape as the input
|
|
containing the Cholesky decompositions for all input submatrices `[..., :, :]`.</p></div></div><div class="top"><p class="src"><a name="v:cholesky-39-" class="def">cholesky'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape is `[..., M, M]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Shape is `[..., M, M]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:choleskyGrad" class="def">choleskyGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>l</strong>: Output of batch Cholesky algorithm l = cholesky(A). Shape is `[..., M, M]`.
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Algorithm depends only on lower triangular part of the innermost matrices of
|
|
this tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>grad</strong>: df/dl where f is some scalar function. Shape is `[..., M, M]`.
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|
Algorithm depends only on lower triangular part of the innermost matrices of
|
|
this tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Symmetrized version of df/dA . Shape is `[..., M, M]`</p></td></tr></table></div><div class="doc"><p>Computes the reverse mode backpropagated gradient of the Cholesky algorithm.</p><p>For an explanation see "Differentiation of the Cholesky algorithm" by
|
|
Iain Murray <a href="http://arxiv.org/abs/1602.07527">http://arxiv.org/abs/1602.07527</a>.</p></div></div><div class="top"><p class="src"><a name="v:choleskyGrad-39-" class="def">choleskyGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>l</strong>: Output of batch Cholesky algorithm l = cholesky(A). Shape is `[..., M, M]`.
|
|
Algorithm depends only on lower triangular part of the innermost matrices of
|
|
this tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>grad</strong>: df/dl where f is some scalar function. Shape is `[..., M, M]`.
|
|
Algorithm depends only on lower triangular part of the innermost matrices of
|
|
this tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Symmetrized version of df/dA . Shape is `[..., M, M]`</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:complex" class="def">complex</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tout)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>real</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>imag</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tout</td><td class="doc"><p><strong>out</strong></p></td></tr></table></div><div class="doc"><p>Converts two real numbers to a complex number.</p><p>Given a tensor <code><a href="TensorFlow-GenOps-Core.html#v:real">real</a></code> representing the real part of a complex number, and a
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tensor <code><a href="TensorFlow-GenOps-Core.html#v:imag">imag</a></code> representing the imaginary part of a complex number, this
|
|
operation returns complex numbers elementwise of the form \(a + bj\), where
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|
*a* represents the <code><a href="TensorFlow-GenOps-Core.html#v:real">real</a></code> part and *b* represents the <code><a href="TensorFlow-GenOps-Core.html#v:imag">imag</a></code> part.</p><p>The input tensors <code><a href="TensorFlow-GenOps-Core.html#v:real">real</a></code> and <code><a href="TensorFlow-GenOps-Core.html#v:imag">imag</a></code> must have the same shape.</p><p>For example:</p><p>```
|
|
# tensor <code><a href="TensorFlow-GenOps-Core.html#v:real">real</a></code> is [2.25, 3.25]
|
|
# tensor <code><a href="TensorFlow-GenOps-Core.html#v:imag">imag</a></code> is [4.75, 5.75]
|
|
tf.complex(real, imag) ==> [[2.25 + 4.75j], [3.25 + 5.75j]]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:complex-39-" class="def">complex'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tout)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>real</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>imag</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tout</td><td class="doc"><p><strong>out</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:complexAbs" class="def">complexAbs</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tout)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tout</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes the complex absolute value of a tensor.</p><p>Given a tensor <code>x</code> of complex numbers, this operation returns a tensor of type
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<code>float</code> or <code>double</code> that is the absolute value of each element in <code>x</code>. All
|
|
elements in <code>x</code> must be complex numbers of the form \(a + bj\). The absolute
|
|
value is computed as \( sqrt{a^2 + b^2}\).</p></div></div><div class="top"><p class="src"><a name="v:complexAbs-39-" class="def">complexAbs'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tout)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tout</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:computeAccidentalHits" class="def">computeAccidentalHits</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_true</strong>: Number of true labels per context.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>true_classes</strong>: The true_classes output of UnpackSparseLabels.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sampled_candidates</strong>: The sampled_candidates output of CandidateSampler.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>indices</strong>, <strong>ids</strong>, <strong>weights</strong>)</p><ul><li><strong>indices</strong>: A vector of indices corresponding to rows of true_candidates.</li><li><strong>ids</strong>: A vector of IDs of positions in sampled_candidates that match a true_label
|
|
for the row with the corresponding index in indices.</li><li><strong>weights</strong>: A vector of the same length as indices and ids, in which each element
|
|
is -FLOAT_MAX.</li></ul></td></tr></table></div><div class="doc"><p>Computes the ids of the positions in sampled_candidates that match true_labels.</p><p>When doing log-odds NCE, the result of this op should be passed through a
|
|
SparseToDense op, then added to the logits of the sampled candidates. This has
|
|
the effect of <code>removing</code> the sampled labels that match the true labels by
|
|
making the classifier sure that they are sampled labels.</p></div></div><div class="top"><p class="src"><a name="v:computeAccidentalHits-39-" class="def">computeAccidentalHits'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_true</strong>: Number of true labels per context.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>true_classes</strong>: The true_classes output of UnpackSparseLabels.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sampled_candidates</strong>: The sampled_candidates output of CandidateSampler.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>indices</strong>, <strong>ids</strong>, <strong>weights</strong>)</p><ul><li><strong>indices</strong>: A vector of indices corresponding to rows of true_candidates.</li><li><strong>ids</strong>: A vector of IDs of positions in sampled_candidates that match a true_label
|
|
for the row with the corresponding index in indices.</li><li><strong>weights</strong>: A vector of the same length as indices and ids, in which each element
|
|
is -FLOAT_MAX.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:concat" class="def">concat</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>concat_dim</strong>: 0-D. The dimension along which to concatenate. Must be in the
|
|
range [0, rank(values)).</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t]</td><td class="doc"><p><strong>values</strong>: The <code>N</code> Tensors to concatenate. Their ranks and types must match,
|
|
and their sizes must match in all dimensions except <code>concat_dim</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: A <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with the concatenation of values stacked along the
|
|
<code>concat_dim</code> dimension. This tensor's shape matches that of <code>values</code> except
|
|
in <code>concat_dim</code> where it has the sum of the sizes.</p></td></tr></table></div><div class="doc"><p>Concatenates tensors along one dimension.</p></div></div><div class="top"><p class="src"><a name="v:concat-39-" class="def">concat'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>concat_dim</strong>: 0-D. The dimension along which to concatenate. Must be in the
|
|
range [0, rank(values)).</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t]</td><td class="doc"><p><strong>values</strong>: The <code>N</code> Tensors to concatenate. Their ranks and types must match,
|
|
and their sizes must match in all dimensions except <code>concat_dim</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: A <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with the concatenation of values stacked along the
|
|
<code>concat_dim</code> dimension. This tensor's shape matches that of <code>values</code> except
|
|
in <code>concat_dim</code> where it has the sum of the sizes.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:concatOffset" class="def">concatOffset</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>concat_dim</strong>: The dimension along which to concatenate.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>]</td><td class="doc"><p><strong>shape</strong>: The <code>N</code> int32 vectors representing shape of tensors being concatenated.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>]</td><td class="doc"><p><strong>offset</strong>: The <code>N</code> int32 vectors representing the starting offset
|
|
of input tensors within the concatenated output.</p><p>This is typically used by gradient computations for a concat operation.</p></td></tr></table></div><div class="doc"><p>Computes offsets of concat inputs within its output.</p><p>For example:</p><p>```prettyprint
|
|
# <code>x</code> is [2, 2, 7]
|
|
# <code>y</code> is [2, 3, 7]
|
|
# <code>z</code> is [2, 5, 7]
|
|
concat_offset(2, [x, y, z]) => [0, 0, 0], [0, 2, 0], [0, 5, 0]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:concatOffset-39-" class="def">concatOffset'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>concat_dim</strong>: The dimension along which to concatenate.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>]</td><td class="doc"><p><strong>shape</strong>: The <code>N</code> int32 vectors representing shape of tensors being concatenated.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>]</td><td class="doc"><p><strong>offset</strong>: The <code>N</code> int32 vectors representing the starting offset
|
|
of input tensors within the concatenated output.</p><p>This is typically used by gradient computations for a concat operation.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:concatV2" class="def">concatV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t]</td><td class="doc"><p><strong>values</strong>: List of <code>N</code> Tensors to concatenate. Their ranks and types must match,
|
|
and their sizes must match in all dimensions except <code>concat_dim</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>axis</strong>: 0-D. The dimension along which to concatenate. Must be in the
|
|
range [-rank(values), rank(values)).</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: A <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with the concatenation of values stacked along the
|
|
<code>concat_dim</code> dimension. This tensor's shape matches that of <code>values</code> except
|
|
in <code>concat_dim</code> where it has the sum of the sizes.</p></td></tr></table></div><div class="doc"><p>Concatenates tensors along one dimension.</p></div></div><div class="top"><p class="src"><a name="v:concatV2-39-" class="def">concatV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t]</td><td class="doc"><p><strong>values</strong>: List of <code>N</code> Tensors to concatenate. Their ranks and types must match,
|
|
and their sizes must match in all dimensions except <code>concat_dim</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>axis</strong>: 0-D. The dimension along which to concatenate. Must be in the
|
|
range [-rank(values), rank(values)).</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: A <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with the concatenation of values stacked along the
|
|
<code>concat_dim</code> dimension. This tensor's shape matches that of <code>values</code> except
|
|
in <code>concat_dim</code> where it has the sum of the sizes.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:conditionalAccumulator" class="def">conditionalAccumulator</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>dtype</strong>: The type of the value being accumulated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: The shape of the values, can be [], in which case shape is unknown.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong>: The handle to the accumulator.</p></td></tr></table></div><div class="doc"><p>A conditional accumulator for aggregating gradients. The accumulator accepts</p><p>gradients marked with local_step greater or equal to the most recent global_step
|
|
known to the accumulator. The average can be extracted from the accumulator,
|
|
provided sufficient gradients have been accumulated. Extracting the average
|
|
automatically resets the aggregate to 0, and increments the global_step recorded
|
|
by the accumulator.</p></div></div><div class="top"><p class="src"><a name="v:conditionalAccumulator-39-" class="def">conditionalAccumulator'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>dtype</strong>: The type of the value being accumulated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: The shape of the values, can be [], in which case shape is unknown.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong>: The handle to the accumulator.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:conj" class="def">conj</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Returns the complex conjugate of a complex number.</p><p>Given a tensor <code>input</code> of complex numbers, this operation returns a tensor of
|
|
complex numbers that are the complex conjugate of each element in <code>input</code>. The
|
|
complex numbers in <code>input</code> must be of the form \(a + bj\), where *a* is the
|
|
real part and *b* is the imaginary part.</p><p>The complex conjugate returned by this operation is of the form \(a - bj\).</p><p>For example:</p><p>```
|
|
# tensor <code>input</code> is [-2.25 + 4.75j, 3.25 + 5.75j]
|
|
tf.conj(input) ==> [-2.25 - 4.75j, 3.25 - 5.75j]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:conj-39-" class="def">conj'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:const" class="def">const</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Returns a constant tensor.</p></div></div><div class="top"><p class="src"><a name="v:const-39-" class="def">const'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:controlTrigger" class="def">controlTrigger</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></p><div class="doc"><p>Does nothing. Serves as a control trigger for scheduling.</p><p>Only useful as a placeholder for control edges.</p></div></div><div class="top"><p class="src"><a name="v:controlTrigger-39-" class="def">controlTrigger'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></p></div><div class="top"><p class="src"><a name="v:conv2D" class="def">conv2D</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Computes a 2-D convolution given 4-D <code>input</code> and <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code> tensors.</p><p>Given an input tensor of shape `[batch, in_height, in_width, in_channels]`
|
|
and a filter / kernel tensor of shape
|
|
`[filter_height, filter_width, in_channels, out_channels]`, this op
|
|
performs the following:</p><ol><li>Flattens the filter to a 2-D matrix with shape
|
|
`[filter_height * filter_width * in_channels, output_channels]`.</li><li>Extracts image patches from the input tensor to form a *virtual*
|
|
tensor of shape `[batch, out_height, out_width,
|
|
filter_height * filter_width * in_channels]`.</li><li>For each patch, right-multiplies the filter matrix and the image patch
|
|
vector.</li></ol><p>In detail, with the default NHWC format,</p><p>output[b, i, j, k] =
|
|
sum_{di, dj, q} input[b, strides[1] * i + di, strides[2] * j + dj, q] *
|
|
filter[di, dj, q, k]</p><p>Must have `strides[0] = strides[3] = 1`. For the most common case of the same
|
|
horizontal and vertices strides, `strides = [1, stride, stride, 1]`.</p></div></div><div class="top"><p class="src"><a name="v:conv2D-39-" class="def">conv2D'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:conv2DBackpropFilter" class="def">conv2DBackpropFilter</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, in_height, in_width, in_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>filter_sizes</strong>: An integer vector representing the tensor shape of <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code>,
|
|
where <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code> is a 4-D
|
|
`[filter_height, filter_width, in_channels, out_channels]` tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: 4-D with shape `[batch, out_height, out_width, out_channels]`.
|
|
Gradients w.r.t. the output of the convolution.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D with shape
|
|
`[filter_height, filter_width, in_channels, out_channels]`. Gradient w.r.t.
|
|
the <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code> input of the convolution.</p></td></tr></table></div><div class="doc"><p>Computes the gradients of convolution with respect to the filter.</p></div></div><div class="top"><p class="src"><a name="v:conv2DBackpropFilter-39-" class="def">conv2DBackpropFilter'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, in_height, in_width, in_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>filter_sizes</strong>: An integer vector representing the tensor shape of <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code>,
|
|
where <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code> is a 4-D
|
|
`[filter_height, filter_width, in_channels, out_channels]` tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: 4-D with shape `[batch, out_height, out_width, out_channels]`.
|
|
Gradients w.r.t. the output of the convolution.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D with shape
|
|
`[filter_height, filter_width, in_channels, out_channels]`. Gradient w.r.t.
|
|
the <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code> input of the convolution.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:conv2DBackpropInput" class="def">conv2DBackpropInput</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>input_sizes</strong>: An integer vector representing the shape of <code>input</code>,
|
|
where <code>input</code> is a 4-D `[batch, height, width, channels]` tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong>: 4-D with shape
|
|
`[filter_height, filter_width, in_channels, out_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: 4-D with shape `[batch, out_height, out_width, out_channels]`.
|
|
Gradients w.r.t. the output of the convolution.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D with shape `[batch, in_height, in_width, in_channels]`. Gradient
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w.r.t. the input of the convolution.</p></td></tr></table></div><div class="doc"><p>Computes the gradients of convolution with respect to the input.</p></div></div><div class="top"><p class="src"><a name="v:conv2DBackpropInput-39-" class="def">conv2DBackpropInput'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>input_sizes</strong>: An integer vector representing the shape of <code>input</code>,
|
|
where <code>input</code> is a 4-D `[batch, height, width, channels]` tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong>: 4-D with shape
|
|
`[filter_height, filter_width, in_channels, out_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: 4-D with shape `[batch, out_height, out_width, out_channels]`.
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Gradients w.r.t. the output of the convolution.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D with shape `[batch, in_height, in_width, in_channels]`. Gradient
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w.r.t. the input of the convolution.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:conv3D" class="def">conv3D</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape `[batch, in_depth, in_height, in_width, in_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong>: Shape `[filter_depth, filter_height, filter_width, in_channels,
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out_channels]`. <code>in_channels</code> must match between <code>input</code> and <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Computes a 3-D convolution given 5-D <code>input</code> and <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code> tensors.</p><p>In signal processing, cross-correlation is a measure of similarity of
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two waveforms as a function of a time-lag applied to one of them. This
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is also known as a sliding dot product or sliding inner-product.</p><p>Our Conv3D implements a form of cross-correlation.</p></div></div><div class="top"><p class="src"><a name="v:conv3D-39-" class="def">conv3D'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape `[batch, in_depth, in_height, in_width, in_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong>: Shape `[filter_depth, filter_height, filter_width, in_channels,
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|
out_channels]`. <code>in_channels</code> must match between <code>input</code> and <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:conv3DBackpropFilter" class="def">conv3DBackpropFilter</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape `[batch, depth, rows, cols, in_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong>: Shape `[depth, rows, cols, in_channels, out_channels]`.
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|
<code>in_channels</code> must match between <code>input</code> and <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: Backprop signal of shape `[batch, out_depth, out_rows, out_cols,
|
|
out_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Computes the gradients of 3-D convolution with respect to the filter.</p></div></div><div class="top"><p class="src"><a name="v:conv3DBackpropFilter-39-" class="def">conv3DBackpropFilter'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape `[batch, depth, rows, cols, in_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong>: Shape `[depth, rows, cols, in_channels, out_channels]`.
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|
<code>in_channels</code> must match between <code>input</code> and <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: Backprop signal of shape `[batch, out_depth, out_rows, out_cols,
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|
out_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:conv3DBackpropFilterV2" class="def">conv3DBackpropFilterV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape `[batch, depth, rows, cols, in_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>filter_sizes</strong>: An integer vector representing the tensor shape of <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code>,
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|
where <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code> is a 5-D
|
|
`[filter_depth, filter_height, filter_width, in_channels, out_channels]`
|
|
tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: Backprop signal of shape `[batch, out_depth, out_rows, out_cols,
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|
out_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Computes the gradients of 3-D convolution with respect to the filter.</p></div></div><div class="top"><p class="src"><a name="v:conv3DBackpropFilterV2-39-" class="def">conv3DBackpropFilterV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape `[batch, depth, rows, cols, in_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>filter_sizes</strong>: An integer vector representing the tensor shape of <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code>,
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|
where <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code> is a 5-D
|
|
`[filter_depth, filter_height, filter_width, in_channels, out_channels]`
|
|
tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: Backprop signal of shape `[batch, out_depth, out_rows, out_cols,
|
|
out_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:conv3DBackpropInput" class="def">conv3DBackpropInput</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape `[batch, depth, rows, cols, in_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong>: Shape `[depth, rows, cols, in_channels, out_channels]`.
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|
<code>in_channels</code> must match between <code>input</code> and <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: Backprop signal of shape `[batch, out_depth, out_rows, out_cols,
|
|
out_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Computes the gradients of 3-D convolution with respect to the input.</p></div></div><div class="top"><p class="src"><a name="v:conv3DBackpropInput-39-" class="def">conv3DBackpropInput'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape `[batch, depth, rows, cols, in_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong>: Shape `[depth, rows, cols, in_channels, out_channels]`.
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|
<code>in_channels</code> must match between <code>input</code> and <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: Backprop signal of shape `[batch, out_depth, out_rows, out_cols,
|
|
out_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:conv3DBackpropInputV2" class="def">conv3DBackpropInputV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>input_sizes</strong>: An integer vector representing the tensor shape of <code>input</code>,
|
|
where <code>input</code> is a 5-D
|
|
`[batch, depth, rows, cols, in_channels]` tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong>: Shape `[depth, rows, cols, in_channels, out_channels]`.
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|
<code>in_channels</code> must match between <code>input</code> and <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: Backprop signal of shape `[batch, out_depth, out_rows, out_cols,
|
|
out_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Computes the gradients of 3-D convolution with respect to the input.</p></div></div><div class="top"><p class="src"><a name="v:conv3DBackpropInputV2-39-" class="def">conv3DBackpropInputV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>input_sizes</strong>: An integer vector representing the tensor shape of <code>input</code>,
|
|
where <code>input</code> is a 5-D
|
|
`[batch, depth, rows, cols, in_channels]` tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong>: Shape `[depth, rows, cols, in_channels, out_channels]`.
|
|
<code>in_channels</code> must match between <code>input</code> and <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: Backprop signal of shape `[batch, out_depth, out_rows, out_cols,
|
|
out_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:copy" class="def">copy</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Input tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Output tensor, deep-copied from input.</p></td></tr></table></div><div class="doc"><p>Copy Op.</p><p>Performs CPU-to-CPU or GPU-to-GPU deep-copying of tensor, depending on the
|
|
device on which the tensor is allocated.</p><p>Unlike the CopyHost Op, this op does not have HostMemory constraint on its
|
|
input or output.</p></div></div><div class="top"><p class="src"><a name="v:copy-39-" class="def">copy'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Input tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Output tensor, deep-copied from input.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:copyHost" class="def">copyHost</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Input tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Output tensor, deep-copied from input.</p></td></tr></table></div><div class="doc"><p>Copy Host Op.</p><p>Performs CPU-to-CPU deep-copying of tensor.</p><p>Unlike the Copy Op, this op has HostMemory constraint on its input or output.</p></div></div><div class="top"><p class="src"><a name="v:copyHost-39-" class="def">copyHost'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Input tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Output tensor, deep-copied from input.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:cos" class="def">cos</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes cos of x element-wise.</p></div></div><div class="top"><p class="src"><a name="v:cos-39-" class="def">cos'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:countUpTo" class="def">countUpTo</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>limit</strong>: If incrementing ref would bring it above limit, instead generates an
|
|
<code>OutOfRange</code> error.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: Should be from a scalar <code>Variable</code> node.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</td><td class="doc"><p><strong>output</strong>: A copy of the input before increment. If nothing else modifies the
|
|
input, the values produced will all be distinct.</p></td></tr></table></div><div class="doc"><p>Increments <code>ref</code> until it reaches <code>limit</code>.</p></div></div><div class="top"><p class="src"><a name="v:countUpTo-39-" class="def">countUpTo'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>limit</strong>: If incrementing ref would bring it above limit, instead generates an
|
|
<code>OutOfRange</code> error.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: Should be from a scalar <code>Variable</code> node.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</td><td class="doc"><p><strong>output</strong>: A copy of the input before increment. If nothing else modifies the
|
|
input, the values produced will all be distinct.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:cropAndResize" class="def">cropAndResize</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>image</strong>: A 4-D tensor of shape `[batch, image_height, image_width, depth]`.
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|
Both <code>image_height</code> and <code>image_width</code> need to be positive.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>boxes</strong>: A 2-D tensor of shape `[num_boxes, 4]`. The <code>i</code>-th row of the tensor
|
|
specifies the coordinates of a box in the `box_ind[i]` image and is specified
|
|
in normalized coordinates `[y1, x1, y2, x2]`. A normalized coordinate value of
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|
<code>y</code> is mapped to the image coordinate at `y * (image_height - 1)`, so as the
|
|
`[0, 1]` interval of normalized image height is mapped to
|
|
`[0, image_height - 1] in image height coordinates. We do allow y1 > y2, in
|
|
which case the sampled crop is an up-down flipped version of the original
|
|
image. The width dimension is treated similarly. Normalized coordinates
|
|
outside the `[0, 1]` range are allowed, in which case we use
|
|
<code>extrapolation_value</code> to extrapolate the input image values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>box_ind</strong>: A 1-D tensor of shape `[num_boxes]` with int32 values in `[0, batch)`.
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|
The value of `box_ind[i]` specifies the image that the <code>i</code>-th box refers to.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>crop_size</strong>: A 1-D tensor of 2 elements, `size = [crop_height, crop_width]`. All
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|
cropped image patches are resized to this size. The aspect ratio of the image
|
|
content is not preserved. Both <code>crop_height</code> and <code>crop_width</code> need to be
|
|
positive.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>crops</strong>: A 4-D tensor of shape `[num_boxes, crop_height, crop_width, depth]`.</p></td></tr></table></div><div class="doc"><p>Extracts crops from the input image tensor and bilinearly resizes them (possibly</p><p>with aspect ratio change) to a common output size specified by <code>crop_size</code>. This
|
|
is more general than the <code>crop_to_bounding_box</code> op which extracts a fixed size
|
|
slice from the input image and does not allow resizing or aspect ratio change.</p><p>Returns a tensor with <code>crops</code> from the input <code>image</code> at positions defined at the
|
|
bounding box locations in <code>boxes</code>. The cropped boxes are all resized (with
|
|
bilinear interpolation) to a fixed `size = [crop_height, crop_width]`. The
|
|
result is a 4-D tensor `[num_boxes, crop_height, crop_width, depth]`.</p></div></div><div class="top"><p class="src"><a name="v:cropAndResize-39-" class="def">cropAndResize'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>image</strong>: A 4-D tensor of shape `[batch, image_height, image_width, depth]`.
|
|
Both <code>image_height</code> and <code>image_width</code> need to be positive.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>boxes</strong>: A 2-D tensor of shape `[num_boxes, 4]`. The <code>i</code>-th row of the tensor
|
|
specifies the coordinates of a box in the `box_ind[i]` image and is specified
|
|
in normalized coordinates `[y1, x1, y2, x2]`. A normalized coordinate value of
|
|
<code>y</code> is mapped to the image coordinate at `y * (image_height - 1)`, so as the
|
|
`[0, 1]` interval of normalized image height is mapped to
|
|
`[0, image_height - 1] in image height coordinates. We do allow y1 > y2, in
|
|
which case the sampled crop is an up-down flipped version of the original
|
|
image. The width dimension is treated similarly. Normalized coordinates
|
|
outside the `[0, 1]` range are allowed, in which case we use
|
|
<code>extrapolation_value</code> to extrapolate the input image values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>box_ind</strong>: A 1-D tensor of shape `[num_boxes]` with int32 values in `[0, batch)`.
|
|
The value of `box_ind[i]` specifies the image that the <code>i</code>-th box refers to.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>crop_size</strong>: A 1-D tensor of 2 elements, `size = [crop_height, crop_width]`. All
|
|
cropped image patches are resized to this size. The aspect ratio of the image
|
|
content is not preserved. Both <code>crop_height</code> and <code>crop_width</code> need to be
|
|
positive.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>crops</strong>: A 4-D tensor of shape `[num_boxes, crop_height, crop_width, depth]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:cropAndResizeGradBoxes" class="def">cropAndResizeGradBoxes</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>grads</strong>: A 4-D tensor of shape `[num_boxes, crop_height, crop_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>image</strong>: A 4-D tensor of shape `[batch, image_height, image_width, depth]`.
|
|
Both <code>image_height</code> and <code>image_width</code> need to be positive.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>boxes</strong>: A 2-D tensor of shape `[num_boxes, 4]`. The <code>i</code>-th row of the tensor
|
|
specifies the coordinates of a box in the `box_ind[i]` image and is specified
|
|
in normalized coordinates `[y1, x1, y2, x2]`. A normalized coordinate value of
|
|
<code>y</code> is mapped to the image coordinate at `y * (image_height - 1)`, so as the
|
|
`[0, 1]` interval of normalized image height is mapped to
|
|
`[0, image_height - 1] in image height coordinates. We do allow y1 > y2, in
|
|
which case the sampled crop is an up-down flipped version of the original
|
|
image. The width dimension is treated similarly. Normalized coordinates
|
|
outside the `[0, 1]` range are allowed, in which case we use
|
|
<code>extrapolation_value</code> to extrapolate the input image values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>box_ind</strong>: A 1-D tensor of shape `[num_boxes]` with int32 values in `[0, batch)`.
|
|
The value of `box_ind[i]` specifies the image that the <code>i</code>-th box refers to.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>output</strong>: A 2-D tensor of shape `[num_boxes, 4]`.</p></td></tr></table></div><div class="doc"><p>Computes the gradient of the crop_and_resize op wrt the input boxes tensor.</p></div></div><div class="top"><p class="src"><a name="v:cropAndResizeGradBoxes-39-" class="def">cropAndResizeGradBoxes'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>grads</strong>: A 4-D tensor of shape `[num_boxes, crop_height, crop_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>image</strong>: A 4-D tensor of shape `[batch, image_height, image_width, depth]`.
|
|
Both <code>image_height</code> and <code>image_width</code> need to be positive.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>boxes</strong>: A 2-D tensor of shape `[num_boxes, 4]`. The <code>i</code>-th row of the tensor
|
|
specifies the coordinates of a box in the `box_ind[i]` image and is specified
|
|
in normalized coordinates `[y1, x1, y2, x2]`. A normalized coordinate value of
|
|
<code>y</code> is mapped to the image coordinate at `y * (image_height - 1)`, so as the
|
|
`[0, 1]` interval of normalized image height is mapped to
|
|
`[0, image_height - 1] in image height coordinates. We do allow y1 > y2, in
|
|
which case the sampled crop is an up-down flipped version of the original
|
|
image. The width dimension is treated similarly. Normalized coordinates
|
|
outside the `[0, 1]` range are allowed, in which case we use
|
|
<code>extrapolation_value</code> to extrapolate the input image values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>box_ind</strong>: A 1-D tensor of shape `[num_boxes]` with int32 values in `[0, batch)`.
|
|
The value of `box_ind[i]` specifies the image that the <code>i</code>-th box refers to.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>output</strong>: A 2-D tensor of shape `[num_boxes, 4]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:cropAndResizeGradImage" class="def">cropAndResizeGradImage</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>grads</strong>: A 4-D tensor of shape `[num_boxes, crop_height, crop_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>boxes</strong>: A 2-D tensor of shape `[num_boxes, 4]`. The <code>i</code>-th row of the tensor
|
|
specifies the coordinates of a box in the `box_ind[i]` image and is specified
|
|
in normalized coordinates `[y1, x1, y2, x2]`. A normalized coordinate value of
|
|
<code>y</code> is mapped to the image coordinate at `y * (image_height - 1)`, so as the
|
|
`[0, 1]` interval of normalized image height is mapped to
|
|
`[0, image_height - 1] in image height coordinates. We do allow y1 > y2, in
|
|
which case the sampled crop is an up-down flipped version of the original
|
|
image. The width dimension is treated similarly. Normalized coordinates
|
|
outside the `[0, 1]` range are allowed, in which case we use
|
|
<code>extrapolation_value</code> to extrapolate the input image values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>box_ind</strong>: A 1-D tensor of shape `[num_boxes]` with int32 values in `[0, batch)`.
|
|
The value of `box_ind[i]` specifies the image that the <code>i</code>-th box refers to.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>image_size</strong>: A 1-D tensor with value `[batch, image_height, image_width, depth]`
|
|
containing the original image size. Both <code>image_height</code> and <code>image_width</code> need
|
|
to be positive.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: A 4-D tensor of shape `[batch, image_height, image_width, depth]`.</p></td></tr></table></div><div class="doc"><p>Computes the gradient of the crop_and_resize op wrt the input image tensor.</p></div></div><div class="top"><p class="src"><a name="v:cropAndResizeGradImage-39-" class="def">cropAndResizeGradImage'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>grads</strong>: A 4-D tensor of shape `[num_boxes, crop_height, crop_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>boxes</strong>: A 2-D tensor of shape `[num_boxes, 4]`. The <code>i</code>-th row of the tensor
|
|
specifies the coordinates of a box in the `box_ind[i]` image and is specified
|
|
in normalized coordinates `[y1, x1, y2, x2]`. A normalized coordinate value of
|
|
<code>y</code> is mapped to the image coordinate at `y * (image_height - 1)`, so as the
|
|
`[0, 1]` interval of normalized image height is mapped to
|
|
`[0, image_height - 1] in image height coordinates. We do allow y1 > y2, in
|
|
which case the sampled crop is an up-down flipped version of the original
|
|
image. The width dimension is treated similarly. Normalized coordinates
|
|
outside the `[0, 1]` range are allowed, in which case we use
|
|
<code>extrapolation_value</code> to extrapolate the input image values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>box_ind</strong>: A 1-D tensor of shape `[num_boxes]` with int32 values in `[0, batch)`.
|
|
The value of `box_ind[i]` specifies the image that the <code>i</code>-th box refers to.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>image_size</strong>: A 1-D tensor with value `[batch, image_height, image_width, depth]`
|
|
containing the original image size. Both <code>image_height</code> and <code>image_width</code> need
|
|
to be positive.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: A 4-D tensor of shape `[batch, image_height, image_width, depth]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:cross" class="def">cross</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>a</strong>: A tensor containing 3-element vectors.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>b</strong>: Another tensor, of same type and shape as <code>a</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>product</strong>: Pairwise cross product of the vectors in <code>a</code> and <code>b</code>.</p></td></tr></table></div><div class="doc"><p>Compute the pairwise cross product.</p><p><code>a</code> and <code>b</code> must be the same shape; they can either be simple 3-element vectors,
|
|
or any shape where the innermost dimension is 3. In the latter case, each pair
|
|
of corresponding 3-element vectors is cross-multiplied independently.</p></div></div><div class="top"><p class="src"><a name="v:cross-39-" class="def">cross'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>a</strong>: A tensor containing 3-element vectors.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>b</strong>: Another tensor, of same type and shape as <code>a</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>product</strong>: Pairwise cross product of the vectors in <code>a</code> and <code>b</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:cumprod" class="def">cumprod</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>axis</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>out</strong></p></td></tr></table></div><div class="doc"><p>Compute the cumulative product of the tensor <code>x</code> along <code>axis</code>.</p><p>By default, this op performs an inclusive cumprod, which means that the first
|
|
element of the input is identical to the first element of the output:
|
|
```prettyprint
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|
tf.cumprod([a, b, c]) ==> [a, a * b, a * b * c]
|
|
```</p><p>By setting the <code>exclusive</code> kwarg to <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code>, an exclusive cumprod is
|
|
performed instead:
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|
```prettyprint
|
|
tf.cumprod([a, b, c], exclusive=True) ==> [0, a, a * b]
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```</p><p>By setting the <code><a href="../base-4.8.2.0/GHC-OldList.html#v:reverse">reverse</a></code> kwarg to <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code>, the cumprod is performed in the
|
|
opposite direction:
|
|
```prettyprint
|
|
tf.cumprod([a, b, c], reverse=True) ==> [a * b * c, b * c, c]
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|
```
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This is more efficient than using separate `tf.reverse` ops.</p><p>The <code><a href="../base-4.8.2.0/GHC-OldList.html#v:reverse">reverse</a></code> and <code>exclusive</code> kwargs can also be combined:
|
|
```prettyprint
|
|
tf.cumprod([a, b, c], exclusive=True, reverse=True) ==> [b * c, c, 0]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:cumprod-39-" class="def">cumprod'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>axis</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>out</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:cumsum" class="def">cumsum</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>axis</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>out</strong></p></td></tr></table></div><div class="doc"><p>Compute the cumulative sum of the tensor <code>x</code> along <code>axis</code>.</p><p>By default, this op performs an inclusive cumsum, which means that the first
|
|
element of the input is identical to the first element of the output:
|
|
```prettyprint
|
|
tf.cumsum([a, b, c]) ==> [a, a + b, a + b + c]
|
|
```</p><p>By setting the <code>exclusive</code> kwarg to <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code>, an exclusive cumsum is
|
|
performed instead:
|
|
```prettyprint
|
|
tf.cumsum([a, b, c], exclusive=True) ==> [0, a, a + b]
|
|
```</p><p>By setting the <code><a href="../base-4.8.2.0/GHC-OldList.html#v:reverse">reverse</a></code> kwarg to <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code>, the cumsum is performed in the
|
|
opposite direction:
|
|
```prettyprint
|
|
tf.cumsum([a, b, c], reverse=True) ==> [a + b + c, b + c, c]
|
|
```
|
|
This is more efficient than using separate `tf.reverse` ops.</p><p>The <code><a href="../base-4.8.2.0/GHC-OldList.html#v:reverse">reverse</a></code> and <code>exclusive</code> kwargs can also be combined:
|
|
```prettyprint
|
|
tf.cumsum([a, b, c], exclusive=True, reverse=True) ==> [b + c, c, 0]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:cumsum-39-" class="def">cumsum'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>axis</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>out</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:debugIdentity" class="def">debugIdentity</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Input tensor, non-Reference type.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Output tensor that equals the input tensor.</p></td></tr></table></div><div class="doc"><p>Debug Identity Op.</p><p>Provides an identity mapping of the non-Ref type input tensor for debugging.</p></div></div><div class="top"><p class="src"><a name="v:debugIdentity-39-" class="def">debugIdentity'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Input tensor, non-Reference type.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Output tensor that equals the input tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:debugNanCount" class="def">debugNanCount</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Input tensor, non-Reference type.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>output</strong>: An integer output tensor that is the number of NaNs in the input.</p></td></tr></table></div><div class="doc"><p>Debug NaN Value Counter Op</p><p>Counts number of NaNs in the input tensor, for debugging.</p></div></div><div class="top"><p class="src"><a name="v:debugNanCount-39-" class="def">debugNanCount'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Input tensor, non-Reference type.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>output</strong>: An integer output tensor that is the number of NaNs in the input.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:debugNumericSummary" class="def">debugNumericSummary</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Input tensor, non-Reference type, float or double.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a></td><td class="doc"><p><strong>output</strong>: A double tensor of shape [12], the elements of which are:
|
|
[0]: is initialized (1.0) or not (0.0).
|
|
[1]: total number of elements
|
|
[2]: -inf count
|
|
[3]: negative element count (excluding -inf)
|
|
[4]: zero element count
|
|
[5]: positive element count (excluding +inf)
|
|
[6]: +inf element count
|
|
[7]: NaN element count
|
|
Output elements [1:8] are all zero, if the tensor is uninitialized.
|
|
[8]: minimum of all non-inf and non-NaN elements.
|
|
If uninitialized or no such element exists: +inf.
|
|
[9]: maximum of all non-inf and non-NaN elements.
|
|
If uninitialized or no such element exists: -inf.
|
|
[10]: mean of all non-inf and non-NaN elements.
|
|
If uninitialized or no such element exists: NaN.
|
|
[11]: variance of all non-inf and non-NaN elements.
|
|
If uninitialized or no such element exists: NaN.</p></td></tr></table></div><div class="doc"><p>Debug Numeric Summary Op.</p><p>Provide a basic summary of numeric value types, range and distribution.</p></div></div><div class="top"><p class="src"><a name="v:debugNumericSummary-39-" class="def">debugNumericSummary'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Input tensor, non-Reference type, float or double.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a></td><td class="doc"><p><strong>output</strong>: A double tensor of shape [12], the elements of which are:
|
|
[0]: is initialized (1.0) or not (0.0).
|
|
[1]: total number of elements
|
|
[2]: -inf count
|
|
[3]: negative element count (excluding -inf)
|
|
[4]: zero element count
|
|
[5]: positive element count (excluding +inf)
|
|
[6]: +inf element count
|
|
[7]: NaN element count
|
|
Output elements [1:8] are all zero, if the tensor is uninitialized.
|
|
[8]: minimum of all non-inf and non-NaN elements.
|
|
If uninitialized or no such element exists: +inf.
|
|
[9]: maximum of all non-inf and non-NaN elements.
|
|
If uninitialized or no such element exists: -inf.
|
|
[10]: mean of all non-inf and non-NaN elements.
|
|
If uninitialized or no such element exists: NaN.
|
|
[11]: variance of all non-inf and non-NaN elements.
|
|
If uninitialized or no such element exists: NaN.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:decodeBase64" class="def">decodeBase64</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>input</strong>: Base64 strings to decode.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>output</strong>: Decoded strings.</p></td></tr></table></div><div class="doc"><p>Decode web-safe base64-encoded strings.</p><p>Input may or may not have padding at the end. See EncodeBase64 for padding.
|
|
Web-safe means that input must use - and _ instead of + and /.</p></div></div><div class="top"><p class="src"><a name="v:decodeBase64-39-" class="def">decodeBase64'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>input</strong>: Base64 strings to decode.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>output</strong>: Decoded strings.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:decodeCSV" class="def">decodeCSV</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` oUT_TYPE</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>records</strong>: Each string is a record/row in the csv and all records should have
|
|
the same format.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 oUT_TYPE</td><td class="doc"><p><strong>record_defaults</strong>: One tensor per column of the input record, with either a
|
|
scalar default value for that column or empty if the column is required.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> oUT_TYPE</td><td class="doc"><p><strong>output</strong>: Each tensor will have the same shape as records.</p></td></tr></table></div><div class="doc"><p>Convert CSV records to tensors. Each column maps to one tensor.</p><p>RFC 4180 format is expected for the CSV records.
|
|
(https:/<em>tools.ietf.org</em>html/rfc4180)
|
|
Note that we allow leading and trailing spaces with int or float field.</p></div></div><div class="top"><p class="src"><a name="v:decodeCSV-39-" class="def">decodeCSV'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` oUT_TYPE</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>records</strong>: Each string is a record/row in the csv and all records should have
|
|
the same format.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 oUT_TYPE</td><td class="doc"><p><strong>record_defaults</strong>: One tensor per column of the input record, with either a
|
|
scalar default value for that column or empty if the column is required.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> oUT_TYPE</td><td class="doc"><p><strong>output</strong>: Each tensor will have the same shape as records.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:decodeGif" class="def">decodeGif</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>contents</strong>: 0-D. The GIF-encoded image.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a></td><td class="doc"><p><strong>image</strong>: 4-D with shape `[num_frames, height, width, 3]`. RGB order</p></td></tr></table></div><div class="doc"><p>Decode the first frame of a GIF-encoded image to a uint8 tensor.</p><p>GIF with frame or transparency compression are not supported
|
|
convert animated GIF from compressed to uncompressed by:</p><p>convert $src.gif -coalesce $dst.gif</p></div></div><div class="top"><p class="src"><a name="v:decodeGif-39-" class="def">decodeGif'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>contents</strong>: 0-D. The GIF-encoded image.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a></td><td class="doc"><p><strong>image</strong>: 4-D with shape `[num_frames, height, width, 3]`. RGB order</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:decodeJSONExample" class="def">decodeJSONExample</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>json_examples</strong>: Each string is a JSON object serialized according to the JSON
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mapping of the Example proto.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>binary_examples</strong>: Each string is a binary Example protocol buffer corresponding
|
|
to the respective element of <code>json_examples</code>.</p></td></tr></table></div><div class="doc"><p>Convert JSON-encoded Example records to binary protocol buffer strings.</p><p>This op translates a tensor containing Example records, encoded using
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|
the <a href="https://developers.google.com/protocol-buffers/docs/proto3#json">standard JSON
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|
mapping</a>,
|
|
into a tensor containing the same records encoded as binary protocol
|
|
buffers. The resulting tensor can then be fed to any of the other
|
|
Example-parsing ops.</p></div></div><div class="top"><p class="src"><a name="v:decodeJSONExample-39-" class="def">decodeJSONExample'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>json_examples</strong>: Each string is a JSON object serialized according to the JSON
|
|
mapping of the Example proto.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>binary_examples</strong>: Each string is a binary Example protocol buffer corresponding
|
|
to the respective element of <code>json_examples</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:decodeJpeg" class="def">decodeJpeg</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>contents</strong>: 0-D. The JPEG-encoded image.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a></td><td class="doc"><p><strong>image</strong>: 3-D with shape `[height, width, channels]`..</p></td></tr></table></div><div class="doc"><p>Decode a JPEG-encoded image to a uint8 tensor.</p><p>The attr <code>channels</code> indicates the desired number of color channels for the
|
|
decoded image.</p><p>Accepted values are:</p><ul><li>0: Use the number of channels in the JPEG-encoded image.</li><li>1: output a grayscale image.</li><li>3: output an RGB image.</li></ul><p>If needed, the JPEG-encoded image is transformed to match the requested number
|
|
of color channels.</p><p>The attr <code>ratio</code> allows downscaling the image by an integer factor during
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|
decoding. Allowed values are: 1, 2, 4, and 8. This is much faster than
|
|
downscaling the image later.</p></div></div><div class="top"><p class="src"><a name="v:decodeJpeg-39-" class="def">decodeJpeg'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>contents</strong>: 0-D. The JPEG-encoded image.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a></td><td class="doc"><p><strong>image</strong>: 3-D with shape `[height, width, channels]`..</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:decodePng" class="def">decodePng</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>contents</strong>: 0-D. The PNG-encoded image.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</td><td class="doc"><p><strong>image</strong>: 3-D with shape `[height, width, channels]`.</p></td></tr></table></div><div class="doc"><p>Decode a PNG-encoded image to a uint8 or uint16 tensor.</p><p>The attr <code>channels</code> indicates the desired number of color channels for the
|
|
decoded image.</p><p>Accepted values are:</p><ul><li>0: Use the number of channels in the PNG-encoded image.</li><li>1: output a grayscale image.</li><li>3: output an RGB image.</li><li>4: output an RGBA image.</li></ul><p>If needed, the PNG-encoded image is transformed to match the requested number
|
|
of color channels.</p></div></div><div class="top"><p class="src"><a name="v:decodePng-39-" class="def">decodePng'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>contents</strong>: 0-D. The PNG-encoded image.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</td><td class="doc"><p><strong>image</strong>: 3-D with shape `[height, width, channels]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:decodeRaw" class="def">decodeRaw</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` out_type</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>bytes</strong>: All the elements must have the same length.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</td><td class="doc"><p><strong>output</strong>: A Tensor with one more dimension than the input <code>bytes</code>. The
|
|
added dimension will have size equal to the length of the elements
|
|
of <code>bytes</code> divided by the number of bytes to represent <code>out_type</code>.</p></td></tr></table></div><div class="doc"><p>Reinterpret the bytes of a string as a vector of numbers.</p></div></div><div class="top"><p class="src"><a name="v:decodeRaw-39-" class="def">decodeRaw'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` out_type</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>bytes</strong>: All the elements must have the same length.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</td><td class="doc"><p><strong>output</strong>: A Tensor with one more dimension than the input <code>bytes</code>. The
|
|
added dimension will have size equal to the length of the elements
|
|
of <code>bytes</code> divided by the number of bytes to represent <code>out_type</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:deleteSessionTensor" class="def">deleteSessionTensor</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle for a tensor stored in the session state.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Delete the tensor specified by its handle in the session.</p></div></div><div class="top"><p class="src"><a name="v:deleteSessionTensor-39-" class="def">deleteSessionTensor'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle for a tensor stored in the session state.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:denseToDenseSetOperation" class="def">denseToDenseSetOperation</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>set1</strong>: <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with rank <code>n</code>. 1st `n-1` dimensions must be the same as <code>set2</code>.
|
|
Dimension <code>n</code> contains values in a set, duplicates are allowed but ignored.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>set2</strong>: <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with rank <code>n</code>. 1st `n-1` dimensions must be the same as <code>set1</code>.
|
|
Dimension <code>n</code> contains values in a set, duplicates are allowed but ignored.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>result_indices</strong>, <strong>result_values</strong>, <strong>result_shape</strong>)</p><ul><li><strong>result_indices</strong>: 2D indices of a <code>SparseTensor</code>.</li><li><strong>result_values</strong>: 1D values of a <code>SparseTensor</code>.</li><li><strong>result_shape</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> shape of a <code>SparseTensor</code>. `result_shape[0...n-1]` is
|
|
the same as the 1st `n-1` dimensions of <code>set1</code> and <code>set2</code>, `result_shape[n]`
|
|
is the max result set size across all `0...n-1` dimensions.</li></ul></td></tr></table></div><div class="doc"><p>Applies set operation along last dimension of 2 <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> inputs.</p><p>See SetOperationOp::SetOperationFromContext for values of <code>set_operation</code>.</p><p>Output <code>result</code> is a <code>SparseTensor</code> represented by <code>result_indices</code>,
|
|
<code>result_values</code>, and <code>result_shape</code>. For <code>set1</code> and <code>set2</code> ranked <code>n</code>, this
|
|
has rank <code>n</code> and the same 1st `n-1` dimensions as <code>set1</code> and <code>set2</code>. The <code>nth</code>
|
|
dimension contains the result of <code>set_operation</code> applied to the corresponding
|
|
`[0...n-1]` dimension of <code>set</code>.</p></div></div><div class="top"><p class="src"><a name="v:denseToDenseSetOperation-39-" class="def">denseToDenseSetOperation'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>set1</strong>: <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with rank <code>n</code>. 1st `n-1` dimensions must be the same as <code>set2</code>.
|
|
Dimension <code>n</code> contains values in a set, duplicates are allowed but ignored.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>set2</strong>: <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with rank <code>n</code>. 1st `n-1` dimensions must be the same as <code>set1</code>.
|
|
Dimension <code>n</code> contains values in a set, duplicates are allowed but ignored.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>result_indices</strong>, <strong>result_values</strong>, <strong>result_shape</strong>)</p><ul><li><strong>result_indices</strong>: 2D indices of a <code>SparseTensor</code>.</li><li><strong>result_values</strong>: 1D values of a <code>SparseTensor</code>.</li><li><strong>result_shape</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> shape of a <code>SparseTensor</code>. `result_shape[0...n-1]` is
|
|
the same as the 1st `n-1` dimensions of <code>set1</code> and <code>set2</code>, `result_shape[n]`
|
|
is the max result set size across all `0...n-1` dimensions.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:denseToSparseSetOperation" class="def">denseToSparseSetOperation</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>set1</strong>: <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with rank <code>n</code>. 1st `n-1` dimensions must be the same as <code>set2</code>.
|
|
Dimension <code>n</code> contains values in a set, duplicates are allowed but ignored.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>set2_indices</strong>: 2D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, indices of a <code>SparseTensor</code>. Must be in row-major
|
|
order.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>set2_values</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, values of a <code>SparseTensor</code>. Must be in row-major
|
|
order.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>set2_shape</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, shape of a <code>SparseTensor</code>. `set2_shape[0...n-1]` must
|
|
be the same as the 1st `n-1` dimensions of <code>set1</code>, `result_shape[n]` is the
|
|
max set size across `n-1` dimensions.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>result_indices</strong>, <strong>result_values</strong>, <strong>result_shape</strong>)</p><ul><li><strong>result_indices</strong>: 2D indices of a <code>SparseTensor</code>.</li><li><strong>result_values</strong>: 1D values of a <code>SparseTensor</code>.</li><li><strong>result_shape</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> shape of a <code>SparseTensor</code>. `result_shape[0...n-1]` is
|
|
the same as the 1st `n-1` dimensions of <code>set1</code> and <code>set2</code>, `result_shape[n]`
|
|
is the max result set size across all `0...n-1` dimensions.</li></ul></td></tr></table></div><div class="doc"><p>Applies set operation along last dimension of <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> and <code>SparseTensor</code>.</p><p>See SetOperationOp::SetOperationFromContext for values of <code>set_operation</code>.</p><p>Input <code>set2</code> is a <code>SparseTensor</code> represented by <code>set2_indices</code>, <code>set2_values</code>,
|
|
and <code>set2_shape</code>. For <code>set2</code> ranked <code>n</code>, 1st `n-1` dimensions must be the same
|
|
as <code>set1</code>. Dimension <code>n</code> contains values in a set, duplicates are allowed but
|
|
ignored.</p><p>If <code>validate_indices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code>, this op validates the order and range of <code>set2</code>
|
|
indices.</p><p>Output <code>result</code> is a <code>SparseTensor</code> represented by <code>result_indices</code>,
|
|
<code>result_values</code>, and <code>result_shape</code>. For <code>set1</code> and <code>set2</code> ranked <code>n</code>, this
|
|
has rank <code>n</code> and the same 1st `n-1` dimensions as <code>set1</code> and <code>set2</code>. The <code>nth</code>
|
|
dimension contains the result of <code>set_operation</code> applied to the corresponding
|
|
`[0...n-1]` dimension of <code>set</code>.</p></div></div><div class="top"><p class="src"><a name="v:denseToSparseSetOperation-39-" class="def">denseToSparseSetOperation'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>set1</strong>: <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with rank <code>n</code>. 1st `n-1` dimensions must be the same as <code>set2</code>.
|
|
Dimension <code>n</code> contains values in a set, duplicates are allowed but ignored.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>set2_indices</strong>: 2D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, indices of a <code>SparseTensor</code>. Must be in row-major
|
|
order.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>set2_values</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, values of a <code>SparseTensor</code>. Must be in row-major
|
|
order.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>set2_shape</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, shape of a <code>SparseTensor</code>. `set2_shape[0...n-1]` must
|
|
be the same as the 1st `n-1` dimensions of <code>set1</code>, `result_shape[n]` is the
|
|
max set size across `n-1` dimensions.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>result_indices</strong>, <strong>result_values</strong>, <strong>result_shape</strong>)</p><ul><li><strong>result_indices</strong>: 2D indices of a <code>SparseTensor</code>.</li><li><strong>result_values</strong>: 1D values of a <code>SparseTensor</code>.</li><li><strong>result_shape</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> shape of a <code>SparseTensor</code>. `result_shape[0...n-1]` is
|
|
the same as the 1st `n-1` dimensions of <code>set1</code> and <code>set2</code>, `result_shape[n]`
|
|
is the max result set size across all `0...n-1` dimensions.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:depthToSpace" class="def">depthToSpace</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>block_size</strong>: The size of the spatial block, same as in Space2Depth.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>DepthToSpace for tensors of type T.</p><p>Rearranges data from depth into blocks of spatial data.
|
|
This is the reverse transformation of SpaceToDepth. More specifically,
|
|
this op outputs a copy of the input tensor where values from the <code>depth</code>
|
|
dimension are moved in spatial blocks to the <code>height</code> and <code>width</code> dimensions.
|
|
The attr <code>block_size</code> indicates the input block size and how the data is moved.</p><ul><li>Chunks of data of size `block_size * block_size` from depth are rearranged
|
|
into non-overlapping blocks of size `block_size x block_size`</li><li>The width the output tensor is `input_depth * block_size`, whereas the
|
|
height is `input_height * block_size`.</li><li>The depth of the input tensor must be divisible by
|
|
`block_size * block_size`.</li></ul><p>That is, assuming the input is in the shape:
|
|
`[batch, height, width, depth]`,
|
|
the shape of the output will be:
|
|
`[batch, height*block_size, width*block_size, depth/(block_size*block_size)]`</p><p>This operation requires that the input tensor be of rank 4, and that
|
|
<code>block_size</code> be >=1 and that `block_size * block_size` be a divisor of the
|
|
input depth.</p><p>This operation is useful for resizing the activations between convolutions
|
|
(but keeping all data), e.g. instead of pooling. It is also useful for training
|
|
purely convolutional models.</p><p>For example, given this input of shape `[1, 1, 1, 4]`, and a block size of 2:</p><p>```prettyprint
|
|
x = [[[[1, 2, 3, 4]]]]</p><p>```</p><p>This operation will output a tensor of shape `[1, 2, 2, 1]`:</p><p>```prettyprint
|
|
[[[[1], [2]],
|
|
[[3], [4]]]]
|
|
```</p><p>Here, the input has a batch of 1 and each batch element has shape `[1, 1, 4]`,
|
|
the corresponding output will have 2x2 elements and will have a depth of
|
|
1 channel (1 = `4 / (block_size * block_size)`).
|
|
The output element shape is `[2, 2, 1]`.</p><p>For an input tensor with larger depth, here of shape `[1, 1, 1, 12]`, e.g.</p><p>```prettyprint
|
|
x = [[[[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]]]]
|
|
```</p><p>This operation, for block size of 2, will return the following tensor of shape
|
|
`[1, 2, 2, 3]`</p><p>```prettyprint
|
|
[[[[1, 2, 3], [4, 5, 6]],
|
|
[[7, 8, 9], [10, 11, 12]]]]</p><p>```</p><p>Similarly, for the following input of shape `[1 2 2 4]`, and a block size of 2:</p><p>```prettyprint
|
|
x = [[[[1, 2, 3, 4],
|
|
[5, 6, 7, 8]],
|
|
[[9, 10, 11, 12],
|
|
[13, 14, 15, 16]]]]
|
|
```</p><p>the operator will return the following tensor of shape `[1 4 4 1]`:</p><p>```prettyprint
|
|
x = [[ [1], [2], [5], [6]],
|
|
[ [3], [4], [7], [8]],
|
|
[ [9], [10], [13], [14]],
|
|
[ [11], [12], [15], [16]]]</p><p>```</p></div></div><div class="top"><p class="src"><a name="v:depthToSpace-39-" class="def">depthToSpace'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>block_size</strong>: The size of the spatial block, same as in Space2Depth.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:depthwiseConv2dNative" class="def">depthwiseConv2dNative</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Computes a 2-D depthwise convolution given 4-D <code>input</code> and <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code> tensors.</p><p>Given an input tensor of shape `[batch, in_height, in_width, in_channels]`
|
|
and a filter / kernel tensor of shape
|
|
`[filter_height, filter_width, in_channels, channel_multiplier]`, containing
|
|
<code>in_channels</code> convolutional filters of depth 1, <code>depthwise_conv2d</code> applies
|
|
a different filter to each input channel (expanding from 1 channel to
|
|
<code>channel_multiplier</code> channels for each), then concatenates the results
|
|
together. Thus, the output has `in_channels * channel_multiplier` channels.</p><p>for k in 0..in_channels-1
|
|
for q in 0..channel_multiplier-1
|
|
output[b, i, j, k * channel_multiplier + q] =
|
|
sum_{di, dj} input[b, strides[1] * i + di, strides[2] * j + dj, k] *
|
|
filter[di, dj, k, q]</p><p>Must have `strides[0] = strides[3] = 1`. For the most common case of the same
|
|
horizontal and vertices strides, `strides = [1, stride, stride, 1]`.</p></div></div><div class="top"><p class="src"><a name="v:depthwiseConv2dNative-39-" class="def">depthwiseConv2dNative'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:depthwiseConv2dNativeBackpropFilter" class="def">depthwiseConv2dNativeBackpropFilter</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, in_height, in_width, in_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>filter_sizes</strong>: An integer vector representing the tensor shape of <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code>,
|
|
where <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code> is a 4-D
|
|
`[filter_height, filter_width, in_channels, depthwise_multiplier]` tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: 4-D with shape `[batch, out_height, out_width, out_channels]`.
|
|
Gradients w.r.t. the output of the convolution.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D with shape
|
|
`[filter_height, filter_width, in_channels, out_channels]`. Gradient w.r.t.
|
|
the <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code> input of the convolution.</p></td></tr></table></div><div class="doc"><p>Computes the gradients of depthwise convolution with respect to the filter.</p></div></div><div class="top"><p class="src"><a name="v:depthwiseConv2dNativeBackpropFilter-39-" class="def">depthwiseConv2dNativeBackpropFilter'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, in_height, in_width, in_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>filter_sizes</strong>: An integer vector representing the tensor shape of <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code>,
|
|
where <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code> is a 4-D
|
|
`[filter_height, filter_width, in_channels, depthwise_multiplier]` tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: 4-D with shape `[batch, out_height, out_width, out_channels]`.
|
|
Gradients w.r.t. the output of the convolution.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D with shape
|
|
`[filter_height, filter_width, in_channels, out_channels]`. Gradient w.r.t.
|
|
the <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code> input of the convolution.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:depthwiseConv2dNativeBackpropInput" class="def">depthwiseConv2dNativeBackpropInput</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>input_sizes</strong>: An integer vector representing the shape of <code>input</code>,
|
|
where <code>input</code> is a 4-D `[batch, height, width, channels]` tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong>: 4-D with shape
|
|
`[filter_height, filter_width, in_channels, depthwise_multiplier]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: 4-D with shape `[batch, out_height, out_width, out_channels]`.
|
|
Gradients w.r.t. the output of the convolution.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D with shape `[batch, in_height, in_width, in_channels]`. Gradient
|
|
w.r.t. the input of the convolution.</p></td></tr></table></div><div class="doc"><p>Computes the gradients of depthwise convolution with respect to the input.</p></div></div><div class="top"><p class="src"><a name="v:depthwiseConv2dNativeBackpropInput-39-" class="def">depthwiseConv2dNativeBackpropInput'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>input_sizes</strong>: An integer vector representing the shape of <code>input</code>,
|
|
where <code>input</code> is a 4-D `[batch, height, width, channels]` tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong>: 4-D with shape
|
|
`[filter_height, filter_width, in_channels, depthwise_multiplier]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: 4-D with shape `[batch, out_height, out_width, out_channels]`.
|
|
Gradients w.r.t. the output of the convolution.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D with shape `[batch, in_height, in_width, in_channels]`. Gradient
|
|
w.r.t. the input of the convolution.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:dequantize" class="def">dequantize</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_range</strong>: The minimum scalar value possibly produced for the input.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_range</strong>: The maximum scalar value possibly produced for the input.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Dequantize the <code>input</code> tensor into a float Tensor.</p><dl><dt>min_range, max_range</dt><dd>are scalar floats that specify the range for
|
|
the <code>input</code> data. The <code>mode</code> attribute controls exactly which calculations are
|
|
used to convert the float values to their quantized equivalents.</dd></dl><p>In <code>MIN_COMBINED</code> mode, each value of the tensor will undergo the following:</p><p>```
|
|
if T == qint8, in[i] += (range(T) + 1)/ 2.0
|
|
out[i] = min_range + (in[i]* (max_range - min_range) / range(T))
|
|
```
|
|
here `range(T) = numeric_limits<a href="T">T</a>::max() - numeric_limits<a href="T">T</a>::min()`</p><ul><li>MIN_COMBINED Mode Example*</li></ul><p>If the input comes from a QuantizedRelu6, the output type is
|
|
quint8 (range of 0-255) but the possible range of QuantizedRelu6 is
|
|
0-6. The min_range and max_range values are therefore 0.0 and 6.0.
|
|
Dequantize on quint8 will take each value, cast to float, and multiply
|
|
by 6 / 255.
|
|
Note that if quantizedtype is qint8, the operation will additionally add
|
|
each value by 128 prior to casting.</p><p>If the mode is <code>MIN_FIRST</code>, then this approach is used:</p><p>```
|
|
number_of_steps = 1 << (# of bits in T)
|
|
range_adjust = number_of_steps / (number_of_steps - 1)
|
|
range = (range_max - range_min) * range_adjust
|
|
range_scale = range / number_of_steps
|
|
const double offset_input = static_cast<a href="double">double</a>(input) - lowest_quantized;
|
|
result = range_min + ((input - numeric_limits<a href="T">T</a>::min()) * range_scale)
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:dequantize-39-" class="def">dequantize'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_range</strong>: The minimum scalar value possibly produced for the input.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_range</strong>: The maximum scalar value possibly produced for the input.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:deserializeManySparse" class="def">deserializeManySparse</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>serialized_sparse</strong>: 2-D, The <code>N</code> serialized <code>SparseTensor</code> objects.
|
|
Must have 3 columns.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>sparse_indices</strong>, <strong>sparse_values</strong>, <strong>sparse_shape</strong>)</p><ul><li><strong>sparse_indices</strong></li><li><strong>sparse_values</strong></li><li><strong>sparse_shape</strong></li></ul></td></tr></table></div><div class="doc"><p>Deserialize and concatenate <code>SparseTensors</code> from a serialized minibatch.</p><p>The input <code>serialized_sparse</code> must be a string matrix of shape `[N x 3]` where
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|
<code>N</code> is the minibatch size and the rows correspond to packed outputs of
|
|
<code>SerializeSparse</code>. The ranks of the original <code>SparseTensor</code> objects
|
|
must all match. When the final <code>SparseTensor</code> is created, it has rank one
|
|
higher than the ranks of the incoming <code>SparseTensor</code> objects
|
|
(they have been concatenated along a new row dimension).</p><p>The output <code>SparseTensor</code> object's shape values for all dimensions but the
|
|
first are the max across the input <code>SparseTensor</code> objects' shape values
|
|
for the corresponding dimensions. Its first shape value is <code>N</code>, the minibatch
|
|
size.</p><p>The input <code>SparseTensor</code> objects' indices are assumed ordered in
|
|
standard lexicographic order. If this is not the case, after this
|
|
step run <code>SparseReorder</code> to restore index ordering.</p><p>For example, if the serialized input is a `[2 x 3]` matrix representing two
|
|
original <code>SparseTensor</code> objects:</p><p>index = [ 0]
|
|
[10]
|
|
[20]
|
|
values = [1, 2, 3]
|
|
shape = [50]</p><p>and</p><p>index = [ 2]
|
|
[10]
|
|
values = [4, 5]
|
|
shape = [30]</p><p>then the final deserialized <code>SparseTensor</code> will be:</p><p>index = [0 0]
|
|
[0 10]
|
|
[0 20]
|
|
[1 2]
|
|
[1 10]
|
|
values = [1, 2, 3, 4, 5]
|
|
shape = [2 50]</p></div></div><div class="top"><p class="src"><a name="v:deserializeManySparse-39-" class="def">deserializeManySparse'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>serialized_sparse</strong>: 2-D, The <code>N</code> serialized <code>SparseTensor</code> objects.
|
|
Must have 3 columns.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>sparse_indices</strong>, <strong>sparse_values</strong>, <strong>sparse_shape</strong>)</p><ul><li><strong>sparse_indices</strong></li><li><strong>sparse_values</strong></li><li><strong>sparse_shape</strong></li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:destroyTemporaryVariable" class="def">destroyTemporaryVariable</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: A reference to the temporary variable tensor.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</td><td class="doc"><p><strong>value</strong></p></td></tr></table></div><div class="doc"><p>Destroys the temporary variable and returns its final value.</p><p>Sets output to the value of the Tensor pointed to by <code>ref</code>, then destroys
|
|
the temporary variable called <code>var_name</code>.
|
|
All other uses of <code>ref</code> *must* have executed before this op.
|
|
This is typically achieved by chaining the ref through each assign op, or by
|
|
using control dependencies.</p><p>Outputs the final value of the tensor pointed to by <code>ref</code>.</p></div></div><div class="top"><p class="src"><a name="v:destroyTemporaryVariable-39-" class="def">destroyTemporaryVariable'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: A reference to the temporary variable tensor.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</td><td class="doc"><p><strong>value</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:diag" class="def">diag</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>diagonal</strong>: Rank k tensor where k is at most 3.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Returns a diagonal tensor with a given diagonal values.</p><p>Given a <code>diagonal</code>, this operation returns a tensor with the <code>diagonal</code> and
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everything else padded with zeros. The diagonal is computed as follows:</p><p>Assume <code>diagonal</code> has dimensions [D1,..., Dk], then the output is a tensor of
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|
rank 2k with dimensions [D1,..., Dk, D1,..., Dk] where:</p><p>`output[i1,..., ik, i1,..., ik] = diagonal[i1, ..., ik]` and 0 everywhere else.</p><p>For example:</p><p>```prettyprint
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|
# <code>diagonal</code> is [1, 2, 3, 4]
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|
tf.diag(diagonal) ==> [[1, 0, 0, 0]
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[0, 2, 0, 0]
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[0, 0, 3, 0]
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[0, 0, 0, 4]]
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```</p></div></div><div class="top"><p class="src"><a name="v:diag-39-" class="def">diag'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>diagonal</strong>: Rank k tensor where k is at most 3.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:diagPart" class="def">diagPart</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Rank k tensor where k is 2, 4, or 6.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>diagonal</strong>: The extracted diagonal.</p></td></tr></table></div><div class="doc"><p>Returns the diagonal part of the tensor.</p><p>This operation returns a tensor with the <code>diagonal</code> part
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|
of the <code>input</code>. The <code>diagonal</code> part is computed as follows:</p><p>Assume <code>input</code> has dimensions `[D1,..., Dk, D1,..., Dk]`, then the output is a
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|
tensor of rank <code>k</code> with dimensions `[D1,..., Dk]` where:</p><p>`diagonal[i1,..., ik] = input[i1, ..., ik, i1,..., ik]`.</p><p>For example:</p><p>```prettyprint
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|
# <code>input</code> is [[1, 0, 0, 0]
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|
[0, 2, 0, 0]
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|
[0, 0, 3, 0]
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|
[0, 0, 0, 4]]</p><p>tf.diag_part(input) ==> [1, 2, 3, 4]
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|
```</p></div></div><div class="top"><p class="src"><a name="v:diagPart-39-" class="def">diagPart'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Rank k tensor where k is 2, 4, or 6.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>diagonal</strong>: The extracted diagonal.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:digamma" class="def">digamma</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes Psi, the derivative of Lgamma (the log of the absolute value of</p><p>`Gamma(x)`), element-wise.</p></div></div><div class="top"><p class="src"><a name="v:digamma-39-" class="def">digamma'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:dilation2D" class="def">dilation2D</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, in_height, in_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong>: 3-D with shape `[filter_height, filter_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D with shape `[batch, out_height, out_width, depth]`.</p></td></tr></table></div><div class="doc"><p>Computes the grayscale dilation of 4-D <code>input</code> and 3-D <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code> tensors.</p><p>The <code>input</code> tensor has shape `[batch, in_height, in_width, depth]` and the
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|
<code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code> tensor has shape `[filter_height, filter_width, depth]`, i.e., each
|
|
input channel is processed independently of the others with its own structuring
|
|
function. The <code>output</code> tensor has shape
|
|
`[batch, out_height, out_width, depth]`. The spatial dimensions of the output
|
|
tensor depend on the <code>padding</code> algorithm. We currently only support the default
|
|
<a href="NHWC.html">NHWC</a> <code>data_format</code>.</p><p>In detail, the grayscale morphological 2-D dilation is the max-sum correlation
|
|
(for consistency with <code>conv2d</code>, we use unmirrored filters):</p><p>output[b, y, x, c] =
|
|
max_{dy, dx} input[b,
|
|
strides[1] * y + rates[1] * dy,
|
|
strides[2] * x + rates[2] * dx,
|
|
c] +
|
|
filter[dy, dx, c]</p><p>Max-pooling is a special case when the filter has size equal to the pooling
|
|
kernel size and contains all zeros.</p><p>Note on duality: The dilation of <code>input</code> by the <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code> is equal to the
|
|
negation of the erosion of `-input` by the reflected <code><a href="../base-4.8.2.0/GHC-OldList.html#v:filter">filter</a></code>.</p></div></div><div class="top"><p class="src"><a name="v:dilation2D-39-" class="def">dilation2D'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, in_height, in_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong>: 3-D with shape `[filter_height, filter_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D with shape `[batch, out_height, out_width, depth]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:dilation2DBackpropFilter" class="def">dilation2DBackpropFilter</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, in_height, in_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong>: 3-D with shape `[filter_height, filter_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: 4-D with shape `[batch, out_height, out_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>filter_backprop</strong>: 3-D with shape `[filter_height, filter_width, depth]`.</p></td></tr></table></div><div class="doc"><p>Computes the gradient of morphological 2-D dilation with respect to the filter.</p></div></div><div class="top"><p class="src"><a name="v:dilation2DBackpropFilter-39-" class="def">dilation2DBackpropFilter'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, in_height, in_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong>: 3-D with shape `[filter_height, filter_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: 4-D with shape `[batch, out_height, out_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>filter_backprop</strong>: 3-D with shape `[filter_height, filter_width, depth]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:dilation2DBackpropInput" class="def">dilation2DBackpropInput</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, in_height, in_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong>: 3-D with shape `[filter_height, filter_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: 4-D with shape `[batch, out_height, out_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>in_backprop</strong>: 4-D with shape `[batch, in_height, in_width, depth]`.</p></td></tr></table></div><div class="doc"><p>Computes the gradient of morphological 2-D dilation with respect to the input.</p></div></div><div class="top"><p class="src"><a name="v:dilation2DBackpropInput-39-" class="def">dilation2DBackpropInput'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, in_height, in_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>filter</strong>: 3-D with shape `[filter_height, filter_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: 4-D with shape `[batch, out_height, out_width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>in_backprop</strong>: 4-D with shape `[batch, in_height, in_width, depth]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:div" class="def">div</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns x / y element-wise.</p><ul><li>NOTE*: <code>Div</code> supports broadcasting. More about broadcasting
|
|
<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:div-39-" class="def">div'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:drawBoundingBoxes" class="def">drawBoundingBoxes</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>images</strong>: 4-D with shape `[batch, height, width, depth]`. A batch of images.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>boxes</strong>: 3-D with shape `[batch, num_bounding_boxes, 4]` containing bounding
|
|
boxes.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D with the same shape as <code>images</code>. The batch of input images with
|
|
bounding boxes drawn on the images.</p></td></tr></table></div><div class="doc"><p>Draw bounding boxes on a batch of images.</p><p>Outputs a copy of <code>images</code> but draws on top of the pixels zero or more bounding
|
|
boxes specified by the locations in <code>boxes</code>. The coordinates of the each
|
|
bounding box in <code>boxes</code> are encoded as `[y_min, x_min, y_max, x_max]`. The
|
|
bounding box coordinates are floats in `[0.0, 1.0]` relative to the width and
|
|
height of the underlying image.</p><p>For example, if an image is 100 x 200 pixels and the bounding box is
|
|
`[0.1, 0.2, 0.5, 0.9]`, the bottom-left and upper-right coordinates of the
|
|
bounding box will be `(10, 40)` to `(50, 180)`.</p><p>Parts of the bounding box may fall outside the image.</p></div></div><div class="top"><p class="src"><a name="v:drawBoundingBoxes-39-" class="def">drawBoundingBoxes'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>images</strong>: 4-D with shape `[batch, height, width, depth]`. A batch of images.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>boxes</strong>: 3-D with shape `[batch, num_bounding_boxes, 4]` containing bounding
|
|
boxes.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D with the same shape as <code>images</code>. The batch of input images with
|
|
bounding boxes drawn on the images.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:dynamicPartition" class="def">dynamicPartition</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_partitions</strong>: The number of partitions to output.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>partitions</strong>: Any shape. Indices in the range `[0, num_partitions)`.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</td><td class="doc"><p><strong>outputs</strong></p></td></tr></table></div><div class="doc"><p>Partitions `data` into <code>num_partitions</code> tensors using indices from <code>partitions</code>.</p><p>For each index tuple <code>js</code> of size `partitions.ndim`, the slice `data[js, ...]`
|
|
becomes part of `outputs[partitions[js]]`. The slices with `partitions[js] = i`
|
|
are placed in `outputs[i]` in lexicographic order of <code>js</code>, and the first
|
|
dimension of `outputs[i]` is the number of entries in <code>partitions</code> equal to <code>i</code>.
|
|
In detail,</p><p>```python
|
|
outputs[i].shape = [sum(partitions == i)] + data.shape[partitions.ndim:]</p><p>outputs[i] = pack([data[js, ...] for js if partitions[js] == i])
|
|
```</p><p>`data.shape` must start with `partitions.shape`.</p><p>For example:</p><p>```python
|
|
# Scalar partitions.
|
|
partitions = 1
|
|
num_partitions = 2
|
|
data = [10, 20]
|
|
outputs[0] = [] # Empty with shape [0, 2]
|
|
outputs[1] = [[10, 20]]</p><p># Vector partitions.
|
|
partitions = [0, 0, 1, 1, 0]
|
|
num_partitions = 2
|
|
data = [10, 20, 30, 40, 50]
|
|
outputs[0] = [10, 20, 50]
|
|
outputs[1] = [30, 40]
|
|
```</p><p><a href="div">style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;"</a>
|
|
<a href="img">style="width:100%" src="../../images/DynamicPartition.png" alt</a>
|
|
<a href="/div">/div</a></p></div></div><div class="top"><p class="src"><a name="v:dynamicPartition-39-" class="def">dynamicPartition'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_partitions</strong>: The number of partitions to output.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>partitions</strong>: Any shape. Indices in the range `[0, num_partitions)`.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</td><td class="doc"><p><strong>outputs</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:dynamicStitch" class="def">dynamicStitch</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>]</td><td class="doc"><p><strong>indices</strong></p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t]</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>merged</strong></p></td></tr></table></div><div class="doc"><p>Interleave the values from the `data` tensors into a single tensor.</p><p>Builds a merged tensor such that</p><p>```python
|
|
merged[indices[m][i, ..., j], ...] = data[m][i, ..., j, ...]
|
|
```</p><p>For example, if each `indices[m]` is scalar or vector, we have</p><p>```python
|
|
# Scalar indices:
|
|
merged[indices[m], ...] = data[m][...]</p><p># Vector indices:
|
|
merged[indices[m][i], ...] = data[m][i, ...]
|
|
```</p><p>Each `data[i].shape` must start with the corresponding `indices[i].shape`,
|
|
and the rest of `data[i].shape` must be constant w.r.t. <code>i</code>. That is, we
|
|
must have `data[i].shape = indices[i].shape + constant`. In terms of this
|
|
<code>constant</code>, the output shape is</p><p>merged.shape = [max(indices)] + constant</p><p>Values are merged in order, so if an index appears in both `indices[m][i]` and
|
|
`indices[n][j]` for `(m,i) < (n,j)` the slice `data[n][j]` will appear in the
|
|
merged result.</p><p>For example:</p><p>```python
|
|
indices[0] = 6
|
|
indices[1] = [4, 1]
|
|
indices[2] = [[5, 2], [0, 3]]
|
|
data[0] = [61, 62]
|
|
data[1] = [[41, 42], [11, 12]]
|
|
data[2] = [[[51, 52], [21, 22]], [[1, 2], [31, 32]]]
|
|
merged = [[1, 2], [11, 12], [21, 22], [31, 32], [41, 42],
|
|
[51, 52], [61, 62]]
|
|
```</p><p><a href="div">style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;"</a>
|
|
<a href="img">style="width:100%" src="../../images/DynamicStitch.png" alt</a>
|
|
<a href="/div">/div</a></p></div></div><div class="top"><p class="src"><a name="v:dynamicStitch-39-" class="def">dynamicStitch'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>]</td><td class="doc"><p><strong>indices</strong></p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t]</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>merged</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:editDistance" class="def">editDistance</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>hypothesis_indices</strong>: The indices of the hypothesis list SparseTensor.
|
|
This is an N x R int64 matrix.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>hypothesis_values</strong>: The values of the hypothesis list SparseTensor.
|
|
This is an N-length vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>hypothesis_shape</strong>: The shape of the hypothesis list SparseTensor.
|
|
This is an R-length vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>truth_indices</strong>: The indices of the truth list SparseTensor.
|
|
This is an M x R int64 matrix.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>truth_values</strong>: The values of the truth list SparseTensor.
|
|
This is an M-length vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>truth_shape</strong>: truth indices, vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>output</strong>: A dense float tensor with rank R - 1.</p><p>For the example input:</p><p>// hypothesis represents a 2x1 matrix with variable-length values:
|
|
// (0,0) = ["a"]
|
|
// (1,0) = ["b"]
|
|
hypothesis_indices = [[0, 0, 0],
|
|
[1, 0, 0]]
|
|
hypothesis_values = ["a", "b"]
|
|
hypothesis_shape = [2, 1, 1]</p><p>// truth represents a 2x2 matrix with variable-length values:
|
|
// (0,0) = []
|
|
// (0,1) = ["a"]
|
|
// (1,0) = ["b", "c"]
|
|
// (1,1) = ["a"]
|
|
truth_indices = [[0, 1, 0],
|
|
[1, 0, 0],
|
|
[1, 0, 1],
|
|
[1, 1, 0]]
|
|
truth_values = ["a", "b", "c", "a"]
|
|
truth_shape = [2, 2, 2]
|
|
normalize = true</p><p>The output will be:</p><p>// output is a 2x2 matrix with edit distances normalized by truth lengths.
|
|
output = [[inf, 1.0], // (0,0): no truth, (0,1): no hypothesis
|
|
[0.5, 1.0]] // (1,0): addition, (1,1): no hypothesis</p></td></tr></table></div><div class="doc"><p>Computes the (possibly normalized) Levenshtein Edit Distance.</p><p>The inputs are variable-length sequences provided by SparseTensors
|
|
(hypothesis_indices, hypothesis_values, hypothesis_shape)
|
|
and
|
|
(truth_indices, truth_values, truth_shape).</p><p>The inputs are:</p></div></div><div class="top"><p class="src"><a name="v:editDistance-39-" class="def">editDistance'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>hypothesis_indices</strong>: The indices of the hypothesis list SparseTensor.
|
|
This is an N x R int64 matrix.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>hypothesis_values</strong>: The values of the hypothesis list SparseTensor.
|
|
This is an N-length vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>hypothesis_shape</strong>: The shape of the hypothesis list SparseTensor.
|
|
This is an R-length vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>truth_indices</strong>: The indices of the truth list SparseTensor.
|
|
This is an M x R int64 matrix.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>truth_values</strong>: The values of the truth list SparseTensor.
|
|
This is an M-length vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>truth_shape</strong>: truth indices, vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>output</strong>: A dense float tensor with rank R - 1.</p><p>For the example input:</p><p>// hypothesis represents a 2x1 matrix with variable-length values:
|
|
// (0,0) = ["a"]
|
|
// (1,0) = ["b"]
|
|
hypothesis_indices = [[0, 0, 0],
|
|
[1, 0, 0]]
|
|
hypothesis_values = ["a", "b"]
|
|
hypothesis_shape = [2, 1, 1]</p><p>// truth represents a 2x2 matrix with variable-length values:
|
|
// (0,0) = []
|
|
// (0,1) = ["a"]
|
|
// (1,0) = ["b", "c"]
|
|
// (1,1) = ["a"]
|
|
truth_indices = [[0, 1, 0],
|
|
[1, 0, 0],
|
|
[1, 0, 1],
|
|
[1, 1, 0]]
|
|
truth_values = ["a", "b", "c", "a"]
|
|
truth_shape = [2, 2, 2]
|
|
normalize = true</p><p>The output will be:</p><p>// output is a 2x2 matrix with edit distances normalized by truth lengths.
|
|
output = [[inf, 1.0], // (0,0): no truth, (0,1): no hypothesis
|
|
[0.5, 1.0]] // (1,0): addition, (1,1): no hypothesis</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:elu" class="def">elu</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>features</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>activations</strong></p></td></tr></table></div><div class="doc"><p>Computes exponential linear: `exp(features) - 1` if < 0, <code>features</code> otherwise.</p><p>See <a href="http://arxiv.org/abs/1511.07289">Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)</a></p></div></div><div class="top"><p class="src"><a name="v:elu-39-" class="def">elu'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>features</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>activations</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:eluGrad" class="def">eluGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>gradients</strong>: The backpropagated gradients to the corresponding Elu operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>outputs</strong>: The outputs of the corresponding Elu operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>backprops</strong>: The gradients: `gradients * (outputs + 1)` if outputs < 0,
|
|
<code>gradients</code> otherwise.</p></td></tr></table></div><div class="doc"><p>Computes gradients for the exponential linear (Elu) operation.</p></div></div><div class="top"><p class="src"><a name="v:eluGrad-39-" class="def">eluGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>gradients</strong>: The backpropagated gradients to the corresponding Elu operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>outputs</strong>: The outputs of the corresponding Elu operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>backprops</strong>: The gradients: `gradients * (outputs + 1)` if outputs < 0,
|
|
<code>gradients</code> otherwise.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:encodeBase64" class="def">encodeBase64</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>input</strong>: Strings to be encoded.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>output</strong>: Input strings encoded in base64.</p></td></tr></table></div><div class="doc"><p>Encode strings into web-safe base64 format.</p><p>Refer to the following article for more information on base64 format:
|
|
en.wikipedia.org<em>wiki</em>Base64. Base64 strings may have padding with '=' at the
|
|
end so that the encoded has length multiple of 4. See Padding section of the
|
|
link above.</p><p>Web-safe means that the encoder uses - and _ instead of + and /.</p></div></div><div class="top"><p class="src"><a name="v:encodeBase64-39-" class="def">encodeBase64'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>input</strong>: Strings to be encoded.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>output</strong>: Input strings encoded in base64.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:encodeJpeg" class="def">encodeJpeg</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a></td><td class="doc"><p><strong>image</strong>: 3-D with shape `[height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>contents</strong>: 0-D. JPEG-encoded image.</p></td></tr></table></div><div class="doc"><p>JPEG-encode an image.</p><p><code>image</code> is a 3-D uint8 Tensor of shape `[height, width, channels]`.</p><p>The attr <code>format</code> can be used to override the color format of the encoded
|
|
output. Values can be:</p><ul><li>`''`: Use a default format based on the number of channels in the image.</li><li><code>grayscale</code>: Output a grayscale JPEG image. The <code>channels</code> dimension
|
|
of <code>image</code> must be 1.</li><li><code>rgb</code>: Output an RGB JPEG image. The <code>channels</code> dimension
|
|
of <code>image</code> must be 3.</li></ul><p>If <code>format</code> is not specified or is the empty string, a default format is picked
|
|
in function of the number of channels in <code>image</code>:</p><ul><li>1: Output a grayscale image.</li><li>3: Output an RGB image.</li></ul></div></div><div class="top"><p class="src"><a name="v:encodeJpeg-39-" class="def">encodeJpeg'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a></td><td class="doc"><p><strong>image</strong>: 3-D with shape `[height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>contents</strong>: 0-D. JPEG-encoded image.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:encodePng" class="def">encodePng</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>image</strong>: 3-D with shape `[height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>contents</strong>: 0-D. PNG-encoded image.</p></td></tr></table></div><div class="doc"><p>PNG-encode an image.</p><p><code>image</code> is a 3-D uint8 or uint16 Tensor of shape `[height, width, channels]`
|
|
where <code>channels</code> is:</p><ul><li>1: for grayscale.</li><li>2: for grayscale + alpha.</li><li>3: for RGB.</li><li>4: for RGBA.</li></ul><p>The ZLIB compression level, <code>compression</code>, can be -1 for the PNG-encoder
|
|
default or a value from 0 to 9. 9 is the highest compression level, generating
|
|
the smallest output, but is slower.</p></div></div><div class="top"><p class="src"><a name="v:encodePng-39-" class="def">encodePng'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>image</strong>: 3-D with shape `[height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>contents</strong>: 0-D. PNG-encoded image.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:enter" class="def">enter</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong>: The tensor to be made available to the child frame.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The same tensor as `data`.</p></td></tr></table></div><div class="doc"><p>Creates or finds a child frame, and makes `data` available to the child frame.</p><p>This op is used together with <code>Exit</code> to create loops in the graph.
|
|
The unique <code>frame_name</code> is used by the <code>Executor</code> to identify frames. If
|
|
<code>is_constant</code> is true, <code>output</code> is a constant in the child frame; otherwise
|
|
it may be changed in the child frame. At most <code>parallel_iterations</code> iterations
|
|
are run in parallel in the child frame.</p></div></div><div class="top"><p class="src"><a name="v:enter-39-" class="def">enter'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong>: The tensor to be made available to the child frame.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The same tensor as `data`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:equal" class="def">equal</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns the truth value of (x == y) element-wise.</p><ul><li>NOTE*: <code>Equal</code> supports broadcasting. More about broadcasting
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<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:equal-39-" class="def">equal'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:erf" class="def">erf</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes the Gauss error function of <code>x</code> element-wise.</p></div></div><div class="top"><p class="src"><a name="v:erf-39-" class="def">erf'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:erfc" class="def">erfc</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes the complementary error function of <code>x</code> element-wise.</p></div></div><div class="top"><p class="src"><a name="v:erfc-39-" class="def">erfc'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:exit" class="def">exit</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong>: The tensor to be made available to the parent frame.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The same tensor as `data`.</p></td></tr></table></div><div class="doc"><p>Exits the current frame to its parent frame.</p><p>Exit makes its input `data` available to the parent frame.</p></div></div><div class="top"><p class="src"><a name="v:exit-39-" class="def">exit'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong>: The tensor to be made available to the parent frame.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The same tensor as `data`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:exp" class="def">exp</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes exponential of x element-wise. \(y = e^x\).</p></div></div><div class="top"><p class="src"><a name="v:exp-39-" class="def">exp'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:expandDims" class="def">expandDims</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tdim)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tdim</td><td class="doc"><p><strong>dim</strong>: 0-D (scalar). Specifies the dimension index at which to
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expand the shape of <code>input</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Contains the same data as <code>input</code>, but its shape has an additional
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dimension of size 1 added.</p></td></tr></table></div><div class="doc"><p>Inserts a dimension of 1 into a tensor's shape.</p><p>Given a tensor <code>input</code>, this operation inserts a dimension of 1 at the
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dimension index <code>dim</code> of <code>input</code>'s shape. The dimension index <code>dim</code> starts at
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zero; if you specify a negative number for <code>dim</code> it is counted backward from
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the end.</p><p>This operation is useful if you want to add a batch dimension to a single
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element. For example, if you have a single image of shape `[height, width,
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channels]`, you can make it a batch of 1 image with `expand_dims(image, 0)`,
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which will make the shape `[1, height, width, channels]`.</p><p>Other examples:</p><p>```prettyprint
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|
# <code>t</code> is a tensor of shape [2]
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shape(expand_dims(t, 0)) ==> [1, 2]
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|
shape(expand_dims(t, 1)) ==> [2, 1]
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shape(expand_dims(t, -1)) ==> [2, 1]</p><p># <code>t2</code> is a tensor of shape [2, 3, 5]
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|
shape(expand_dims(t2, 0)) ==> [1, 2, 3, 5]
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shape(expand_dims(t2, 2)) ==> [2, 3, 1, 5]
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shape(expand_dims(t2, 3)) ==> [2, 3, 5, 1]
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```</p><p>This operation requires that:</p><p>`-1-input.dims() <= dim <= input.dims()`</p><p>This operation is related to `squeeze()`, which removes dimensions of
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size 1.</p></div></div><div class="top"><p class="src"><a name="v:expandDims-39-" class="def">expandDims'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tdim)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tdim</td><td class="doc"><p><strong>dim</strong>: 0-D (scalar). Specifies the dimension index at which to
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expand the shape of <code>input</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Contains the same data as <code>input</code>, but its shape has an additional
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dimension of size 1 added.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:expm1" class="def">expm1</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes exponential of x - 1 element-wise.</p><p>I.e., \(y = (exp x) - 1\).</p></div></div><div class="top"><p class="src"><a name="v:expm1-39-" class="def">expm1'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:extractGlimpse" class="def">extractGlimpse</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input</strong>: A 4-D float tensor of shape `[batch_size, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong>: A 1-D tensor of 2 elements containing the size of the glimpses
|
|
to extract. The glimpse height must be specified first, following
|
|
by the glimpse width.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>offsets</strong>: A 2-D integer tensor of shape `[batch_size, 2]` containing
|
|
the x, y locations of the center of each window.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>glimpse</strong>: A tensor representing the glimpses `[batch_size,
|
|
glimpse_height, glimpse_width, channels]`.</p></td></tr></table></div><div class="doc"><p>Extracts a glimpse from the input tensor.</p><p>Returns a set of windows called glimpses extracted at location
|
|
<code>offsets</code> from the input tensor. If the windows only partially
|
|
overlaps the inputs, the non overlapping areas will be filled with
|
|
random noise.</p><p>The result is a 4-D tensor of shape `[batch_size, glimpse_height,
|
|
glimpse_width, channels]`. The channels and batch dimensions are the
|
|
same as that of the input tensor. The height and width of the output
|
|
windows are specified in the <code><a href="TensorFlow-GenOps-Core.html#v:size">size</a></code> parameter.</p><p>The argument <code>normalized</code> and <code>centered</code> controls how the windows are built:</p><ul><li>If the coordinates are normalized but not centered, 0.0 and 1.0
|
|
correspond to the minimum and maximum of each height and width
|
|
dimension.</li><li>If the coordinates are both normalized and centered, they range from</li><li>1.0 to 1.0. The coordinates (-1.0, -1.0) correspond to the upper
|
|
left corner, the lower right corner is located at (1.0, 1.0) and the
|
|
center is at (0, 0).</li><li>If the coordinates are not normalized they are interpreted as
|
|
numbers of pixels.</li></ul></div></div><div class="top"><p class="src"><a name="v:extractGlimpse-39-" class="def">extractGlimpse'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input</strong>: A 4-D float tensor of shape `[batch_size, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong>: A 1-D tensor of 2 elements containing the size of the glimpses
|
|
to extract. The glimpse height must be specified first, following
|
|
by the glimpse width.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>offsets</strong>: A 2-D integer tensor of shape `[batch_size, 2]` containing
|
|
the x, y locations of the center of each window.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>glimpse</strong>: A tensor representing the glimpses `[batch_size,
|
|
glimpse_height, glimpse_width, channels]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:extractImagePatches" class="def">extractImagePatches</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>images</strong>: 4-D Tensor with shape `[batch, in_rows, in_cols, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>patches</strong>: 4-D Tensor with shape `[batch, out_rows, out_cols, ksize_rows *
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|
ksize_cols * depth]` containing image patches with size
|
|
`ksize_rows x ksize_cols x depth` vectorized in the "depth" dimension.</p></td></tr></table></div><div class="doc"><p>Extract <code>patches</code> from <code>images</code> and put them in the "depth" output dimension.</p></div></div><div class="top"><p class="src"><a name="v:extractImagePatches-39-" class="def">extractImagePatches'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>images</strong>: 4-D Tensor with shape `[batch, in_rows, in_cols, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>patches</strong>: 4-D Tensor with shape `[batch, out_rows, out_cols, ksize_rows *
|
|
ksize_cols * depth]` containing image patches with size
|
|
`ksize_rows x ksize_cols x depth` vectorized in the "depth" dimension.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fFT" class="def">fFT</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong>: A complex64 tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong>: A complex64 tensor of the same shape as <code>input</code>. The inner-most
|
|
dimension of <code>input</code> is replaced with its 1D Fourier Transform.</p></td></tr></table></div><div class="doc"><p>Compute the 1-dimensional discrete Fourier Transform over the inner-most</p><p>dimension of <code>input</code>.</p></div></div><div class="top"><p class="src"><a name="v:fFT-39-" class="def">fFT'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong>: A complex64 tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong>: A complex64 tensor of the same shape as <code>input</code>. The inner-most
|
|
dimension of <code>input</code> is replaced with its 1D Fourier Transform.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fFT2D" class="def">fFT2D</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong>: A complex64 tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong>: A complex64 tensor of the same shape as <code>input</code>. The inner-most 2
|
|
dimensions of <code>input</code> are replaced with their 2D Fourier Transform.</p><p><code>compatibility(numpy)
|
|
Equivalent to np.fft2
|
|
</code>end_compatibility</p></td></tr></table></div><div class="doc"><p>Compute the 2-dimensional discrete Fourier Transform over the inner-most</p><p>2 dimensions of <code>input</code>.</p></div></div><div class="top"><p class="src"><a name="v:fFT2D-39-" class="def">fFT2D'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong>: A complex64 tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong>: A complex64 tensor of the same shape as <code>input</code>. The inner-most 2
|
|
dimensions of <code>input</code> are replaced with their 2D Fourier Transform.</p><p><code>compatibility(numpy)
|
|
Equivalent to np.fft2
|
|
</code>end_compatibility</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fFT3D" class="def">fFT3D</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong>: A complex64 tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong>: A complex64 tensor of the same shape as <code>input</code>. The inner-most 3
|
|
dimensions of <code>input</code> are replaced with their 3D Fourier Transform.</p><p><code>compatibility(numpy)
|
|
Equivalent to np.fft3
|
|
</code>end_compatibility</p></td></tr></table></div><div class="doc"><p>Compute the 3-dimensional discrete Fourier Transform over the inner-most 3</p><p>dimensions of <code>input</code>.</p></div></div><div class="top"><p class="src"><a name="v:fFT3D-39-" class="def">fFT3D'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong>: A complex64 tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong>: A complex64 tensor of the same shape as <code>input</code>. The inner-most 3
|
|
dimensions of <code>input</code> are replaced with their 3D Fourier Transform.</p><p><code>compatibility(numpy)
|
|
Equivalent to np.fft3
|
|
</code>end_compatibility</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fIFOQueue" class="def">fIFOQueue</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>]</td><td class="doc"><p><strong>component_types</strong>: The type of each component in a value.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong>: The handle to the queue.</p></td></tr></table></div><div class="doc"><p>A queue that produces elements in first-in first-out order.</p></div></div><div class="top"><p class="src"><a name="v:fIFOQueue-39-" class="def">fIFOQueue'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>]</td><td class="doc"><p><strong>component_types</strong>: The type of each component in a value.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong>: The handle to the queue.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fIFOQueueV2" class="def">fIFOQueueV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>]</td><td class="doc"><p><strong>component_types</strong>: The type of each component in a value.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to the queue.</p></td></tr></table></div><div class="doc"><p>A queue that produces elements in first-in first-out order.</p></div></div><div class="top"><p class="src"><a name="v:fIFOQueueV2-39-" class="def">fIFOQueueV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>]</td><td class="doc"><p><strong>component_types</strong>: The type of each component in a value.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to the queue.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fact" class="def">fact</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>fact</strong></p></td></tr></table></div><div class="doc"><p>Output a fact about factorials.</p></div></div><div class="top"><p class="src"><a name="v:fact-39-" class="def">fact'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>fact</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fakeQuantWithMinMaxArgs" class="def">fakeQuantWithMinMaxArgs</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>inputs</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>outputs</strong></p></td></tr></table></div><div class="doc"><p>Fake-quantize the <code>inputs</code> tensor, type float to <code>outputs</code> tensor of same type.</p><p>Attributes [min; max] define the clamping range for the <code>inputs</code> data. Op
|
|
divides this range into 255 steps (total of 256 values), then replaces each
|
|
<code>inputs</code> value with the closest of the quantized step values.</p><p>Quantization is called fake since the output is still in floating point.</p></div></div><div class="top"><p class="src"><a name="v:fakeQuantWithMinMaxArgs-39-" class="def">fakeQuantWithMinMaxArgs'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>inputs</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>outputs</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fakeQuantWithMinMaxArgsGradient" class="def">fakeQuantWithMinMaxArgsGradient</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>gradients</strong>: Backpropagated gradients above the FakeQuantWithMinMaxArgs operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>inputs</strong>: Values passed as inputs to the FakeQuantWithMinMaxArgs operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>backprops</strong>: Backpropagated gradients below the FakeQuantWithMinMaxArgs operation:
|
|
`gradients * (inputs >= min && inputs <= max)`.</p></td></tr></table></div><div class="doc"><p>Compute gradients for a FakeQuantWithMinMaxArgs operation.</p></div></div><div class="top"><p class="src"><a name="v:fakeQuantWithMinMaxArgsGradient-39-" class="def">fakeQuantWithMinMaxArgsGradient'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>gradients</strong>: Backpropagated gradients above the FakeQuantWithMinMaxArgs operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>inputs</strong>: Values passed as inputs to the FakeQuantWithMinMaxArgs operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>backprops</strong>: Backpropagated gradients below the FakeQuantWithMinMaxArgs operation:
|
|
`gradients * (inputs >= min && inputs <= max)`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fakeQuantWithMinMaxVars" class="def">fakeQuantWithMinMaxVars</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>inputs</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>outputs</strong></p></td></tr></table></div><div class="doc"><p>Fake-quantize the <code>inputs</code> tensor of type float and shape `[b, h, w, d]` via</p><p>global float scalars <code><a href="../base-4.8.2.0/Data-Ord.html#v:min">min</a></code> and <code><a href="../base-4.8.2.0/Data-Ord.html#v:max">max</a></code> to <code>outputs</code> tensor of same shape as
|
|
<code>inputs</code>.</p><dl><dt>min; max</dt><dd>is the clamping range for the <code>inputs</code> data. Op divides this range
|
|
into 255 steps (total of 256 values), then replaces each <code>inputs</code> value with the
|
|
closest of the quantized step values.</dd></dl><p>This operation has a gradient and thus allows for training <code><a href="../base-4.8.2.0/Data-Ord.html#v:min">min</a></code> and <code><a href="../base-4.8.2.0/Data-Ord.html#v:max">max</a></code> values.</p></div></div><div class="top"><p class="src"><a name="v:fakeQuantWithMinMaxVars-39-" class="def">fakeQuantWithMinMaxVars'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>inputs</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>outputs</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fakeQuantWithMinMaxVarsGradient" class="def">fakeQuantWithMinMaxVarsGradient</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>gradients</strong>: Backpropagated gradients above the FakeQuantWithMinMaxVars operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>inputs</strong>: Values passed as inputs to the FakeQuantWithMinMaxVars operation.
|
|
min, max: Quantization interval, scalar floats.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max</strong></p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>backprops_wrt_input</strong>, <strong>backprop_wrt_min</strong>, <strong>backprop_wrt_max</strong>)</p><ul><li><strong>backprops_wrt_input</strong>: Backpropagated gradients w.r.t. inputs:
|
|
`gradients * (inputs >= min && inputs <= max)`.</li><li><strong>backprop_wrt_min</strong>: Backpropagated gradients w.r.t. min parameter:
|
|
`sum(gradients * (inputs < min))`.</li><li><strong>backprop_wrt_max</strong>: Backpropagated gradients w.r.t. max parameter:
|
|
`sum(gradients * (inputs > max))`.</li></ul></td></tr></table></div><div class="doc"><p>Compute gradients for a FakeQuantWithMinMaxVars operation.</p></div></div><div class="top"><p class="src"><a name="v:fakeQuantWithMinMaxVarsGradient-39-" class="def">fakeQuantWithMinMaxVarsGradient'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>gradients</strong>: Backpropagated gradients above the FakeQuantWithMinMaxVars operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>inputs</strong>: Values passed as inputs to the FakeQuantWithMinMaxVars operation.
|
|
min, max: Quantization interval, scalar floats.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max</strong></p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>backprops_wrt_input</strong>, <strong>backprop_wrt_min</strong>, <strong>backprop_wrt_max</strong>)</p><ul><li><strong>backprops_wrt_input</strong>: Backpropagated gradients w.r.t. inputs:
|
|
`gradients * (inputs >= min && inputs <= max)`.</li><li><strong>backprop_wrt_min</strong>: Backpropagated gradients w.r.t. min parameter:
|
|
`sum(gradients * (inputs < min))`.</li><li><strong>backprop_wrt_max</strong>: Backpropagated gradients w.r.t. max parameter:
|
|
`sum(gradients * (inputs > max))`.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fakeQuantWithMinMaxVarsPerChannel" class="def">fakeQuantWithMinMaxVarsPerChannel</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>inputs</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>outputs</strong></p></td></tr></table></div><div class="doc"><p>Fake-quantize the <code>inputs</code> tensor of type float and one of the shapes: `[d]`,</p><p>`[b, d]` `[b, h, w, d]` via per-channel floats <code><a href="../base-4.8.2.0/Data-Ord.html#v:min">min</a></code> and <code><a href="../base-4.8.2.0/Data-Ord.html#v:max">max</a></code> of shape `[d]`
|
|
to <code>outputs</code> tensor of same shape as <code>inputs</code>.</p><dl><dt>min; max</dt><dd>is the clamping range for the <code>inputs</code> data in the corresponding
|
|
depth channel. Op divides this range into 255 steps (total of 256 values), then
|
|
replaces each <code>inputs</code> value with the closest of the quantized step values.</dd></dl><p>This operation has a gradient and thus allows for training <code><a href="../base-4.8.2.0/Data-Ord.html#v:min">min</a></code> and <code><a href="../base-4.8.2.0/Data-Ord.html#v:max">max</a></code> values.</p></div></div><div class="top"><p class="src"><a name="v:fakeQuantWithMinMaxVarsPerChannel-39-" class="def">fakeQuantWithMinMaxVarsPerChannel'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>inputs</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>outputs</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fakeQuantWithMinMaxVarsPerChannelGradient" class="def">fakeQuantWithMinMaxVarsPerChannelGradient</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>gradients</strong>: Backpropagated gradients above the FakeQuantWithMinMaxVars operation,
|
|
shape one of: `[d]`, `[b, d]`, `[b, h, w, d]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>inputs</strong>: Values passed as inputs to the FakeQuantWithMinMaxVars operation, shape
|
|
same as <code>gradients</code>.
|
|
min, max: Quantization interval, floats of shape `[d]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max</strong></p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>backprops_wrt_input</strong>, <strong>backprop_wrt_min</strong>, <strong>backprop_wrt_max</strong>)</p><ul><li><strong>backprops_wrt_input</strong>: Backpropagated gradients w.r.t. inputs, shape same as
|
|
<code>inputs</code>:
|
|
`gradients * (inputs >= min && inputs <= max)`.</li><li><strong>backprop_wrt_min</strong>: Backpropagated gradients w.r.t. min parameter, shape `[d]`:
|
|
`sum_per_d(gradients * (inputs < min))`.</li><li><strong>backprop_wrt_max</strong>: Backpropagated gradients w.r.t. max parameter, shape `[d]`:
|
|
`sum_per_d(gradients * (inputs > max))`.</li></ul></td></tr></table></div><div class="doc"><p>Compute gradients for a FakeQuantWithMinMaxVarsPerChannel operation.</p></div></div><div class="top"><p class="src"><a name="v:fakeQuantWithMinMaxVarsPerChannelGradient-39-" class="def">fakeQuantWithMinMaxVarsPerChannelGradient'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>gradients</strong>: Backpropagated gradients above the FakeQuantWithMinMaxVars operation,
|
|
shape one of: `[d]`, `[b, d]`, `[b, h, w, d]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>inputs</strong>: Values passed as inputs to the FakeQuantWithMinMaxVars operation, shape
|
|
same as <code>gradients</code>.
|
|
min, max: Quantization interval, floats of shape `[d]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max</strong></p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>backprops_wrt_input</strong>, <strong>backprop_wrt_min</strong>, <strong>backprop_wrt_max</strong>)</p><ul><li><strong>backprops_wrt_input</strong>: Backpropagated gradients w.r.t. inputs, shape same as
|
|
<code>inputs</code>:
|
|
`gradients * (inputs >= min && inputs <= max)`.</li><li><strong>backprop_wrt_min</strong>: Backpropagated gradients w.r.t. min parameter, shape `[d]`:
|
|
`sum_per_d(gradients * (inputs < min))`.</li><li><strong>backprop_wrt_max</strong>: Backpropagated gradients w.r.t. max parameter, shape `[d]`:
|
|
`sum_per_d(gradients * (inputs > max))`.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fakeQueue" class="def">fakeQueue</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>resource</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong></p></td></tr></table></div><div class="doc"><p>Deprecated. Do not use.</p></div></div><div class="top"><p class="src"><a name="v:fakeQueue-39-" class="def">fakeQueue'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>resource</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fill" class="def">fill</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>dims</strong>: 1-D. Represents the shape of the output tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>value</strong>: 0-D (scalar). Value to fill the returned tensor.</p><p><code>compatibility(numpy)
|
|
Equivalent to np.full
|
|
</code>end_compatibility</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Creates a tensor filled with a scalar value.</p><p>This operation creates a tensor of shape <code>dims</code> and fills it with <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>.</p><p>For example:</p><p>```prettyprint
|
|
# Output tensor has shape [2, 3].
|
|
fill([2, 3], 9) ==> [[9, 9, 9]
|
|
[9, 9, 9]]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:fill-39-" class="def">fill'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>dims</strong>: 1-D. Represents the shape of the output tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>value</strong>: 0-D (scalar). Value to fill the returned tensor.</p><p><code>compatibility(numpy)
|
|
Equivalent to np.full
|
|
</code>end_compatibility</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fixedLengthRecordReader" class="def">fixedLengthRecordReader</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>record_bytes</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div><div class="doc"><p>A Reader that outputs fixed-length records from a file.</p></div></div><div class="top"><p class="src"><a name="v:fixedLengthRecordReader-39-" class="def">fixedLengthRecordReader'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>record_bytes</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fixedLengthRecordReaderV2" class="def">fixedLengthRecordReaderV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>record_bytes</strong></p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div><div class="doc"><p>A Reader that outputs fixed-length records from a file.</p></div></div><div class="top"><p class="src"><a name="v:fixedLengthRecordReaderV2-39-" class="def">fixedLengthRecordReaderV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>record_bytes</strong></p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fixedUnigramCandidateSampler" class="def">fixedUnigramCandidateSampler</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_sampled</strong>: Number of candidates to randomly sample per batch.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_true</strong>: Number of true labels per context.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>range_max</strong>: The sampler will sample integers from the interval [0, range_max).</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>unique</strong>: If unique is true, we sample with rejection, so that all sampled
|
|
candidates in a batch are unique. This requires some approximation to
|
|
estimate the post-rejection sampling probabilities.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>true_classes</strong>: A batch_size * num_true matrix, in which each row contains the
|
|
IDs of the num_true target_classes in the corresponding original label.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>sampled_candidates</strong>, <strong>true_expected_count</strong>, <strong>sampled_expected_count</strong>)</p><ul><li><strong>sampled_candidates</strong>: A vector of length num_sampled, in which each element is
|
|
the ID of a sampled candidate.</li><li><strong>true_expected_count</strong>: A batch_size * num_true matrix, representing
|
|
the number of times each candidate is expected to occur in a batch
|
|
of sampled candidates. If unique=true, then this is a probability.</li><li><strong>sampled_expected_count</strong>: A vector of length num_sampled, for each sampled
|
|
candidate representing the number of times the candidate is expected
|
|
to occur in a batch of sampled candidates. If unique=true, then this is a
|
|
probability.</li></ul></td></tr></table></div><div class="doc"><p>Generates labels for candidate sampling with a learned unigram distribution.</p><p>A unigram sampler could use a fixed unigram distribution read from a
|
|
file or passed in as an in-memory array instead of building up the distribution
|
|
from data on the fly. There is also an option to skew the distribution by
|
|
applying a distortion power to the weights.</p><p>The vocabulary file should be in CSV-like format, with the last field
|
|
being the weight associated with the word.</p><p>For each batch, this op picks a single set of sampled candidate labels.</p><p>The advantages of sampling candidates per-batch are simplicity and the
|
|
possibility of efficient dense matrix multiplication. The disadvantage is that
|
|
the sampled candidates must be chosen independently of the context and of the
|
|
true labels.</p></div></div><div class="top"><p class="src"><a name="v:fixedUnigramCandidateSampler-39-" class="def">fixedUnigramCandidateSampler'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_sampled</strong>: Number of candidates to randomly sample per batch.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_true</strong>: Number of true labels per context.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>range_max</strong>: The sampler will sample integers from the interval [0, range_max).</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>unique</strong>: If unique is true, we sample with rejection, so that all sampled
|
|
candidates in a batch are unique. This requires some approximation to
|
|
estimate the post-rejection sampling probabilities.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>true_classes</strong>: A batch_size * num_true matrix, in which each row contains the
|
|
IDs of the num_true target_classes in the corresponding original label.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>sampled_candidates</strong>, <strong>true_expected_count</strong>, <strong>sampled_expected_count</strong>)</p><ul><li><strong>sampled_candidates</strong>: A vector of length num_sampled, in which each element is
|
|
the ID of a sampled candidate.</li><li><strong>true_expected_count</strong>: A batch_size * num_true matrix, representing
|
|
the number of times each candidate is expected to occur in a batch
|
|
of sampled candidates. If unique=true, then this is a probability.</li><li><strong>sampled_expected_count</strong>: A vector of length num_sampled, for each sampled
|
|
candidate representing the number of times the candidate is expected
|
|
to occur in a batch of sampled candidates. If unique=true, then this is a
|
|
probability.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:floor" class="def">floor</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Returns element-wise largest integer not greater than x.</p></div></div><div class="top"><p class="src"><a name="v:floor-39-" class="def">floor'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:floorDiv" class="def">floorDiv</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns x // y element-wise.</p><ul><li>NOTE*: <code>FloorDiv</code> supports broadcasting. More about broadcasting
|
|
<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:floorDiv-39-" class="def">floorDiv'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:floorMod" class="def">floorMod</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns element-wise remainder of division. When `x < 0` xor `y < 0` is</p><p>true, this follows Python semantics in that the result here is consistent
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with a flooring divide. E.g. `floor(x / y) * y + mod(x, y) = x`.</p><ul><li>NOTE*: <code>FloorMod</code> supports broadcasting. More about broadcasting
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|
<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:floorMod-39-" class="def">floorMod'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fractionalAvgPool" class="def">fractionalAvgPool</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>row_pooling_sequence</strong>, <strong>col_pooling_sequence</strong>)</p><ul><li><strong>output</strong>: output tensor after fractional avg pooling.</li><li><strong>row_pooling_sequence</strong>: row pooling sequence, needed to calculate gradient.</li><li><strong>col_pooling_sequence</strong>: column pooling sequence, needed to calculate gradient.</li></ul></td></tr></table></div><div class="doc"><p>Performs fractional average pooling on the input.</p><p>Fractional average pooling is similar to Fractional max pooling in the pooling
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region generation step. The only difference is that after pooling regions are
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generated, a mean operation is performed instead of a max operation in each
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|
pooling region.</p></div></div><div class="top"><p class="src"><a name="v:fractionalAvgPool-39-" class="def">fractionalAvgPool'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>row_pooling_sequence</strong>, <strong>col_pooling_sequence</strong>)</p><ul><li><strong>output</strong>: output tensor after fractional avg pooling.</li><li><strong>row_pooling_sequence</strong>: row pooling sequence, needed to calculate gradient.</li><li><strong>col_pooling_sequence</strong>: column pooling sequence, needed to calculate gradient.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fractionalAvgPoolGrad" class="def">fractionalAvgPoolGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>orig_input_tensor_shape</strong>: Original input tensor shape for <code>fractional_avg_pool</code></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>out_backprop</strong>: 4-D with shape `[batch, height, width, channels]`. Gradients
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|
w.r.t. the output of <code>fractional_avg_pool</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>row_pooling_sequence</strong>: row pooling sequence, form pooling region with
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|
col_pooling_sequence.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>col_pooling_sequence</strong>: column pooling sequence, form pooling region with
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|
row_pooling sequence.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D. Gradients w.r.t. the input of <code>fractional_avg_pool</code>.</p></td></tr></table></div><div class="doc"><p>Computes gradient of the FractionalAvgPool function.</p><p>Unlike FractionalMaxPoolGrad, we don't need to find arg_max for
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FractionalAvgPoolGrad, we just need to evenly back-propagate each element of
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out_backprop to those indices that form the same pooling cell. Therefore, we
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|
just need to know the shape of original input tensor, instead of the whole
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|
tensor.</p></div></div><div class="top"><p class="src"><a name="v:fractionalAvgPoolGrad-39-" class="def">fractionalAvgPoolGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>orig_input_tensor_shape</strong>: Original input tensor shape for <code>fractional_avg_pool</code></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>out_backprop</strong>: 4-D with shape `[batch, height, width, channels]`. Gradients
|
|
w.r.t. the output of <code>fractional_avg_pool</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>row_pooling_sequence</strong>: row pooling sequence, form pooling region with
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|
col_pooling_sequence.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>col_pooling_sequence</strong>: column pooling sequence, form pooling region with
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|
row_pooling sequence.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D. Gradients w.r.t. the input of <code>fractional_avg_pool</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fractionalMaxPool" class="def">fractionalMaxPool</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>row_pooling_sequence</strong>, <strong>col_pooling_sequence</strong>)</p><ul><li><strong>output</strong>: output tensor after fractional max pooling.</li><li><strong>row_pooling_sequence</strong>: row pooling sequence, needed to calculate gradient.</li><li><strong>col_pooling_sequence</strong>: column pooling sequence, needed to calculate gradient.</li></ul></td></tr></table></div><div class="doc"><p>Performs fractional max pooling on the input.</p><p>Fractional max pooling is slightly different than regular max pooling. In
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|
regular max pooling, you downsize an input set by taking the maximum value of
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|
smaller N x N subsections of the set (often 2x2), and try to reduce the set by
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|
a factor of N, where N is an integer. Fractional max pooling, as you might
|
|
expect from the word "fractional", means that the overall reduction ratio N
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|
does not have to be an integer.</p><p>The sizes of the pooling regions are generated randomly but are fairly uniform.
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For example, let's look at the height dimension, and the constraints on the
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|
list of rows that will be pool boundaries.</p><p>First we define the following:</p><ol><li>input_row_length : the number of rows from the input set</li><li>output_row_length : which will be smaller than the input</li><li>alpha = input_row_length / output_row_length : our reduction ratio</li><li>K = floor(alpha)</li><li>row_pooling_sequence : this is the result list of pool boundary rows</li></ol><p>Then, row_pooling_sequence should satisfy:</p><ol><li>a[0] = 0 : the first value of the sequence is 0</li><li>a[end] = input_row_length : the last value of the sequence is the size</li><li>K <= (a[i+1] - a[i]) <= K+1 : all intervals are K or K+1 size</li><li>length(row_pooling_sequence) = output_row_length+1</li></ol><p>For more details on fractional max pooling, see this paper:
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|
<a href="http://arxiv.org/abs/1412.6071">Benjamin Graham, Fractional Max-Pooling</a></p></div></div><div class="top"><p class="src"><a name="v:fractionalMaxPool-39-" class="def">fractionalMaxPool'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>row_pooling_sequence</strong>, <strong>col_pooling_sequence</strong>)</p><ul><li><strong>output</strong>: output tensor after fractional max pooling.</li><li><strong>row_pooling_sequence</strong>: row pooling sequence, needed to calculate gradient.</li><li><strong>col_pooling_sequence</strong>: column pooling sequence, needed to calculate gradient.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fractionalMaxPoolGrad" class="def">fractionalMaxPoolGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>orig_input</strong>: Original input for <code>fractional_max_pool</code></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>orig_output</strong>: Original output for <code>fractional_max_pool</code></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: 4-D with shape `[batch, height, width, channels]`. Gradients
|
|
w.r.t. the output of <code>fractional_max_pool</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>row_pooling_sequence</strong>: row pooling sequence, form pooling region with
|
|
col_pooling_sequence.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>col_pooling_sequence</strong>: column pooling sequence, form pooling region with
|
|
row_pooling sequence.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D. Gradients w.r.t. the input of <code>fractional_max_pool</code>.</p></td></tr></table></div><div class="doc"><p>Computes gradient of the FractionalMaxPool function.</p></div></div><div class="top"><p class="src"><a name="v:fractionalMaxPoolGrad-39-" class="def">fractionalMaxPoolGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>orig_input</strong>: Original input for <code>fractional_max_pool</code></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>orig_output</strong>: Original output for <code>fractional_max_pool</code></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>out_backprop</strong>: 4-D with shape `[batch, height, width, channels]`. Gradients
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|
w.r.t. the output of <code>fractional_max_pool</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>row_pooling_sequence</strong>: row pooling sequence, form pooling region with
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|
col_pooling_sequence.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>col_pooling_sequence</strong>: column pooling sequence, form pooling region with
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|
row_pooling sequence.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D. Gradients w.r.t. the input of <code>fractional_max_pool</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fusedBatchNorm" class="def">fusedBatchNorm</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong>: A 4D Tensor for input data.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>scale</strong>: A 1D Tensor for scaling factor, to scale the normalized x.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>offset</strong>: A 1D Tensor for offset, to shift to the normalized x.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>mean</strong>: A 1D Tensor for population mean. Used for inference only;
|
|
must be empty for training.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>variance</strong>: A 1D Tensor for population variance. Used for inference only;
|
|
must be empty for training.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>y</strong>, <strong>batch_mean</strong>, <strong>batch_variance</strong>, <strong>reserve_space_1</strong>, <strong>reserve_space_2</strong>)</p><ul><li><strong>y</strong>: A 4D Tensor for output data.</li><li><strong>batch_mean</strong>: A 1D Tensor for the computed batch mean, to be used by TensorFlow
|
|
to compute the running mean.</li><li><strong>batch_variance</strong>: A 1D Tensor for the computed batch variance, to be used by
|
|
TensorFlow to compute the running variance.</li><li><strong>reserve_space_1</strong>: A 1D Tensor for the computed batch mean, to be reused
|
|
in the gradient computation.</li><li><strong>reserve_space_2</strong>: A 1D Tensor for the computed batch variance (inverted variance
|
|
in the cuDNN case), to be used in the gradient computation.</li></ul></td></tr></table></div><div class="doc"><p>Batch normalization.</p><p>Note that the size of 4D Tensors are defined by either <a href="NHWC.html">NHWC</a> or <a href="NCHW.html">NCHW</a>.
|
|
The size of 1D Tensors matches the dimension C of the 4D Tensors.</p></div></div><div class="top"><p class="src"><a name="v:fusedBatchNorm-39-" class="def">fusedBatchNorm'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong>: A 4D Tensor for input data.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>scale</strong>: A 1D Tensor for scaling factor, to scale the normalized x.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>offset</strong>: A 1D Tensor for offset, to shift to the normalized x.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>mean</strong>: A 1D Tensor for population mean. Used for inference only;
|
|
must be empty for training.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>variance</strong>: A 1D Tensor for population variance. Used for inference only;
|
|
must be empty for training.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>y</strong>, <strong>batch_mean</strong>, <strong>batch_variance</strong>, <strong>reserve_space_1</strong>, <strong>reserve_space_2</strong>)</p><ul><li><strong>y</strong>: A 4D Tensor for output data.</li><li><strong>batch_mean</strong>: A 1D Tensor for the computed batch mean, to be used by TensorFlow
|
|
to compute the running mean.</li><li><strong>batch_variance</strong>: A 1D Tensor for the computed batch variance, to be used by
|
|
TensorFlow to compute the running variance.</li><li><strong>reserve_space_1</strong>: A 1D Tensor for the computed batch mean, to be reused
|
|
in the gradient computation.</li><li><strong>reserve_space_2</strong>: A 1D Tensor for the computed batch variance (inverted variance
|
|
in the cuDNN case), to be used in the gradient computation.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fusedBatchNormGrad" class="def">fusedBatchNormGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>y_backprop</strong>: A 4D Tensor for the gradient with respect to y.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>x</strong>: A 4D Tensor for input data.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>scale</strong>: A 1D Tensor for scaling factor, to scale the normalized x.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>reserve_space_1</strong>: A 1D Tensor for the computed batch mean, to be reused
|
|
in the gradient computation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>reserve_space_2</strong>: A 1D Tensor for the computed batch variance (inverted variance
|
|
in the cuDNN case), to be used in the gradient computation.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>x_backprop</strong>, <strong>scale_backprop</strong>, <strong>offset_backprop</strong>, <strong>reserve_space_3</strong>, <strong>reserve_space_4</strong>)</p><ul><li><strong>x_backprop</strong>: A 4D Tensor for the gradient with respect to x.</li><li><strong>scale_backprop</strong>: A 1D Tensor for the gradient with respect to scale.</li><li><strong>offset_backprop</strong>: A 1D Tensor for the gradient with respect to offset.</li><li><strong>reserve_space_3</strong>: Unused placeholder to match the mean input in FusedBatchNorm.</li><li><strong>reserve_space_4</strong>: Unused placeholder to match the variance input
|
|
in FusedBatchNorm.</li></ul></td></tr></table></div><div class="doc"><p>Gradient for batch normalization.</p><p>Note that the size of 4D Tensors are defined by either <a href="NHWC.html">NHWC</a> or <a href="NCHW.html">NCHW</a>.
|
|
The size of 1D Tensors matches the dimension C of the 4D Tensors.</p></div></div><div class="top"><p class="src"><a name="v:fusedBatchNormGrad-39-" class="def">fusedBatchNormGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>y_backprop</strong>: A 4D Tensor for the gradient with respect to y.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>x</strong>: A 4D Tensor for input data.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>scale</strong>: A 1D Tensor for scaling factor, to scale the normalized x.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>reserve_space_1</strong>: A 1D Tensor for the computed batch mean, to be reused
|
|
in the gradient computation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>reserve_space_2</strong>: A 1D Tensor for the computed batch variance (inverted variance
|
|
in the cuDNN case), to be used in the gradient computation.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>x_backprop</strong>, <strong>scale_backprop</strong>, <strong>offset_backprop</strong>, <strong>reserve_space_3</strong>, <strong>reserve_space_4</strong>)</p><ul><li><strong>x_backprop</strong>: A 4D Tensor for the gradient with respect to x.</li><li><strong>scale_backprop</strong>: A 1D Tensor for the gradient with respect to scale.</li><li><strong>offset_backprop</strong>: A 1D Tensor for the gradient with respect to offset.</li><li><strong>reserve_space_3</strong>: Unused placeholder to match the mean input in FusedBatchNorm.</li><li><strong>reserve_space_4</strong>: Unused placeholder to match the variance input
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|
in FusedBatchNorm.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fusedPadConv2D" class="def">fusedPadConv2D</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, in_height, in_width, in_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>paddings</strong>: A two-column matrix specifying the padding sizes. The number of
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|
rows must be the same as the rank of <code>input</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>filter</strong>: 4-D with shape
|
|
`[filter_height, filter_width, in_channels, out_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Performs a padding as a preprocess during a convolution.</p><p>Similar to FusedResizeAndPadConv2d, this op allows for an optimized
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|
implementation where the spatial padding transformation stage is fused with the
|
|
im2col lookup, but in this case without the bilinear filtering required for
|
|
resizing. Fusing the padding prevents the need to write out the intermediate
|
|
results as whole tensors, reducing memory pressure, and we can get some latency
|
|
gains by merging the transformation calculations.
|
|
The data_format attribute for Conv2D isn't supported by this op, and <code>NHWC</code>
|
|
order is used instead.
|
|
Internally this op uses a single per-graph scratch buffer, which means that it
|
|
will block if multiple versions are being run in parallel. This is because this
|
|
operator is primarily an optimization to minimize memory usage.</p></div></div><div class="top"><p class="src"><a name="v:fusedPadConv2D-39-" class="def">fusedPadConv2D'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, in_height, in_width, in_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>paddings</strong>: A two-column matrix specifying the padding sizes. The number of
|
|
rows must be the same as the rank of <code>input</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>filter</strong>: 4-D with shape
|
|
`[filter_height, filter_width, in_channels, out_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:fusedResizeAndPadConv2D" class="def">fusedResizeAndPadConv2D</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, in_height, in_width, in_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong>: A 1-D int32 Tensor of 2 elements: `new_height, new_width`. The
|
|
new size for the images.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>paddings</strong>: A two-column matrix specifying the padding sizes. The number of
|
|
rows must be the same as the rank of <code>input</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>filter</strong>: 4-D with shape
|
|
`[filter_height, filter_width, in_channels, out_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Performs a resize and padding as a preprocess during a convolution.</p><p>It's often possible to do spatial transformations more efficiently as part of
|
|
the packing stage of a convolution, so this op allows for an optimized
|
|
implementation where these stages are fused together. This prevents the need to
|
|
write out the intermediate results as whole tensors, reducing memory pressure,
|
|
and we can get some latency gains by merging the transformation calculations.
|
|
The data_format attribute for Conv2D isn't supported by this op, and defaults to
|
|
<code>NHWC</code> order.
|
|
Internally this op uses a single per-graph scratch buffer, which means that it
|
|
will block if multiple versions are being run in parallel. This is because this
|
|
operator is primarily an optimization to minimize memory usage.</p></div></div><div class="top"><p class="src"><a name="v:fusedResizeAndPadConv2D-39-" class="def">fusedResizeAndPadConv2D'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, in_height, in_width, in_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong>: A 1-D int32 Tensor of 2 elements: `new_height, new_width`. The
|
|
new size for the images.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>paddings</strong>: A two-column matrix specifying the padding sizes. The number of
|
|
rows must be the same as the rank of <code>input</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>filter</strong>: 4-D with shape
|
|
`[filter_height, filter_width, in_channels, out_channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:gather" class="def">gather</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tparams, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tparams</td><td class="doc"><p><strong>params</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tparams</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Gather slices from <code>params</code> according to <code>indices</code>.</p><p><code>indices</code> must be an integer tensor of any dimension (usually 0-D or 1-D).
|
|
Produces an output tensor with shape `indices.shape + params.shape[1:]` where:</p><p>```python
|
|
# Scalar indices
|
|
output[:, ..., :] = params[indices, :, ... :]</p><p># Vector indices
|
|
output[i, :, ..., :] = params[indices[i], :, ... :]</p><p># Higher rank indices
|
|
output[i, ..., j, :, ... :] = params[indices[i, ..., j], :, ..., :]
|
|
```</p><p>If <code>indices</code> is a permutation and `len(indices) == params.shape[0]` then
|
|
this operation will permute <code>params</code> accordingly.</p><p><a href="div">style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;"</a>
|
|
<a href="img">style="width:100%" src="../../images/Gather.png" alt</a>
|
|
<a href="/div">/div</a></p></div></div><div class="top"><p class="src"><a name="v:gather-39-" class="def">gather'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tparams, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tparams</td><td class="doc"><p><strong>params</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tparams</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:gatherNd" class="def">gatherNd</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tparams, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tparams</td><td class="doc"><p><strong>params</strong>: `P-D`. The tensor from which to gather values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: `Q-D`. Index tensor having shape `[d_0, ..., d_{Q-2}, K]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tparams</td><td class="doc"><p><strong>output</strong>: `(P+Q-K-1)-D`. Values from <code>params</code> gathered from indices given by
|
|
<code>indices</code>.</p></td></tr></table></div><div class="doc"><p>Gather values or slices from <code>params</code> according to <code>indices</code>.</p><p><code>params</code> is a Tensor of rank <code>P</code> and <code>indices</code> is a Tensor of rank <code>Q</code>.</p><p><code>indices</code> must be integer tensor, containing indices into <code>params</code>.
|
|
It must be shape `[d_0, ..., d_{Q-2}, K]` where `0 < K <= P`.</p><p>The innermost dimension of <code>indices</code> (with length <code>K</code>) corresponds to
|
|
indices into elements (if `K = P`) or slices (if `K < P`) along the <code>K</code>th
|
|
dimension of <code>params</code>.</p><p>Produces an output tensor with shape</p><p>```
|
|
[d_0, ..., d_{Q-2}, params.shape[K], ..., params.shape[P-1]].
|
|
```</p><p>Some examples below.</p><p>Simple indexing into a matrix:</p><p>```python
|
|
indices = [[0, 0], [1, 1]]
|
|
params = [[<code>a</code>, <code>b</code>], [<code>c</code>, <code>d</code>]]
|
|
output = [<code>a</code>, <code>d</code>]
|
|
```</p><p>Slice indexing into a matrix:</p><p>```python
|
|
indices = [[1], [0]]
|
|
params = [[<code>a</code>, <code>b</code>], [<code>c</code>, <code>d</code>]]
|
|
output = [[<code>c</code>, <code>d</code>], [<code>a</code>, <code>b</code>]]
|
|
```</p><p>Indexing into a 3-tensor:</p><p>```python
|
|
indices = [[1]]
|
|
params = [[[<code>a0</code>, <code>b0</code>], [<code>c0</code>, <code>d0</code>]],
|
|
[[<code>a1</code>, <code>b1</code>], [<code>c1</code>, <code>d1</code>]]]
|
|
output = [[[<code>a1</code>, <code>b1</code>], [<code>c1</code>, <code>d1</code>]]]</p><p>indices = [[0, 1], [1, 0]]
|
|
params = [[[<code>a0</code>, <code>b0</code>], [<code>c0</code>, <code>d0</code>]],
|
|
[[<code>a1</code>, <code>b1</code>], [<code>c1</code>, <code>d1</code>]]]
|
|
output = [[<code>c0</code>, <code>d0</code>], [<code>a1</code>, <code>b1</code>]]</p><p>indices = [[0, 0, 1], [1, 0, 1]]
|
|
params = [[[<code>a0</code>, <code>b0</code>], [<code>c0</code>, <code>d0</code>]],
|
|
[[<code>a1</code>, <code>b1</code>], [<code>c1</code>, <code>d1</code>]]]
|
|
output = [<code>b0</code>, <code>b1</code>]
|
|
```</p><p>Batched indexing into a matrix:</p><p>```python
|
|
indices = [[[0, 0]], [[0, 1]]]
|
|
params = [[<code>a</code>, <code>b</code>], [<code>c</code>, <code>d</code>]]
|
|
output = [[<code>a</code>], [<code>b</code>]]
|
|
```</p><p>Batched slice indexing into a matrix:</p><p>```python
|
|
indices = [[[1]], [[0]]]
|
|
params = [[<code>a</code>, <code>b</code>], [<code>c</code>, <code>d</code>]]
|
|
output = [[[<code>c</code>, <code>d</code>]], [[<code>a</code>, <code>b</code>]]]
|
|
```</p><p>Batched indexing into a 3-tensor:</p><p>```python
|
|
indices = [[[1]], [[0]]]
|
|
params = [[[<code>a0</code>, <code>b0</code>], [<code>c0</code>, <code>d0</code>]],
|
|
[[<code>a1</code>, <code>b1</code>], [<code>c1</code>, <code>d1</code>]]]
|
|
output = [[[[<code>a1</code>, <code>b1</code>], [<code>c1</code>, <code>d1</code>]]],
|
|
[[[<code>a0</code>, <code>b0</code>], [<code>c0</code>, <code>d0</code>]]]]</p><p>indices = [[[0, 1], [1, 0]], [[0, 0], [1, 1]]]
|
|
params = [[[<code>a0</code>, <code>b0</code>], [<code>c0</code>, <code>d0</code>]],
|
|
[[<code>a1</code>, <code>b1</code>], [<code>c1</code>, <code>d1</code>]]]
|
|
output = [[[<code>c0</code>, <code>d0</code>], [<code>a1</code>, <code>b1</code>]],
|
|
[[<code>a0</code>, <code>b0</code>], [<code>c1</code>, <code>d1</code>]]]</p><p>indices = [[[0, 0, 1], [1, 0, 1]], [[0, 1, 1], [1, 1, 0]]]
|
|
params = [[[<code>a0</code>, <code>b0</code>], [<code>c0</code>, <code>d0</code>]],
|
|
[[<code>a1</code>, <code>b1</code>], [<code>c1</code>, <code>d1</code>]]]
|
|
output = [[<code>b0</code>, <code>b1</code>], [<code>d0</code>, <code>c1</code>]]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:gatherNd-39-" class="def">gatherNd'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tparams, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tparams</td><td class="doc"><p><strong>params</strong>: `P-D`. The tensor from which to gather values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: `Q-D`. Index tensor having shape `[d_0, ..., d_{Q-2}, K]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tparams</td><td class="doc"><p><strong>output</strong>: `(P+Q-K-1)-D`. Values from <code>params</code> gathered from indices given by
|
|
<code>indices</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:getSessionHandle" class="def">getSessionHandle</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: The tensor to be stored.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle for the tensor stored in the session state.</p></td></tr></table></div><div class="doc"><p>Store the input tensor in the state of the current session.</p></div></div><div class="top"><p class="src"><a name="v:getSessionHandle-39-" class="def">getSessionHandle'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: The tensor to be stored.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle for the tensor stored in the session state.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:getSessionTensor" class="def">getSessionTensor</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle for a tensor stored in the session state.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</td><td class="doc"><p><strong>value</strong>: The tensor for the given handle.</p></td></tr></table></div><div class="doc"><p>Get the value of the tensor specified by its handle.</p></div></div><div class="top"><p class="src"><a name="v:getSessionTensor-39-" class="def">getSessionTensor'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle for a tensor stored in the session state.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</td><td class="doc"><p><strong>value</strong>: The tensor for the given handle.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:greater" class="def">greater</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns the truth value of (x > y) element-wise.</p><ul><li>NOTE*: <code>Greater</code> supports broadcasting. More about broadcasting
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<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:greater-39-" class="def">greater'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:greaterEqual" class="def">greaterEqual</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns the truth value of (x >= y) element-wise.</p><ul><li>NOTE*: <code>GreaterEqual</code> supports broadcasting. More about broadcasting
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|
<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:greaterEqual-39-" class="def">greaterEqual'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:hSVToRGB" class="def">hSVToRGB</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>images</strong>: 1-D or higher rank. HSV data to convert. Last dimension must be size 3.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: <code>images</code> converted to RGB.</p></td></tr></table></div><div class="doc"><p>Convert one or more images from HSV to RGB.</p><p>Outputs a tensor of the same shape as the <code>images</code> tensor, containing the RGB
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value of the pixels. The output is only well defined if the value in <code>images</code>
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|
are in `[0,1]`.</p><p>See <code>rgb_to_hsv</code> for a description of the HSV encoding.</p></div></div><div class="top"><p class="src"><a name="v:hSVToRGB-39-" class="def">hSVToRGB'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>images</strong>: 1-D or higher rank. HSV data to convert. Last dimension must be size 3.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: <code>images</code> converted to RGB.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:hashTable" class="def">hashTable</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>key_dtype</strong>: Type of the table keys.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>value_dtype</strong>: Type of the table values.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>table_handle</strong>: Handle to a table.</p></td></tr></table></div><div class="doc"><p>Creates a non-initialized hash table.</p><p>This op creates a hash table, specifying the type of its keys and values.
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Before using the table you will have to initialize it. After initialization the
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table will be immutable.</p></div></div><div class="top"><p class="src"><a name="v:hashTable-39-" class="def">hashTable'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>key_dtype</strong>: Type of the table keys.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>value_dtype</strong>: Type of the table values.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>table_handle</strong>: Handle to a table.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:histogramSummary" class="def">histogramSummary</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tag</strong>: Scalar. Tag to use for the <code><a href="Summary.html#v:Value">Value</a></code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>values</strong>: Any shape. Values to use to build the histogram.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>summary</strong>: Scalar. Serialized <code>Summary</code> protocol buffer.</p></td></tr></table></div><div class="doc"><p>Outputs a <code>Summary</code> protocol buffer with a histogram.</p><p>The generated
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<a href="https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto">`Summary`</a>
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has one summary value containing a histogram for <code>values</code>.</p><p>This op reports an <code>InvalidArgument</code> error if any value is not finite.</p></div></div><div class="top"><p class="src"><a name="v:histogramSummary-39-" class="def">histogramSummary'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tag</strong>: Scalar. Tag to use for the <code><a href="Summary.html#v:Value">Value</a></code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>values</strong>: Any shape. Values to use to build the histogram.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>summary</strong>: Scalar. Serialized <code>Summary</code> protocol buffer.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:iFFT" class="def">iFFT</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong>: A complex64 tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong>: A complex64 tensor of the same shape as <code>input</code>. The inner-most
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dimension of <code>input</code> is replaced with its inverse 1D Fourier Transform.</p></td></tr></table></div><div class="doc"><p>Compute the inverse 1-dimensional discrete Fourier Transform over the inner-most</p><p>dimension of <code>input</code>.</p></div></div><div class="top"><p class="src"><a name="v:iFFT-39-" class="def">iFFT'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong>: A complex64 tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong>: A complex64 tensor of the same shape as <code>input</code>. The inner-most
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dimension of <code>input</code> is replaced with its inverse 1D Fourier Transform.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:iFFT2D" class="def">iFFT2D</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong>: A complex64 tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong>: A complex64 tensor of the same shape as <code>input</code>. The inner-most 2
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dimensions of <code>input</code> are replaced with their inverse 2D Fourier Transform.</p><p><code>compatibility(numpy)
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Equivalent to np.ifft2
|
|
</code>end_compatibility</p></td></tr></table></div><div class="doc"><p>Compute the inverse 2-dimensional discrete Fourier Transform over the inner-most</p><p>2 dimensions of <code>input</code>.</p></div></div><div class="top"><p class="src"><a name="v:iFFT2D-39-" class="def">iFFT2D'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong>: A complex64 tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong>: A complex64 tensor of the same shape as <code>input</code>. The inner-most 2
|
|
dimensions of <code>input</code> are replaced with their inverse 2D Fourier Transform.</p><p><code>compatibility(numpy)
|
|
Equivalent to np.ifft2
|
|
</code>end_compatibility</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:iFFT3D" class="def">iFFT3D</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong>: A complex64 tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong>: A complex64 tensor of the same shape as <code>input</code>. The inner-most 3
|
|
dimensions of <code>input</code> are replaced with their inverse 3D Fourier Transform.</p><p><code>compatibility(numpy)
|
|
Equivalent to np.fft3
|
|
</code>end_compatibility</p></td></tr></table></div><div class="doc"><p>Compute the inverse 3-dimensional discrete Fourier Transform over the inner-most</p><p>3 dimensions of <code>input</code>.</p></div></div><div class="top"><p class="src"><a name="v:iFFT3D-39-" class="def">iFFT3D'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>input</strong>: A complex64 tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> (<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>output</strong>: A complex64 tensor of the same shape as <code>input</code>. The inner-most 3
|
|
dimensions of <code>input</code> are replaced with their inverse 3D Fourier Transform.</p><p><code>compatibility(numpy)
|
|
Equivalent to np.fft3
|
|
</code>end_compatibility</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:identity" class="def">identity</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Return a tensor with the same shape and contents as the input tensor or value.</p></div></div><div class="top"><p class="src"><a name="v:identity-39-" class="def">identity'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:identityReader" class="def">identityReader</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div><div class="doc"><p>A Reader that outputs the queued work as both the key and value.</p><p>To use, enqueue strings in a Queue. ReaderRead will take the front
|
|
work string and output (work, work).</p></div></div><div class="top"><p class="src"><a name="v:identityReader-39-" class="def">identityReader'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:identityReaderV2" class="def">identityReaderV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div><div class="doc"><p>A Reader that outputs the queued work as both the key and value.</p><p>To use, enqueue strings in a Queue. ReaderRead will take the front
|
|
work string and output (work, work).</p></div></div><div class="top"><p class="src"><a name="v:identityReaderV2-39-" class="def">identityReaderV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:igamma" class="def">igamma</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>a</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Compute the lower regularized incomplete Gamma function `Q(a, x)`.</p><p>The lower regularized incomplete Gamma function is defined as:</p><p>```
|
|
P(a, x) = gamma(a, x) / Gamma(a) = 1 - Q(a, x)
|
|
```
|
|
where
|
|
```
|
|
gamma(a, x) = int_{0}^{x} t^{a-1} exp(-t) dt
|
|
```
|
|
is the lower incomplete Gamma function.</p><p>Note, above `Q(a, x)` (<code>Igammac</code>) is the upper regularized complete
|
|
Gamma function.</p></div></div><div class="top"><p class="src"><a name="v:igamma-39-" class="def">igamma'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>a</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:igammac" class="def">igammac</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>a</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Compute the upper regularized incomplete Gamma function `Q(a, x)`.</p><p>The upper regularized incomplete Gamma function is defined as:</p><p>```
|
|
Q(a, x) = Gamma(a, x) / Gamma(a) = 1 - P(a, x)
|
|
```
|
|
where
|
|
```
|
|
Gamma(a, x) = int_{x}^{infty} t^{a-1} exp(-t) dt
|
|
```
|
|
is the upper incomplete Gama function.</p><p>Note, above `P(a, x)` (<code>Igamma</code>) is the lower regularized complete
|
|
Gamma function.</p></div></div><div class="top"><p class="src"><a name="v:igammac-39-" class="def">igammac'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>a</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:imag" class="def">imag</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tout)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tout</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Returns the imaginary part of a complex number.</p><p>Given a tensor <code>input</code> of complex numbers, this operation returns a tensor of
|
|
type <code>float</code> that is the imaginary part of each element in <code>input</code>. All
|
|
elements in <code>input</code> must be complex numbers of the form \(a + bj\), where *a*
|
|
is the real part and *b* is the imaginary part returned by this operation.</p><p>For example:</p><p>```
|
|
# tensor <code>input</code> is [-2.25 + 4.75j, 3.25 + 5.75j]
|
|
tf.imag(input) ==> [4.75, 5.75]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:imag-39-" class="def">imag'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tout)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tout</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:imageSummary" class="def">imageSummary</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tag</strong>: Scalar. Used to build the <code>tag</code> attribute of the summary values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>tensor</strong>: 4-D of shape `[batch_size, height, width, channels]` where
|
|
<code>channels</code> is 1, 3, or 4.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>summary</strong>: Scalar. Serialized <code>Summary</code> protocol buffer.</p></td></tr></table></div><div class="doc"><p>Outputs a <code>Summary</code> protocol buffer with images.</p><p>The summary has up to <code>max_images</code> summary values containing images. The
|
|
images are built from <code>tensor</code> which must be 4-D with shape `[batch_size,
|
|
height, width, channels]` and where <code>channels</code> can be:</p><ul><li>1: <code>tensor</code> is interpreted as Grayscale.</li><li>3: <code>tensor</code> is interpreted as RGB.</li><li>4: <code>tensor</code> is interpreted as RGBA.</li></ul><p>The images have the same number of channels as the input tensor. For float
|
|
input, the values are normalized one image at a time to fit in the range
|
|
`[0, 255]`. <code>uint8</code> values are unchanged. The op uses two different
|
|
normalization algorithms:</p><ul><li>If the input values are all positive, they are rescaled so the largest one
|
|
is 255.</li><li>If any input value is negative, the values are shifted so input value 0.0
|
|
is at 127. They are then rescaled so that either the smallest value is 0,
|
|
or the largest one is 255.</li></ul><p>The <code>tag</code> argument is a scalar <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> of type <code>string</code>. It is used to
|
|
build the <code>tag</code> of the summary values:</p><ul><li>If <code>max_images</code> is 1, the summary value tag is '*tag*/image'.</li><li>If <code>max_images</code> is greater than 1, the summary value tags are
|
|
generated sequentially as '*tag*/image/0', '*tag*/image/1', etc.</li></ul><p>The <code>bad_color</code> argument is the color to use in the generated images for
|
|
non-finite input values. It is a <code>unit8</code> 1-D tensor of length <code>channels</code>.
|
|
Each element must be in the range `[0, 255]` (It represents the value of a
|
|
pixel in the output image). Non-finite values in the input tensor are
|
|
replaced by this tensor in the output image. The default value is the color
|
|
red.</p></div></div><div class="top"><p class="src"><a name="v:imageSummary-39-" class="def">imageSummary'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tag</strong>: Scalar. Used to build the <code>tag</code> attribute of the summary values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>tensor</strong>: 4-D of shape `[batch_size, height, width, channels]` where
|
|
<code>channels</code> is 1, 3, or 4.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>summary</strong>: Scalar. Serialized <code>Summary</code> protocol buffer.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:immutableConst" class="def">immutableConst</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: Shape of the returned tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</td><td class="doc"><p><strong>tensor</strong></p></td></tr></table></div><div class="doc"><p>Returns immutable tensor from memory region.</p><p>The current implementation memmaps the tensor from a file.</p></div></div><div class="top"><p class="src"><a name="v:immutableConst-39-" class="def">immutableConst'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: Shape of the returned tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</td><td class="doc"><p><strong>tensor</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:inTopK" class="def">inTopK</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>k</strong>: Number of top elements to look at for computing precision.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>predictions</strong>: A <code>batch_size</code> x <code>classes</code> tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>targets</strong>: A <code>batch_size</code> vector of class ids.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>precision</strong>: Computed Precision at <code>k</code> as a `bool Tensor`.</p></td></tr></table></div><div class="doc"><p>Says whether the targets are in the top <code>K</code> predictions.</p><p>This outputs a <code>batch_size</code> bool array, an entry `out[i]` is <code>true</code> if the
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prediction for the target class is among the top <code>k</code> predictions among
|
|
all predictions for example <code>i</code>. Note that the behavior of <code>InTopK</code> differs
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from the <code>TopK</code> op in its handling of ties; if multiple classes have the
|
|
same prediction value and straddle the top-<code>k</code> boundary, all of those
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|
classes are considered to be in the top <code>k</code>.</p><p>More formally, let</p><p>\(predictions_i\) be the predictions for all classes for example <code>i</code>,
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\(targets_i\) be the target class for example <code>i</code>,
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\(out_i\) be the output for example <code>i</code>,</p><p>$$out_i = predictions_{i, targets_i} in TopKIncludingTies(predictions_i)$$</p></div></div><div class="top"><p class="src"><a name="v:inTopK-39-" class="def">inTopK'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>k</strong>: Number of top elements to look at for computing precision.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>predictions</strong>: A <code>batch_size</code> x <code>classes</code> tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>targets</strong>: A <code>batch_size</code> vector of class ids.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>precision</strong>: Computed Precision at <code>k</code> as a `bool Tensor`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:initializeTable" class="def">initializeTable</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tkey, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tval)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>table_handle</strong>: Handle to a table which will be initialized.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tkey</td><td class="doc"><p><strong>keys</strong>: Keys of type Tkey.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tval</td><td class="doc"><p><strong>values</strong>: Values of type Tval.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Table initializer that takes two tensors for keys and values respectively.</p></div></div><div class="top"><p class="src"><a name="v:initializeTable-39-" class="def">initializeTable'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tkey, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tval)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>table_handle</strong>: Handle to a table which will be initialized.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tkey</td><td class="doc"><p><strong>keys</strong>: Keys of type Tkey.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tval</td><td class="doc"><p><strong>values</strong>: Values of type Tval.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:initializeTableFromTextFile" class="def">initializeTableFromTextFile</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>key_index</strong>: Column index in a line to get the table <code>key</code> values from.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>value_index</strong>: Column index that represents information of a line to get the table
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<code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> values from.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>table_handle</strong>: Handle to a table which will be initialized.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>filename</strong>: Filename of a vocabulary text file.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Initializes a table from a text file.</p><p>It inserts one key-value pair into the table for each line of the file.
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The key and value is extracted from the whole line content, elements from the
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|
split line based on <code>delimiter</code> or the line number (starting from zero).
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Where to extract the key and value from a line is specified by <code>key_index</code> and
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|
<code>value_index</code>.</p><ul><li>A value of -1 means use the line number(starting from zero), expects <code>int64</code>.</li><li>A value of -2 means use the whole line content, expects <code>string</code>.</li><li>A value >= 0 means use the index (starting at zero) of the split line based
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|
on <code>delimiter</code>.</li></ul></div></div><div class="top"><p class="src"><a name="v:initializeTableFromTextFile-39-" class="def">initializeTableFromTextFile'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>key_index</strong>: Column index in a line to get the table <code>key</code> values from.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>value_index</strong>: Column index that represents information of a line to get the table
|
|
<code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> values from.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>table_handle</strong>: Handle to a table which will be initialized.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>filename</strong>: Filename of a vocabulary text file.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:inv" class="def">inv</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes the reciprocal of x element-wise.</p><p>I.e., \(y = 1 / x\).</p></div></div><div class="top"><p class="src"><a name="v:inv-39-" class="def">inv'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:invGrad" class="def">invGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Computes the gradient for the inverse of <code>x</code> wrt its input.</p><p>Specifically, `grad = -dy * y*y`, where `y = 1/x`, and <code>dy</code>
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is the corresponding input gradient.</p></div></div><div class="top"><p class="src"><a name="v:invGrad-39-" class="def">invGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:invertPermutation" class="def">invertPermutation</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong>: 1-D.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong>: 1-D.</p></td></tr></table></div><div class="doc"><p>Computes the inverse permutation of a tensor.</p><p>This operation computes the inverse of an index permutation. It takes a 1-D
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integer tensor <code>x</code>, which represents the indices of a zero-based array, and
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|
swaps each value with its index position. In other words, for an output tensor
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|
<code>y</code> and an input tensor <code>x</code>, this operation computes the following:</p><p>`y[x[i]] = i for i in [0, 1, ..., len(x) - 1]`</p><p>The values must include 0. There can be no duplicate values or negative values.</p><p>For example:</p><p>```prettyprint
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|
# tensor <code>x</code> is [3, 4, 0, 2, 1]
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|
invert_permutation(x) ==> [2, 4, 3, 0, 1]
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|
```</p></div></div><div class="top"><p class="src"><a name="v:invertPermutation-39-" class="def">invertPermutation'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong>: 1-D.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong>: 1-D.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:isFinite" class="def">isFinite</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Returns which elements of x are finite.</p><p><code>compatibility(numpy)
|
|
Equivalent to np.isfinite
|
|
</code>end_compatibility</p></div></div><div class="top"><p class="src"><a name="v:isFinite-39-" class="def">isFinite'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:isInf" class="def">isInf</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Returns which elements of x are Inf.</p><p><code>compatibility(numpy)
|
|
Equivalent to np.isinf
|
|
</code>end_compatibility</p></div></div><div class="top"><p class="src"><a name="v:isInf-39-" class="def">isInf'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:isNan" class="def">isNan</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Returns which elements of x are NaN.</p><p><code>compatibility(numpy)
|
|
Equivalent to np.isnan
|
|
</code>end_compatibility</p></div></div><div class="top"><p class="src"><a name="v:isNan-39-" class="def">isNan'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:isVariableInitialized" class="def">isVariableInitialized</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> dtype</td><td class="doc"><p><strong>ref</strong>: Should be from a <code>Variable</code> node. May be uninitialized.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>)</td><td class="doc"><p><strong>is_initialized</strong></p></td></tr></table></div><div class="doc"><p>Checks whether a tensor has been initialized.</p><p>Outputs boolean scalar indicating whether the tensor has been initialized.</p></div></div><div class="top"><p class="src"><a name="v:isVariableInitialized-39-" class="def">isVariableInitialized'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> dtype</td><td class="doc"><p><strong>ref</strong>: Should be from a <code>Variable</code> node. May be uninitialized.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>)</td><td class="doc"><p><strong>is_initialized</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:l2Loss" class="def">l2Loss</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>t</strong>: Typically 2-D, but may have any dimensions.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 0-D.</p></td></tr></table></div><div class="doc"><p>L2 Loss.</p><p>Computes half the L2 norm of a tensor without the <code><a href="../base-4.8.2.0/Prelude.html#v:sqrt">sqrt</a></code>:</p><p>output = sum(t ** 2) / 2</p></div></div><div class="top"><p class="src"><a name="v:l2Loss-39-" class="def">l2Loss'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>t</strong>: Typically 2-D, but may have any dimensions.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 0-D.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:lRN" class="def">lRN</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Local Response Normalization.</p><p>The 4-D <code>input</code> tensor is treated as a 3-D array of 1-D vectors (along the last
|
|
dimension), and each vector is normalized independently. Within a given vector,
|
|
each component is divided by the weighted, squared sum of inputs within
|
|
<code>depth_radius</code>. In detail,</p><p>sqr_sum[a, b, c, d] =
|
|
sum(input[a, b, c, d - depth_radius : d + depth_radius + 1] ** 2)
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|
output = input / (bias + alpha * sqr_sum) ** beta</p><p>For details, see <a href="http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks">Krizhevsky et al., ImageNet classification with deep
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|
convolutional neural networks (NIPS 2012)</a>.</p></div></div><div class="top"><p class="src"><a name="v:lRN-39-" class="def">lRN'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:lRNGrad" class="def">lRNGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input_grads</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>input_image</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>output_image</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The gradients for LRN.</p></td></tr></table></div><div class="doc"><p>Gradients for Local Response Normalization.</p></div></div><div class="top"><p class="src"><a name="v:lRNGrad-39-" class="def">lRNGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input_grads</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>input_image</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>output_image</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The gradients for LRN.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:learnedUnigramCandidateSampler" class="def">learnedUnigramCandidateSampler</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_sampled</strong>: Number of candidates to randomly sample per batch.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_true</strong>: Number of true labels per context.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>range_max</strong>: The sampler will sample integers from the interval [0, range_max).</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>unique</strong>: If unique is true, we sample with rejection, so that all sampled
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|
candidates in a batch are unique. This requires some approximation to
|
|
estimate the post-rejection sampling probabilities.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>true_classes</strong>: A batch_size * num_true matrix, in which each row contains the
|
|
IDs of the num_true target_classes in the corresponding original label.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>sampled_candidates</strong>, <strong>true_expected_count</strong>, <strong>sampled_expected_count</strong>)</p><ul><li><strong>sampled_candidates</strong>: A vector of length num_sampled, in which each element is
|
|
the ID of a sampled candidate.</li><li><strong>true_expected_count</strong>: A batch_size * num_true matrix, representing
|
|
the number of times each candidate is expected to occur in a batch
|
|
of sampled candidates. If unique=true, then this is a probability.</li><li><strong>sampled_expected_count</strong>: A vector of length num_sampled, for each sampled
|
|
candidate representing the number of times the candidate is expected
|
|
to occur in a batch of sampled candidates. If unique=true, then this is a
|
|
probability.</li></ul></td></tr></table></div><div class="doc"><p>Generates labels for candidate sampling with a learned unigram distribution.</p><p>See explanations of candidate sampling and the data formats at
|
|
go/candidate-sampling.</p><p>For each batch, this op picks a single set of sampled candidate labels.</p><p>The advantages of sampling candidates per-batch are simplicity and the
|
|
possibility of efficient dense matrix multiplication. The disadvantage is that
|
|
the sampled candidates must be chosen independently of the context and of the
|
|
true labels.</p></div></div><div class="top"><p class="src"><a name="v:learnedUnigramCandidateSampler-39-" class="def">learnedUnigramCandidateSampler'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_sampled</strong>: Number of candidates to randomly sample per batch.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_true</strong>: Number of true labels per context.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>range_max</strong>: The sampler will sample integers from the interval [0, range_max).</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>unique</strong>: If unique is true, we sample with rejection, so that all sampled
|
|
candidates in a batch are unique. This requires some approximation to
|
|
estimate the post-rejection sampling probabilities.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>true_classes</strong>: A batch_size * num_true matrix, in which each row contains the
|
|
IDs of the num_true target_classes in the corresponding original label.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>sampled_candidates</strong>, <strong>true_expected_count</strong>, <strong>sampled_expected_count</strong>)</p><ul><li><strong>sampled_candidates</strong>: A vector of length num_sampled, in which each element is
|
|
the ID of a sampled candidate.</li><li><strong>true_expected_count</strong>: A batch_size * num_true matrix, representing
|
|
the number of times each candidate is expected to occur in a batch
|
|
of sampled candidates. If unique=true, then this is a probability.</li><li><strong>sampled_expected_count</strong>: A vector of length num_sampled, for each sampled
|
|
candidate representing the number of times the candidate is expected
|
|
to occur in a batch of sampled candidates. If unique=true, then this is a
|
|
probability.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:less" class="def">less</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns the truth value of (x < y) element-wise.</p><ul><li>NOTE*: <code>Less</code> supports broadcasting. More about broadcasting
|
|
<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:less-39-" class="def">less'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:lessEqual" class="def">lessEqual</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns the truth value of (x <= y) element-wise.</p><ul><li>NOTE*: <code>LessEqual</code> supports broadcasting. More about broadcasting
|
|
<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:lessEqual-39-" class="def">lessEqual'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:lgamma" class="def">lgamma</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes the log of the absolute value of `Gamma(x)` element-wise.</p></div></div><div class="top"><p class="src"><a name="v:lgamma-39-" class="def">lgamma'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:linSpace" class="def">linSpace</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>start</strong>: First entry in the range.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>stop</strong>: Last entry in the range.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tidx</td><td class="doc"><p><strong>num</strong>: Number of values to generate.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 1-D. The generated values.</p></td></tr></table></div><div class="doc"><p>Generates values in an interval.</p><p>A sequence of <code>num</code> evenly-spaced values are generated beginning at <code>start</code>.
|
|
If `num > 1`, the values in the sequence increase by `stop - start / num - 1`,
|
|
so that the last one is exactly <code>stop</code>.</p><p>For example:</p><p>```
|
|
tf.linspace(10.0, 12.0, 3, name="linspace") => [ 10.0 11.0 12.0]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:linSpace-39-" class="def">linSpace'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>start</strong>: First entry in the range.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>stop</strong>: Last entry in the range.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tidx</td><td class="doc"><p><strong>num</strong>: Number of values to generate.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 1-D. The generated values.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:listDiff" class="def">listDiff</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_idx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong>: 1-D. Values to keep.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong>: 1-D. Values to remove.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_idx)</td><td class="doc"><p>(<strong>out</strong>, <strong>idx</strong>)</p><ul><li><strong>out</strong>: 1-D. Values present in <code>x</code> but not in <code>y</code>.</li><li><strong>idx</strong>: 1-D. Positions of <code>x</code> values preserved in <code>out</code>.</li></ul></td></tr></table></div><div class="doc"><p>Computes the difference between two lists of numbers or strings.</p><p>Given a list <code>x</code> and a list <code>y</code>, this operation returns a list <code>out</code> that
|
|
represents all values that are in <code>x</code> but not in <code>y</code>. The returned list <code>out</code>
|
|
is sorted in the same order that the numbers appear in <code>x</code> (duplicates are
|
|
preserved). This operation also returns a list <code>idx</code> that represents the
|
|
position of each <code>out</code> element in <code>x</code>. In other words:</p><p>`out[i] = x[idx[i]] for i in [0, 1, ..., len(out) - 1]`</p><p>For example, given this input:</p><p>```prettyprint
|
|
x = [1, 2, 3, 4, 5, 6]
|
|
y = [1, 3, 5]
|
|
```</p><p>This operation would return:</p><p>```prettyprint
|
|
out ==> [2, 4, 6]
|
|
idx ==> [1, 3, 5]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:listDiff-39-" class="def">listDiff'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_idx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong>: 1-D. Values to keep.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong>: 1-D. Values to remove.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_idx)</td><td class="doc"><p>(<strong>out</strong>, <strong>idx</strong>)</p><ul><li><strong>out</strong>: 1-D. Values present in <code>x</code> but not in <code>y</code>.</li><li><strong>idx</strong>: 1-D. Positions of <code>x</code> values preserved in <code>out</code>.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:log" class="def">log</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes natural logarithm of x element-wise.</p><p>I.e., \(y = log_e x\).</p></div></div><div class="top"><p class="src"><a name="v:log-39-" class="def">log'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:log1p" class="def">log1p</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes natural logarithm of (1 + x) element-wise.</p><p>I.e., \(y = log_e (1 + x)\).</p></div></div><div class="top"><p class="src"><a name="v:log1p-39-" class="def">log1p'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:logSoftmax" class="def">logSoftmax</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>logits</strong>: 2-D with shape `[batch_size, num_classes]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>logsoftmax</strong>: Same shape as <code>logits</code>.</p></td></tr></table></div><div class="doc"><p>Computes log softmax activations.</p><p>For each batch <code>i</code> and class <code>j</code> we have</p><p>logsoftmax[i, j] = logits[i, j] - log(sum(exp(logits[i])))</p></div></div><div class="top"><p class="src"><a name="v:logSoftmax-39-" class="def">logSoftmax'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>logits</strong>: 2-D with shape `[batch_size, num_classes]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>logsoftmax</strong>: Same shape as <code>logits</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:logUniformCandidateSampler" class="def">logUniformCandidateSampler</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_sampled</strong>: Number of candidates to randomly sample per batch.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_true</strong>: Number of true labels per context.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>range_max</strong>: The sampler will sample integers from the interval [0, range_max).</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>unique</strong>: If unique is true, we sample with rejection, so that all sampled
|
|
candidates in a batch are unique. This requires some approximation to
|
|
estimate the post-rejection sampling probabilities.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>true_classes</strong>: A batch_size * num_true matrix, in which each row contains the
|
|
IDs of the num_true target_classes in the corresponding original label.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>sampled_candidates</strong>, <strong>true_expected_count</strong>, <strong>sampled_expected_count</strong>)</p><ul><li><strong>sampled_candidates</strong>: A vector of length num_sampled, in which each element is
|
|
the ID of a sampled candidate.</li><li><strong>true_expected_count</strong>: A batch_size * num_true matrix, representing
|
|
the number of times each candidate is expected to occur in a batch
|
|
of sampled candidates. If unique=true, then this is a probability.</li><li><strong>sampled_expected_count</strong>: A vector of length num_sampled, for each sampled
|
|
candidate representing the number of times the candidate is expected
|
|
to occur in a batch of sampled candidates. If unique=true, then this is a
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probability.</li></ul></td></tr></table></div><div class="doc"><p>Generates labels for candidate sampling with a log-uniform distribution.</p><p>See explanations of candidate sampling and the data formats at
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go/candidate-sampling.</p><p>For each batch, this op picks a single set of sampled candidate labels.</p><p>The advantages of sampling candidates per-batch are simplicity and the
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possibility of efficient dense matrix multiplication. The disadvantage is that
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the sampled candidates must be chosen independently of the context and of the
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|
true labels.</p></div></div><div class="top"><p class="src"><a name="v:logUniformCandidateSampler-39-" class="def">logUniformCandidateSampler'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_sampled</strong>: Number of candidates to randomly sample per batch.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_true</strong>: Number of true labels per context.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>range_max</strong>: The sampler will sample integers from the interval [0, range_max).</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>unique</strong>: If unique is true, we sample with rejection, so that all sampled
|
|
candidates in a batch are unique. This requires some approximation to
|
|
estimate the post-rejection sampling probabilities.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>true_classes</strong>: A batch_size * num_true matrix, in which each row contains the
|
|
IDs of the num_true target_classes in the corresponding original label.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>sampled_candidates</strong>, <strong>true_expected_count</strong>, <strong>sampled_expected_count</strong>)</p><ul><li><strong>sampled_candidates</strong>: A vector of length num_sampled, in which each element is
|
|
the ID of a sampled candidate.</li><li><strong>true_expected_count</strong>: A batch_size * num_true matrix, representing
|
|
the number of times each candidate is expected to occur in a batch
|
|
of sampled candidates. If unique=true, then this is a probability.</li><li><strong>sampled_expected_count</strong>: A vector of length num_sampled, for each sampled
|
|
candidate representing the number of times the candidate is expected
|
|
to occur in a batch of sampled candidates. If unique=true, then this is a
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probability.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:logicalAnd" class="def">logicalAnd</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns the truth value of x AND y element-wise.</p><ul><li>NOTE*: <code>LogicalAnd</code> supports broadcasting. More about broadcasting
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<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:logicalAnd-39-" class="def">logicalAnd'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:logicalNot" class="def">logicalNot</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Returns the truth value of NOT x element-wise.</p></div></div><div class="top"><p class="src"><a name="v:logicalNot-39-" class="def">logicalNot'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:logicalOr" class="def">logicalOr</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns the truth value of x OR y element-wise.</p><ul><li>NOTE*: <code>LogicalOr</code> supports broadcasting. More about broadcasting
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<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:logicalOr-39-" class="def">logicalOr'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:lookupTableExport" class="def">lookupTableExport</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tkeys, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tvalues)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>table_handle</strong>: Handle to the table.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tkeys, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tvalues)</td><td class="doc"><p>(<strong>keys</strong>, <strong>values</strong>)</p><ul><li><strong>keys</strong>: Vector of all keys present in the table.</li><li><strong>values</strong>: Tensor of all values in the table. Indexed in parallel with <code>keys</code>.</li></ul></td></tr></table></div><div class="doc"><p>Outputs all keys and values in the table.</p></div></div><div class="top"><p class="src"><a name="v:lookupTableExport-39-" class="def">lookupTableExport'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tkeys, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tvalues)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>table_handle</strong>: Handle to the table.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tkeys, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tvalues)</td><td class="doc"><p>(<strong>keys</strong>, <strong>values</strong>)</p><ul><li><strong>keys</strong>: Vector of all keys present in the table.</li><li><strong>values</strong>: Tensor of all values in the table. Indexed in parallel with <code>keys</code>.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:lookupTableFind" class="def">lookupTableFind</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tin, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tout)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>table_handle</strong>: Handle to the table.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tin</td><td class="doc"><p><strong>keys</strong>: Any shape. Keys to look up.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tout</td><td class="doc"><p><strong>default_value</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tout)</td><td class="doc"><p><strong>values</strong>: Same shape as <code>keys</code>. Values found in the table, or <code>default_values</code>
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for missing keys.</p></td></tr></table></div><div class="doc"><p>Looks up keys in a table, outputs the corresponding values.</p><p>The tensor <code>keys</code> must of the same type as the keys of the table.
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The output <code>values</code> is of the type of the table values.</p><p>The scalar <code>default_value</code> is the value output for keys not present in the
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table. It must also be of the same type as the table values.</p></div></div><div class="top"><p class="src"><a name="v:lookupTableFind-39-" class="def">lookupTableFind'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tin, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tout)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>table_handle</strong>: Handle to the table.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tin</td><td class="doc"><p><strong>keys</strong>: Any shape. Keys to look up.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tout</td><td class="doc"><p><strong>default_value</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tout)</td><td class="doc"><p><strong>values</strong>: Same shape as <code>keys</code>. Values found in the table, or <code>default_values</code>
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for missing keys.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:lookupTableImport" class="def">lookupTableImport</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tin, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tout)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>table_handle</strong>: Handle to the table.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tin</td><td class="doc"><p><strong>keys</strong>: Any shape. Keys to look up.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tout</td><td class="doc"><p><strong>values</strong>: Values to associate with keys.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Replaces the contents of the table with the specified keys and values.</p><p>The tensor <code>keys</code> must be of the same type as the keys of the table.
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The tensor <code>values</code> must be of the type of the table values.</p></div></div><div class="top"><p class="src"><a name="v:lookupTableImport-39-" class="def">lookupTableImport'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tin, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tout)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>table_handle</strong>: Handle to the table.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tin</td><td class="doc"><p><strong>keys</strong>: Any shape. Keys to look up.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tout</td><td class="doc"><p><strong>values</strong>: Values to associate with keys.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:lookupTableInsert" class="def">lookupTableInsert</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tin, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tout)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>table_handle</strong>: Handle to the table.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tin</td><td class="doc"><p><strong>keys</strong>: Any shape. Keys to look up.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tout</td><td class="doc"><p><strong>values</strong>: Values to associate with keys.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Updates the table to associates keys with values.</p><p>The tensor <code>keys</code> must be of the same type as the keys of the table.
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The tensor <code>values</code> must be of the type of the table values.</p></div></div><div class="top"><p class="src"><a name="v:lookupTableInsert-39-" class="def">lookupTableInsert'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tin, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tout)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>table_handle</strong>: Handle to the table.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tin</td><td class="doc"><p><strong>keys</strong>: Any shape. Keys to look up.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tout</td><td class="doc"><p><strong>values</strong>: Values to associate with keys.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:lookupTableSize" class="def">lookupTableSize</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>table_handle</strong>: Handle to the table.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p><strong>size</strong>: Scalar that contains number of elements in the table.</p></td></tr></table></div><div class="doc"><p>Computes the number of elements in the given table.</p></div></div><div class="top"><p class="src"><a name="v:lookupTableSize-39-" class="def">lookupTableSize'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>table_handle</strong>: Handle to the table.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p><strong>size</strong>: Scalar that contains number of elements in the table.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:loopCond" class="def">loopCond</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>input</strong>: A boolean scalar, representing the branch predicate of the Switch op.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>output</strong>: The same tensor as <code>input</code>.</p></td></tr></table></div><div class="doc"><p>Forwards the input to the output.</p><p>This operator represents the loop termination condition used by the
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"pivot" switches of a loop.</p></div></div><div class="top"><p class="src"><a name="v:loopCond-39-" class="def">loopCond'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>input</strong>: A boolean scalar, representing the branch predicate of the Switch op.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>output</strong>: The same tensor as <code>input</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:matMul" class="def">matMul</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>a</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>b</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>product</strong></p></td></tr></table></div><div class="doc"><p>Multiply the matrix "a" by the matrix "b".</p><p>The inputs must be two-dimensional matrices and the inner dimension of
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"a" (after being transposed if transpose_a is true) must match the
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outer dimension of "b" (after being transposed if transposed_b is
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true).</p><ul><li>Note*: The default kernel implementation for MatMul on GPUs uses
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cublas.</li></ul></div></div><div class="top"><p class="src"><a name="v:matMul-39-" class="def">matMul'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>a</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>b</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>product</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:matchingFiles" class="def">matchingFiles</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>pattern</strong>: A (scalar) shell wildcard pattern.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>filenames</strong>: A vector of matching filenames.</p></td></tr></table></div><div class="doc"><p>Returns the set of files matching a pattern.</p><p>Note that this routine only supports wildcard characters in the
|
|
basename portion of the pattern, not in the directory portion.</p></div></div><div class="top"><p class="src"><a name="v:matchingFiles-39-" class="def">matchingFiles'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>pattern</strong>: A (scalar) shell wildcard pattern.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>filenames</strong>: A vector of matching filenames.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:matrixBandPart" class="def">matrixBandPart</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Rank <code>k</code> tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_lower</strong>: 0-D tensor. Number of subdiagonals to keep. If negative, keep entire
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|
lower triangle.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_upper</strong>: 0-D tensor. Number of superdiagonals to keep. If negative, keep
|
|
entire upper triangle.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>band</strong>: Rank <code>k</code> tensor of the same shape as input. The extracted banded tensor.</p></td></tr></table></div><div class="doc"><p>Copy a tensor setting everything outside a central band in each innermost matrix</p><p>to zero.</p><p>The <code>band</code> part is computed as follows:
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|
Assume <code>input</code> has <code>k</code> dimensions `[I, J, K, ..., M, N]`, then the output is a
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|
tensor with the same shape where</p><p>`band[i, j, k, ..., m, n] = in_band(m, n) * input[i, j, k, ..., m, n]`.</p><p>The indicator function</p><p>`in_band(m, n) = (num_lower < 0 || (m-n) <= num_lower)) &&
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|
(num_upper < 0 || (n-m) <= num_upper)`.</p><p>For example:</p><p>```prettyprint
|
|
# if <code>input</code> is [[ 0, 1, 2, 3]
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|
[-1, 0, 1, 2]
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|
[-2, -1, 0, 1]
|
|
[-3, -2, -1, 0]],</p><p>tf.matrix_band_part(input, 1, -1) ==> [[ 0, 1, 2, 3]
|
|
[-1, 0, 1, 2]
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|
[ 0, -1, 0, 1]
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|
[ 0, 0, -1, 0]],</p><p>tf.matrix_band_part(input, 2, 1) ==> [[ 0, 1, 0, 0]
|
|
[-1, 0, 1, 0]
|
|
[-2, -1, 0, 1]
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|
[ 0, -2, -1, 0]]
|
|
```</p><p>Useful special cases:</p><p>```prettyprint
|
|
tf.matrix_band_part(input, 0, -1) ==> Upper triangular part.
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|
tf.matrix_band_part(input, -1, 0) ==> Lower triangular part.
|
|
tf.matrix_band_part(input, 0, 0) ==> Diagonal.
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:matrixBandPart-39-" class="def">matrixBandPart'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Rank <code>k</code> tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_lower</strong>: 0-D tensor. Number of subdiagonals to keep. If negative, keep entire
|
|
lower triangle.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_upper</strong>: 0-D tensor. Number of superdiagonals to keep. If negative, keep
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|
entire upper triangle.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>band</strong>: Rank <code>k</code> tensor of the same shape as input. The extracted banded tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:matrixDeterminant" class="def">matrixDeterminant</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape is `[..., M, M]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Shape is `[...]`.</p></td></tr></table></div><div class="doc"><p>Computes the determinant of one ore more square matrices.</p><p>The input is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions
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form square matrices. The output is a tensor containing the determinants
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|
for all input submatrices `[..., :, :]`.</p></div></div><div class="top"><p class="src"><a name="v:matrixDeterminant-39-" class="def">matrixDeterminant'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape is `[..., M, M]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Shape is `[...]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:matrixDiag" class="def">matrixDiag</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>diagonal</strong>: Rank <code>k</code>, where `k >= 1`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Rank `k+1`, with `output.shape = diagonal.shape + [diagonal.shape[-1]]`.</p></td></tr></table></div><div class="doc"><p>Returns a batched diagonal tensor with a given batched diagonal values.</p><p>Given a <code>diagonal</code>, this operation returns a tensor with the <code>diagonal</code> and
|
|
everything else padded with zeros. The diagonal is computed as follows:</p><p>Assume <code>diagonal</code> has <code>k</code> dimensions `[I, J, K, ..., N]`, then the output is a
|
|
tensor of rank `k+1` with dimensions [I, J, K, ..., N, N]` where:</p><p>`output[i, j, k, ..., m, n] = 1{m=n} * diagonal[i, j, k, ..., n]`.</p><p>For example:</p><p>```prettyprint
|
|
# <code>diagonal</code> is [[1, 2, 3, 4], [5, 6, 7, 8]]</p><p>and diagonal.shape = (2, 4)</p><p>tf.matrix_diag(diagonal) ==> [[[1, 0, 0, 0]
|
|
[0, 2, 0, 0]
|
|
[0, 0, 3, 0]
|
|
[0, 0, 0, 4]],
|
|
[[5, 0, 0, 0]
|
|
[0, 6, 0, 0]
|
|
[0, 0, 7, 0]
|
|
[0, 0, 0, 8]]]</p><p>which has shape (2, 4, 4)
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:matrixDiag-39-" class="def">matrixDiag'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>diagonal</strong>: Rank <code>k</code>, where `k >= 1`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Rank `k+1`, with `output.shape = diagonal.shape + [diagonal.shape[-1]]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:matrixDiagPart" class="def">matrixDiagPart</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Rank <code>k</code> tensor where `k >= 2`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>diagonal</strong>: The extracted diagonal(s) having shape
|
|
`diagonal.shape = input.shape[:-2] + [min(input.shape[-2:])]`.</p></td></tr></table></div><div class="doc"><p>Returns the batched diagonal part of a batched tensor.</p><p>This operation returns a tensor with the <code>diagonal</code> part
|
|
of the batched <code>input</code>. The <code>diagonal</code> part is computed as follows:</p><p>Assume <code>input</code> has <code>k</code> dimensions `[I, J, K, ..., M, N]`, then the output is a
|
|
tensor of rank `k - 1` with dimensions `[I, J, K, ..., min(M, N)]` where:</p><p>`diagonal[i, j, k, ..., n] = input[i, j, k, ..., n, n]`.</p><p>The input must be at least a matrix.</p><p>For example:</p><p>```prettyprint
|
|
# <code>input</code> is [[[1, 0, 0, 0]
|
|
[0, 2, 0, 0]
|
|
[0, 0, 3, 0]
|
|
[0, 0, 0, 4]],
|
|
[[5, 0, 0, 0]
|
|
[0, 6, 0, 0]
|
|
[0, 0, 7, 0]
|
|
[0, 0, 0, 8]]]</p><p>and input.shape = (2, 4, 4)</p><p>tf.matrix_diag_part(input) ==> [[1, 2, 3, 4], [5, 6, 7, 8]]</p><p>which has shape (2, 4)
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:matrixDiagPart-39-" class="def">matrixDiagPart'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Rank <code>k</code> tensor where `k >= 2`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>diagonal</strong>: The extracted diagonal(s) having shape
|
|
`diagonal.shape = input.shape[:-2] + [min(input.shape[-2:])]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:matrixInverse" class="def">matrixInverse</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape is `[..., M, M]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Shape is `[..., M, M]`.</p><p><code>compatibility(numpy)
|
|
Equivalent to np.linalg.inv
|
|
</code>end_compatibility</p></td></tr></table></div><div class="doc"><p>Computes the inverse of one or more square invertible matrices or their</p><p>adjoints (conjugate transposes).</p><p>The input is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions
|
|
form square matrices. The output is a tensor of the same shape as the input
|
|
containing the inverse for all input submatrices `[..., :, :]`.</p><p>The op uses LU decomposition with partial pivoting to compute the inverses.</p><p>If a matrix is not invertible there is no guarantee what the op does. It
|
|
may detect the condition and raise an exception or it may simply return a
|
|
garbage result.</p></div></div><div class="top"><p class="src"><a name="v:matrixInverse-39-" class="def">matrixInverse'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape is `[..., M, M]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Shape is `[..., M, M]`.</p><p><code>compatibility(numpy)
|
|
Equivalent to np.linalg.inv
|
|
</code>end_compatibility</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:matrixSetDiag" class="def">matrixSetDiag</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Rank `k+1`, where `k >= 1`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>diagonal</strong>: Rank <code>k</code>, where `k >= 1`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Rank `k+1`, with `output.shape = input.shape`.</p></td></tr></table></div><div class="doc"><p>Returns a batched matrix tensor with new batched diagonal values.</p><p>Given <code>input</code> and <code>diagonal</code>, this operation returns a tensor with the
|
|
same shape and values as <code>input</code>, except for the main diagonal of the
|
|
innermost matrices. These will be overwritten by the values in <code>diagonal</code>.</p><p>The output is computed as follows:</p><p>Assume <code>input</code> has `k+1` dimensions `[I, J, K, ..., M, N]` and <code>diagonal</code> has
|
|
<code>k</code> dimensions `[I, J, K, ..., min(M, N)]`. Then the output is a
|
|
tensor of rank `k+1` with dimensions `[I, J, K, ..., M, N]` where:</p><ul><li>`output[i, j, k, ..., m, n] = diagonal[i, j, k, ..., n]` for `m == n`.</li><li>`output[i, j, k, ..., m, n] = input[i, j, k, ..., m, n]` for `m != n`.</li></ul></div></div><div class="top"><p class="src"><a name="v:matrixSetDiag-39-" class="def">matrixSetDiag'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Rank `k+1`, where `k >= 1`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>diagonal</strong>: Rank <code>k</code>, where `k >= 1`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Rank `k+1`, with `output.shape = input.shape`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:matrixSolve" class="def">matrixSolve</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>matrix</strong>: Shape is `[..., M, M]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>rhs</strong>: Shape is `[..., M, K]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Shape is `[..., M, K]`.</p></td></tr></table></div><div class="doc"><p>Solves systems of linear equations.</p><p><code>Matrix</code> is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions
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form square matrices. <code>Rhs</code> is a tensor of shape `[..., M, K]`. The <code>output</code> is
|
|
a tensor shape `[..., M, K]`. If <code>adjoint</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:False">False</a></code> then each output matrix
|
|
satisfies `matrix[..., :, :] * output[..., :, :] = rhs[..., :, :]`.
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If <code>adjoint</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code> then each output matrix satisfies
|
|
`adjoint(matrix[..., :, :]) * output[..., :, :] = rhs[..., :, :]`.</p></div></div><div class="top"><p class="src"><a name="v:matrixSolve-39-" class="def">matrixSolve'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>matrix</strong>: Shape is `[..., M, M]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>rhs</strong>: Shape is `[..., M, K]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Shape is `[..., M, K]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:matrixSolveLs" class="def">matrixSolveLs</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>matrix</strong>: Shape is `[..., M, N]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>rhs</strong>: Shape is `[..., M, K]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a></td><td class="doc"><p><strong>l2_regularizer</strong>: Scalar tensor.</p><p><code>compatibility(numpy)
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Equivalent to np.linalg.lstsq
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|
</code>end_compatibility</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Shape is `[..., N, K]`.</p></td></tr></table></div><div class="doc"><p>Solves one or more linear least-squares problems.</p><p><code>matrix</code> is a tensor of shape `[..., M, N]` whose inner-most 2 dimensions
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form matrices of size `[M, N]`. Rhs is a tensor of shape `[..., M, K]`.
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|
The output is a tensor shape `[..., N, K]` where each output matrix solves
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|
each of the equations matrix[..., :, :] * output[..., :, :] = rhs[..., :, :]
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in the least squares sense.</p><p>matrix and right-hand sides in the batch:</p><p><code>matrix</code>=\(A in Re^{m times n}\),
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|
<code>rhs</code>=\(B in Re^{m times k}\),
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|
<code>output</code>=\(X in Re^{n times k}\),
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|
<code>l2_regularizer</code>=\(lambda\).</p><p>If <code>fast</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code>, then the solution is computed by solving the normal
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|
equations using Cholesky decomposition. Specifically, if \(m ge n\) then
|
|
\(X = (A^T A + lambda I)^{-1} A^T B\), which solves the least-squares
|
|
problem \(X = mathrm{argmin}_{Z in Re^{n times k} } ||A Z - B||_F^2 +
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|
lambda ||Z||_F^2\). If \(m lt n\) then <code>output</code> is computed as
|
|
\(X = A^T (A A^T + lambda I)^{-1} B\), which (for \(lambda = 0\)) is the
|
|
minimum-norm solution to the under-determined linear system, i.e.
|
|
\(X = mathrm{argmin}_{Z in Re^{n times k} } ||Z||_F^2 \), subject to
|
|
\(A Z = B\). Notice that the fast path is only numerically stable when
|
|
\(A\) is numerically full rank and has a condition number
|
|
\(mathrm{cond}(A) lt frac{1}{sqrt{epsilon_{mach} } }\) or\(lambda\) is
|
|
sufficiently large.</p><p>If <code>fast</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:False">False</a></code> an algorithm based on the numerically robust complete
|
|
orthogonal decomposition is used. This computes the minimum-norm
|
|
least-squares solution, even when \(A\) is rank deficient. This path is
|
|
typically 6-7 times slower than the fast path. If <code>fast</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:False">False</a></code> then
|
|
<code>l2_regularizer</code> is ignored.</p></div></div><div class="top"><p class="src"><a name="v:matrixSolveLs-39-" class="def">matrixSolveLs'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>matrix</strong>: Shape is `[..., M, N]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>rhs</strong>: Shape is `[..., M, K]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a></td><td class="doc"><p><strong>l2_regularizer</strong>: Scalar tensor.</p><p><code>compatibility(numpy)
|
|
Equivalent to np.linalg.lstsq
|
|
</code>end_compatibility</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Shape is `[..., N, K]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:matrixTriangularSolve" class="def">matrixTriangularSolve</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>matrix</strong>: Shape is `[..., M, M]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>rhs</strong>: Shape is `[..., M, K]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Shape is `[..., M, K]`.</p></td></tr></table></div><div class="doc"><p>Solves systems of linear equations with upper or lower triangular matrices by</p><p>backsubstitution.</p><p><code>matrix</code> is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions form
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square matrices. If <code>lower</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code> then the strictly upper triangular part
|
|
of each inner-most matrix is assumed to be zero and not accessed.
|
|
If <code>lower</code> is False then the strictly lower triangular part of each inner-most
|
|
matrix is assumed to be zero and not accessed.
|
|
<code>rhs</code> is a tensor of shape `[..., M, K]`.</p><p>The output is a tensor of shape `[..., M, K]`. If <code>adjoint</code> is
|
|
<code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code> then the innermost matrices in output` satisfy matrix equations
|
|
`matrix[..., :, :] * output[..., :, :] = rhs[..., :, :]`.
|
|
If <code>adjoint</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:False">False</a></code> then the strictly then the innermost matrices in
|
|
<code>output</code> satisfy matrix equations
|
|
`adjoint(matrix[..., i, k]) * output[..., k, j] = rhs[..., i, j]`.</p></div></div><div class="top"><p class="src"><a name="v:matrixTriangularSolve-39-" class="def">matrixTriangularSolve'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>matrix</strong>: Shape is `[..., M, M]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>rhs</strong>: Shape is `[..., M, K]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Shape is `[..., M, K]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:max" class="def">max</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The tensor to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>reduction_indices</strong>: The dimensions to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The reduced tensor.</p></td></tr></table></div><div class="doc"><p>Computes the maximum of elements across dimensions of a tensor.</p><p>Reduces <code>input</code> along the dimensions given in <code>reduction_indices</code>. Unless
|
|
<code>keep_dims</code> is true, the rank of the tensor is reduced by 1 for each entry in
|
|
<code>reduction_indices</code>. If <code>keep_dims</code> is true, the reduced dimensions are
|
|
retained with length 1.</p></div></div><div class="top"><p class="src"><a name="v:max-39-" class="def">max'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The tensor to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>reduction_indices</strong>: The dimensions to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The reduced tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:maxPool" class="def">maxPool</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D input to pool over.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The max pooled output tensor.</p></td></tr></table></div><div class="doc"><p>Performs max pooling on the input.</p></div></div><div class="top"><p class="src"><a name="v:maxPool-39-" class="def">maxPool'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D input to pool over.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The max pooled output tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:maxPool3D" class="def">maxPool3D</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape `[batch, depth, rows, cols, channels]` tensor to pool over.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The max pooled output tensor.</p></td></tr></table></div><div class="doc"><p>Performs 3D max pooling on the input.</p></div></div><div class="top"><p class="src"><a name="v:maxPool3D-39-" class="def">maxPool3D'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape `[batch, depth, rows, cols, channels]` tensor to pool over.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The max pooled output tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:maxPool3DGrad" class="def">maxPool3DGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>orig_input</strong>: The original input tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>orig_output</strong>: The original output tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>grad</strong>: Output backprop of shape `[batch, depth, rows, cols, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Computes gradients of max pooling function.</p></div></div><div class="top"><p class="src"><a name="v:maxPool3DGrad-39-" class="def">maxPool3DGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>orig_input</strong>: The original input tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>orig_output</strong>: The original output tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>grad</strong>: Output backprop of shape `[batch, depth, rows, cols, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:maxPoolGrad" class="def">maxPoolGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>orig_input</strong>: The original input tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>orig_output</strong>: The original output tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>grad</strong>: 4-D. Gradients w.r.t. the output of <code>max_pool</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Gradients w.r.t. the input to <code>max_pool</code>.</p></td></tr></table></div><div class="doc"><p>Computes gradients of the maxpooling function.</p></div></div><div class="top"><p class="src"><a name="v:maxPoolGrad-39-" class="def">maxPoolGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>orig_input</strong>: The original input tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>orig_output</strong>: The original output tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>grad</strong>: 4-D. Gradients w.r.t. the output of <code>max_pool</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Gradients w.r.t. the input to <code>max_pool</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:maxPoolGradWithArgmax" class="def">maxPoolGradWithArgmax</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` targmax, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The original input.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>grad</strong>: 4-D with shape `[batch, height, width, channels]`. Gradients w.r.t. the
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output of <code>max_pool</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 targmax</td><td class="doc"><p><strong>argmax</strong>: The indices of the maximum values chosen for each output of <code>max_pool</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Gradients w.r.t. the input of <code>max_pool</code>.</p></td></tr></table></div><div class="doc"><p>Computes gradients of the maxpooling function.</p></div></div><div class="top"><p class="src"><a name="v:maxPoolGradWithArgmax-39-" class="def">maxPoolGradWithArgmax'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` targmax, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The original input.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>grad</strong>: 4-D with shape `[batch, height, width, channels]`. Gradients w.r.t. the
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output of <code>max_pool</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 targmax</td><td class="doc"><p><strong>argmax</strong>: The indices of the maximum values chosen for each output of <code>max_pool</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Gradients w.r.t. the input of <code>max_pool</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:maxPoolWithArgmax" class="def">maxPoolWithArgmax</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` targmax, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, height, width, channels]`. Input to pool over.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> targmax)</td><td class="doc"><p>(<strong>output</strong>, <strong>argmax</strong>)</p><ul><li><strong>output</strong>: The max pooled output tensor.</li><li><strong>argmax</strong>: 4-D. The flattened indices of the max values chosen for each output.</li></ul></td></tr></table></div><div class="doc"><p>Performs max pooling on the input and outputs both max values and indices.</p><p>The indices in <code>argmax</code> are flattened, so that a maximum value at position
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`[b, y, x, c]` becomes flattened index
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`((b * height + y) * width + x) * channels + c`.</p></div></div><div class="top"><p class="src"><a name="v:maxPoolWithArgmax-39-" class="def">maxPoolWithArgmax'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` targmax, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, height, width, channels]`. Input to pool over.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> targmax)</td><td class="doc"><p>(<strong>output</strong>, <strong>argmax</strong>)</p><ul><li><strong>output</strong>: The max pooled output tensor.</li><li><strong>argmax</strong>: 4-D. The flattened indices of the max values chosen for each output.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:maximum" class="def">maximum</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns the max of x and y (i.e. x > y ? x : y) element-wise.</p><ul><li>NOTE*: <code>Maximum</code> supports broadcasting. More about broadcasting
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<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:maximum-39-" class="def">maximum'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:mean" class="def">mean</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The tensor to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>reduction_indices</strong>: The dimensions to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The reduced tensor.</p></td></tr></table></div><div class="doc"><p>Computes the mean of elements across dimensions of a tensor.</p><p>Reduces <code>input</code> along the dimensions given in <code>reduction_indices</code>. Unless
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<code>keep_dims</code> is true, the rank of the tensor is reduced by 1 for each entry in
|
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<code>reduction_indices</code>. If <code>keep_dims</code> is true, the reduced dimensions are
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retained with length 1.</p></div></div><div class="top"><p class="src"><a name="v:mean-39-" class="def">mean'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The tensor to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>reduction_indices</strong>: The dimensions to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The reduced tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:merge" class="def">merge</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t]</td><td class="doc"><p><strong>inputs</strong>: The input tensors, exactly one of which will become available.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>value_index</strong>)</p><ul><li><strong>output</strong>: Will be set to the available input tensor.</li><li><strong>value_index</strong>: The index of the chosen input tensor in <code>inputs</code>.</li></ul></td></tr></table></div><div class="doc"><p>Forwards the value of an available tensor from <code>inputs</code> to <code>output</code>.</p><p><code>Merge</code> waits for at least one of the tensors in <code>inputs</code> to become available.
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It is usually combined with <code>Switch</code> to implement branching.</p><p><code>Merge</code> forwards the first tensor for become available to <code>output</code>, and sets
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<code>value_index</code> to its index in <code>inputs</code>.</p></div></div><div class="top"><p class="src"><a name="v:merge-39-" class="def">merge'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t]</td><td class="doc"><p><strong>inputs</strong>: The input tensors, exactly one of which will become available.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>value_index</strong>)</p><ul><li><strong>output</strong>: Will be set to the available input tensor.</li><li><strong>value_index</strong>: The index of the chosen input tensor in <code>inputs</code>.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:mergeSummary" class="def">mergeSummary</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>]</td><td class="doc"><p><strong>inputs</strong>: Can be of any shape. Each must contain serialized <code>Summary</code> protocol
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buffers.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>summary</strong>: Scalar. Serialized <code>Summary</code> protocol buffer.</p></td></tr></table></div><div class="doc"><p>Merges summaries.</p><p>This op creates a
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<a href="https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto">`Summary`</a>
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protocol buffer that contains the union of all the values in the input
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summaries.</p><p>When the Op is run, it reports an <code>InvalidArgument</code> error if multiple values
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in the summaries to merge use the same tag.</p></div></div><div class="top"><p class="src"><a name="v:mergeSummary-39-" class="def">mergeSummary'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>]</td><td class="doc"><p><strong>inputs</strong>: Can be of any shape. Each must contain serialized <code>Summary</code> protocol
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|
buffers.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>summary</strong>: Scalar. Serialized <code>Summary</code> protocol buffer.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:mergeV2Checkpoints" class="def">mergeV2Checkpoints</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>checkpoint_prefixes</strong>: prefixes of V2 checkpoints to merge.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>destination_prefix</strong>: scalar. The desired final prefix. Allowed to be the same
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as one of the checkpoint_prefixes.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>V2 format specific: merges the metadata files of sharded checkpoints. The</p><p>result is one logical checkpoint, with one physical metadata file and renamed
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data files.</p><p>Intended for "grouping" multiple checkpoints in a sharded checkpoint setup.</p><p>If delete_old_dirs is true, attempts to delete recursively the dirname of each
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path in the input checkpoint_prefixes. This is useful when those paths are non
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user-facing temporary locations.</p></div></div><div class="top"><p class="src"><a name="v:mergeV2Checkpoints-39-" class="def">mergeV2Checkpoints'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>checkpoint_prefixes</strong>: prefixes of V2 checkpoints to merge.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>destination_prefix</strong>: scalar. The desired final prefix. Allowed to be the same
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|
as one of the checkpoint_prefixes.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:min" class="def">min</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The tensor to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>reduction_indices</strong>: The dimensions to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The reduced tensor.</p></td></tr></table></div><div class="doc"><p>Computes the minimum of elements across dimensions of a tensor.</p><p>Reduces <code>input</code> along the dimensions given in <code>reduction_indices</code>. Unless
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|
<code>keep_dims</code> is true, the rank of the tensor is reduced by 1 for each entry in
|
|
<code>reduction_indices</code>. If <code>keep_dims</code> is true, the reduced dimensions are
|
|
retained with length 1.</p></div></div><div class="top"><p class="src"><a name="v:min-39-" class="def">min'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The tensor to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>reduction_indices</strong>: The dimensions to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The reduced tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:minimum" class="def">minimum</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns the min of x and y (i.e. x < y ? x : y) element-wise.</p><ul><li>NOTE*: <code>Minimum</code> supports broadcasting. More about broadcasting
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|
<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:minimum-39-" class="def">minimum'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:mirrorPad" class="def">mirrorPad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The input tensor to be padded.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tpaddings</td><td class="doc"><p><strong>paddings</strong>: A two-column matrix specifying the padding sizes. The number of
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rows must be the same as the rank of <code>input</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The padded tensor.</p></td></tr></table></div><div class="doc"><p>Pads a tensor with mirrored values.</p><p>This operation pads a <code>input</code> with mirrored values according to the <code>paddings</code>
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you specify. <code>paddings</code> is an integer tensor with shape `[n, 2]`, where n is
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the rank of <code>input</code>. For each dimension D of <code>input</code>, `paddings[D, 0]` indicates
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|
how many values to add before the contents of <code>input</code> in that dimension, and
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`paddings[D, 1]` indicates how many values to add after the contents of <code>input</code>
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|
in that dimension. Both `paddings[D, 0]` and `paddings[D, 1]` must be no greater
|
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than `input.dim_size(D)` (or `input.dim_size(D) - 1`) if <code>copy_border</code> is true
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(if false, respectively).</p><p>The padded size of each dimension D of the output is:</p><p>`paddings(D, 0) + input.dim_size(D) + paddings(D, 1)`</p><p>For example:</p><p>```prettyprint
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# <code>t</code> is [[1, 2, 3], [4, 5, 6]].
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# <code>paddings</code> is [[1, 1]], [2, 2]].
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# <code>mode</code> is SYMMETRIC.
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# rank of <code>t</code> is 2.
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pad(t, paddings) ==> [[2, 1, 1, 2, 3, 3, 2]
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[2, 1, 1, 2, 3, 3, 2]
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[5, 4, 4, 5, 6, 6, 5]
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[5, 4, 4, 5, 6, 6, 5]]
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```</p></div></div><div class="top"><p class="src"><a name="v:mirrorPad-39-" class="def">mirrorPad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The input tensor to be padded.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tpaddings</td><td class="doc"><p><strong>paddings</strong>: A two-column matrix specifying the padding sizes. The number of
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|
rows must be the same as the rank of <code>input</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The padded tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:mirrorPadGrad" class="def">mirrorPadGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The input tensor to be folded.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tpaddings</td><td class="doc"><p><strong>paddings</strong>: A two-column matrix specifying the padding sizes. The number of
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|
rows must be the same as the rank of <code>input</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The folded tensor.</p></td></tr></table></div><div class="doc"><p>Gradient op for <code>MirrorPad</code> op. This op folds a mirror-padded tensor.</p><p>This operation folds the padded areas of <code>input</code> by <code>MirrorPad</code> according to the
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|
<code>paddings</code> you specify. <code>paddings</code> must be the same as <code>paddings</code> argument
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|
given to the corresponding <code>MirrorPad</code> op.</p><p>The folded size of each dimension D of the output is:</p><p>`input.dim_size(D) - paddings(D, 0) - paddings(D, 1)`</p><p>For example:</p><p>```prettyprint
|
|
# <code>t</code> is [[1, 2, 3], [4, 5, 6], [7, 8, 9]].
|
|
# <code>paddings</code> is [[0, 1]], [0, 1]].
|
|
# <code>mode</code> is SYMMETRIC.
|
|
# rank of <code>t</code> is 2.
|
|
pad(t, paddings) ==> [[ 1, 5]
|
|
[11, 28]]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:mirrorPadGrad-39-" class="def">mirrorPadGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The input tensor to be folded.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tpaddings</td><td class="doc"><p><strong>paddings</strong>: A two-column matrix specifying the padding sizes. The number of
|
|
rows must be the same as the rank of <code>input</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The folded tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:mod" class="def">mod</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns element-wise remainder of division.</p><ul><li>NOTE*: <code>Mod</code> supports broadcasting. More about broadcasting
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|
<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:mod-39-" class="def">mod'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:mul" class="def">mul</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns x * y element-wise.</p><ul><li>NOTE*: <code>Mul</code> supports broadcasting. More about broadcasting
|
|
<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:mul-39-" class="def">mul'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:multinomial" class="def">multinomial</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>logits</strong>: 2-D Tensor with shape `[batch_size, num_classes]`. Each slice `[i, :]`
|
|
represents the unnormalized log probabilities for all classes.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>num_samples</strong>: 0-D. Number of independent samples to draw for each row slice.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p><strong>output</strong>: 2-D Tensor with shape `[batch_size, num_samples]`. Each slice `[i, :]`
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contains the drawn class labels with range `[0, num_classes)`.</p></td></tr></table></div><div class="doc"><p>Draws samples from a multinomial distribution.</p></div></div><div class="top"><p class="src"><a name="v:multinomial-39-" class="def">multinomial'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>logits</strong>: 2-D Tensor with shape `[batch_size, num_classes]`. Each slice `[i, :]`
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|
represents the unnormalized log probabilities for all classes.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>num_samples</strong>: 0-D. Number of independent samples to draw for each row slice.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p><strong>output</strong>: 2-D Tensor with shape `[batch_size, num_samples]`. Each slice `[i, :]`
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contains the drawn class labels with range `[0, num_classes)`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:mutableDenseHashTable" class="def">mutableDenseHashTable</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> key_dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>value_dtype</strong>: Type of the table values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 key_dtype</td><td class="doc"><p><strong>empty_key</strong>: The key used to represent empty key buckets internally. Must not
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be used in insert or lookup operations.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>table_handle</strong>: Handle to a table.</p></td></tr></table></div><div class="doc"><p>Creates an empty hash table that uses tensors as the backing store. It uses</p><p>"open addressing" with quadratic reprobing to resolve collisions.</p><p>This op creates a mutable hash table, specifying the type of its keys and
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values. Each value must be a scalar. Data can be inserted into the table using
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the insert operations. It does not support the initialization operation.</p></div></div><div class="top"><p class="src"><a name="v:mutableDenseHashTable-39-" class="def">mutableDenseHashTable'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> key_dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>value_dtype</strong>: Type of the table values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 key_dtype</td><td class="doc"><p><strong>empty_key</strong>: The key used to represent empty key buckets internally. Must not
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be used in insert or lookup operations.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>table_handle</strong>: Handle to a table.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:mutableHashTable" class="def">mutableHashTable</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>key_dtype</strong>: Type of the table keys.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>value_dtype</strong>: Type of the table values.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>table_handle</strong>: Handle to a table.</p></td></tr></table></div><div class="doc"><p>Creates an empty hash table.</p><p>This op creates a mutable hash table, specifying the type of its keys and
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values. Each value must be a scalar. Data can be inserted into the table using
|
|
the insert operations. It does not support the initialization operation.</p></div></div><div class="top"><p class="src"><a name="v:mutableHashTable-39-" class="def">mutableHashTable'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>key_dtype</strong>: Type of the table keys.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>value_dtype</strong>: Type of the table values.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>table_handle</strong>: Handle to a table.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:mutableHashTableOfTensors" class="def">mutableHashTableOfTensors</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>key_dtype</strong>: Type of the table keys.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>value_dtype</strong>: Type of the table values.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>table_handle</strong>: Handle to a table.</p></td></tr></table></div><div class="doc"><p>Creates an empty hash table.</p><p>This op creates a mutable hash table, specifying the type of its keys and
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values. Each value must be a vector. Data can be inserted into the table using
|
|
the insert operations. It does not support the initialization operation.</p></div></div><div class="top"><p class="src"><a name="v:mutableHashTableOfTensors-39-" class="def">mutableHashTableOfTensors'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>key_dtype</strong>: Type of the table keys.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>value_dtype</strong>: Type of the table values.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>table_handle</strong>: Handle to a table.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:neg" class="def">neg</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes numerical negative value element-wise.</p><p>I.e., \(y = -x\).</p></div></div><div class="top"><p class="src"><a name="v:neg-39-" class="def">neg'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:negTrain" class="def">negTrain</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_negative_samples</strong>: Number of negative samples per example.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>w_in</strong>: input word embedding.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>w_out</strong>: output word embedding.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>examples</strong>: A vector of word ids.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>labels</strong>: A vector of word ids.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>lr</strong></p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Training via negative sampling.</p></div></div><div class="top"><p class="src"><a name="v:negTrain-39-" class="def">negTrain'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_negative_samples</strong>: Number of negative samples per example.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>w_in</strong>: input word embedding.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>w_out</strong>: output word embedding.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>examples</strong>: A vector of word ids.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>labels</strong>: A vector of word ids.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>lr</strong></p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:nextIteration" class="def">nextIteration</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong>: The tensor to be made available to the next iteration.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The same tensor as `data`.</p></td></tr></table></div><div class="doc"><p>Makes its input available to the next iteration.</p></div></div><div class="top"><p class="src"><a name="v:nextIteration-39-" class="def">nextIteration'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong>: The tensor to be made available to the next iteration.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The same tensor as `data`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:noOp" class="def">noOp</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></p><div class="doc"><p>Does nothing. Only useful as a placeholder for control edges.</p></div></div><div class="top"><p class="src"><a name="v:noOp-39-" class="def">noOp'</a> :: <span class="keyword">forall</span> m'. <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m' => <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a> -> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></p></div><div class="top"><p class="src"><a name="v:nonMaxSuppression" class="def">nonMaxSuppression</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>boxes</strong>: A 2-D float tensor of shape `[num_boxes, 4]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>scores</strong>: A 1-D float tensor of shape `[num_boxes]` representing a single
|
|
score corresponding to each box (each row of boxes).</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>max_output_size</strong>: A scalar integer tensor representing the maximum number of
|
|
boxes to be selected by non max suppression.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>selected_indices</strong>: A 1-D integer tensor of shape `[M]` representing the selected
|
|
indices from the boxes tensor, where `M <= max_output_size`.</p></td></tr></table></div><div class="doc"><p>Greedily selects a subset of bounding boxes in descending order of score,</p><p>pruning away boxes that have high intersection-over-union (IOU) overlap
|
|
with previously selected boxes. Bounding boxes are supplied as
|
|
[y1, x1, y2, x2], where (y1, x1) and (y2, x2) are the coordinates of any
|
|
diagonal pair of box corners and the coordinates can be provided as normalized
|
|
(i.e., lying in the interval [0, 1]) or absolute. Note that this algorithm
|
|
is agnostic to where the origin is in the coordinate system. Note that this
|
|
algorithm is invariant to orthogonal transformations and translations
|
|
of the coordinate system; thus translating or reflections of the coordinate
|
|
system result in the same boxes being selected by the algorithm.</p><p>The output of this operation is a set of integers indexing into the input
|
|
collection of bounding boxes representing the selected boxes. The bounding
|
|
box coordinates corresponding to the selected indices can then be obtained
|
|
using the `tf.gather operation`. For example:</p><p>selected_indices = tf.image.non_max_suppression(
|
|
boxes, scores, max_output_size, iou_threshold)
|
|
selected_boxes = tf.gather(boxes, selected_indices)</p></div></div><div class="top"><p class="src"><a name="v:nonMaxSuppression-39-" class="def">nonMaxSuppression'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>boxes</strong>: A 2-D float tensor of shape `[num_boxes, 4]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>scores</strong>: A 1-D float tensor of shape `[num_boxes]` representing a single
|
|
score corresponding to each box (each row of boxes).</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>max_output_size</strong>: A scalar integer tensor representing the maximum number of
|
|
boxes to be selected by non max suppression.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>selected_indices</strong>: A 1-D integer tensor of shape `[M]` representing the selected
|
|
indices from the boxes tensor, where `M <= max_output_size`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:notEqual" class="def">notEqual</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns the truth value of (x != y) element-wise.</p><ul><li>NOTE*: <code>NotEqual</code> supports broadcasting. More about broadcasting
|
|
<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:notEqual-39-" class="def">notEqual'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:oneHot" class="def">oneHot</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tI)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tI</td><td class="doc"><p><strong>indices</strong>: A tensor of indices.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>depth</strong>: A scalar defining the depth of the one hot dimension.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>on_value</strong>: A scalar defining the value to fill in output when `indices[j] = i`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>off_value</strong>: A scalar defining the value to fill in output when `indices[j] != i`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The one-hot tensor.</p></td></tr></table></div><div class="doc"><p>Returns a one-hot tensor.</p><p>The locations represented by indices in <code>indices</code> take value <code>on_value</code>,
|
|
while all other locations take value <code>off_value</code>.</p><p>If the input <code>indices</code> is rank <code>N</code>, the output will have rank `N+1`,
|
|
The new axis is created at dimension <code>axis</code> (default: the new axis is
|
|
appended at the end).</p><p>If <code>indices</code> is a scalar the output shape will be a vector of length <code>depth</code>.</p><p>If <code>indices</code> is a vector of length <code>features</code>, the output shape will be:
|
|
```
|
|
features x depth if axis == -1
|
|
depth x features if axis == 0
|
|
```</p><p>If <code>indices</code> is a matrix (batch) with shape `[batch, features]`,
|
|
the output shape will be:
|
|
```
|
|
batch x features x depth if axis == -1
|
|
batch x depth x features if axis == 1
|
|
depth x batch x features if axis == 0
|
|
```</p><p>Examples
|
|
=========</p><p>Suppose that</p><p>```
|
|
indices = [0, 2, -1, 1]
|
|
depth = 3
|
|
on_value = 5.0
|
|
off_value = 0.0
|
|
axis = -1
|
|
```</p><p>Then output is `[4 x 3]`:</p><p>```output =
|
|
[5.0 0.0 0.0] // one_hot(0)
|
|
[0.0 0.0 5.0] // one_hot(2)
|
|
[0.0 0.0 0.0] // one_hot(-1)
|
|
[0.0 5.0 0.0] // one_hot(1)
|
|
```</p><p>Suppose that</p><p>```
|
|
indices = [0, 2, -1, 1]
|
|
depth = 3
|
|
on_value = 0.0
|
|
off_value = 3.0
|
|
axis = 0
|
|
```</p><p>Then output is `[3 x 4]`:</p><p>```output =
|
|
[0.0 3.0 3.0 3.0]
|
|
[3.0 3.0 3.0 0.0]
|
|
[3.0 3.0 3.0 3.0]
|
|
[3.0 0.0 3.0 3.0]
|
|
// ^ one_hot(0)
|
|
// ^ one_hot(2)
|
|
// ^ one_hot(-1)
|
|
// ^ one_hot(1)
|
|
```
|
|
Suppose that</p><p>```
|
|
indices = [[0, 2], [1, -1]]
|
|
depth = 3
|
|
on_value = 1.0
|
|
off_value = 0.0
|
|
axis = -1
|
|
```</p><p>Then output is `[2 x 2 x 3]`:</p><p>```output =
|
|
[
|
|
[1.0, 0.0, 0.0] // one_hot(0)
|
|
[0.0, 0.0, 1.0] // one_hot(2)
|
|
][
|
|
[0.0, 1.0, 0.0] // one_hot(1)
|
|
[0.0, 0.0, 0.0] // one_hot(-1)
|
|
]```</p></div></div><div class="top"><p class="src"><a name="v:oneHot-39-" class="def">oneHot'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tI)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tI</td><td class="doc"><p><strong>indices</strong>: A tensor of indices.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>depth</strong>: A scalar defining the depth of the one hot dimension.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>on_value</strong>: A scalar defining the value to fill in output when `indices[j] = i`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>off_value</strong>: A scalar defining the value to fill in output when `indices[j] != i`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The one-hot tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:pack" class="def">pack</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t]</td><td class="doc"><p><strong>values</strong>: Must be of same shape and type.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The packed tensor.</p></td></tr></table></div><div class="doc"><p>Packs a list of <code>N</code> rank-<code>R</code> tensors into one rank-`(R+1)` tensor.</p><p>Packs the <code>N</code> tensors in <code>values</code> into a tensor with rank one higher than each
|
|
tensor in <code>values</code>, by packing them along the <code>axis</code> dimension.
|
|
Given a list of tensors of shape `(A, B, C)`;</p><p>if `axis == 0` then the <code>output</code> tensor will have the shape `(N, A, B, C)`.
|
|
if `axis == 1` then the <code>output</code> tensor will have the shape `(A, N, B, C)`.
|
|
Etc.</p><p>For example:</p><p>```prettyprint
|
|
# <code>x</code> is [1, 4]
|
|
# <code>y</code> is [2, 5]
|
|
# <code>z</code> is [3, 6]
|
|
pack([x, y, z]) => [[1, 4], [2, 5], [3, 6]] # Pack along first dim.
|
|
pack([x, y, z], axis=1) => [[1, 2, 3], [4, 5, 6]]
|
|
```</p><p>This is the opposite of <code><a href="TensorFlow-GenOps-Core.html#v:unpack">unpack</a></code>.</p></div></div><div class="top"><p class="src"><a name="v:pack-39-" class="def">pack'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t]</td><td class="doc"><p><strong>values</strong>: Must be of same shape and type.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The packed tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:pad" class="def">pad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tpaddings</td><td class="doc"><p><strong>paddings</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Pads a tensor with zeros.</p><p>This operation pads a <code>input</code> with zeros according to the <code>paddings</code> you
|
|
specify. <code>paddings</code> is an integer tensor with shape `[Dn, 2]`, where n is the
|
|
rank of <code>input</code>. For each dimension D of <code>input</code>, `paddings[D, 0]` indicates
|
|
how many zeros to add before the contents of <code>input</code> in that dimension, and
|
|
`paddings[D, 1]` indicates how many zeros to add after the contents of <code>input</code>
|
|
in that dimension.</p><p>The padded size of each dimension D of the output is:</p><p>`paddings(D, 0) + input.dim_size(D) + paddings(D, 1)`</p><p>For example:</p><p>```prettyprint
|
|
# <code>t</code> is [[1, 1], [2, 2]]
|
|
# <code>paddings</code> is [[1, 1], [2, 2]]
|
|
# rank of <code>t</code> is 2
|
|
pad(t, paddings) ==> [[0, 0, 0, 0, 0, 0]
|
|
[0, 0, 1, 1, 0, 0]
|
|
[0, 0, 2, 2, 0, 0]
|
|
[0, 0, 0, 0, 0, 0]]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:pad-39-" class="def">pad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tpaddings</td><td class="doc"><p><strong>paddings</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:paddingFIFOQueue" class="def">paddingFIFOQueue</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>]</td><td class="doc"><p><strong>component_types</strong>: The type of each component in a value.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong>: The handle to the queue.</p></td></tr></table></div><div class="doc"><p>A queue that produces elements in first-in first-out order.</p><p>Variable-size shapes are allowed by setting the corresponding shape dimensions
|
|
to 0 in the shape attr. In this case DequeueMany will pad up to the maximum
|
|
size of any given element in the minibatch. See below for details.</p></div></div><div class="top"><p class="src"><a name="v:paddingFIFOQueue-39-" class="def">paddingFIFOQueue'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>]</td><td class="doc"><p><strong>component_types</strong>: The type of each component in a value.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong>: The handle to the queue.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:paddingFIFOQueueV2" class="def">paddingFIFOQueueV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>]</td><td class="doc"><p><strong>component_types</strong>: The type of each component in a value.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to the queue.</p></td></tr></table></div><div class="doc"><p>A queue that produces elements in first-in first-out order.</p><p>Variable-size shapes are allowed by setting the corresponding shape dimensions
|
|
to 0 in the shape attr. In this case DequeueMany will pad up to the maximum
|
|
size of any given element in the minibatch. See below for details.</p></div></div><div class="top"><p class="src"><a name="v:paddingFIFOQueueV2-39-" class="def">paddingFIFOQueueV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>]</td><td class="doc"><p><strong>component_types</strong>: The type of each component in a value.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to the queue.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:parallelConcat" class="def">parallelConcat</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: the final shape of the result; should be equal to the shapes of any input
|
|
but with the number of input values in the first dimension.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t]</td><td class="doc"><p><strong>values</strong>: Tensors to be concatenated. All must have size 1 in the first dimension
|
|
and same shape.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The concatenated tensor.</p></td></tr></table></div><div class="doc"><p>Concatenates a list of <code>N</code> tensors along the first dimension.</p><p>The input tensors are all required to have size 1 in the first dimension.</p><p>For example:</p><p>```prettyprint
|
|
# <code>x</code> is [[1, 4]]
|
|
# <code>y</code> is [[2, 5]]
|
|
# <code>z</code> is [[3, 6]]
|
|
parallel_concat([x, y, z]) => [[1, 4], [2, 5], [3, 6]] # Pack along first dim.
|
|
```</p><p>The difference between concat and parallel_concat is that concat requires all
|
|
of the inputs be computed before the operation will begin but doesn't require
|
|
that the input shapes be known during graph construction. Parallel concat
|
|
will copy pieces of the input into the output as they become available, in
|
|
some situations this can provide a performance benefit.</p></div></div><div class="top"><p class="src"><a name="v:parallelConcat-39-" class="def">parallelConcat'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: the final shape of the result; should be equal to the shapes of any input
|
|
but with the number of input values in the first dimension.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t]</td><td class="doc"><p><strong>values</strong>: Tensors to be concatenated. All must have size 1 in the first dimension
|
|
and same shape.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The concatenated tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:parameterizedTruncatedNormal" class="def">parameterizedTruncatedNormal</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>shape</strong>: The shape of the output tensor. Batches are indexed by the 0th dimension.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 dtype</td><td class="doc"><p><strong>means</strong>: The mean parameter of each batch.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 dtype</td><td class="doc"><p><strong>stdevs</strong>: The standard deviation parameter of each batch. Must be greater than 0.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 dtype</td><td class="doc"><p><strong>minvals</strong>: The minimum cutoff. May be -infinity.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 dtype</td><td class="doc"><p><strong>maxvals</strong>: The maximum cutoff. May be +infinity, and must be more than the minval
|
|
for each batch.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>output</strong>: A matrix of shape num_batches x samples_per_batch, filled with random
|
|
truncated normal values using the parameters for each row.</p></td></tr></table></div><div class="doc"><p>Outputs random values from a normal distribution. The parameters may each be a</p><p>scalar which applies to the entire output, or a vector of length shape[0] which
|
|
stores the parameters for each batch.</p></div></div><div class="top"><p class="src"><a name="v:parameterizedTruncatedNormal-39-" class="def">parameterizedTruncatedNormal'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>shape</strong>: The shape of the output tensor. Batches are indexed by the 0th dimension.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 dtype</td><td class="doc"><p><strong>means</strong>: The mean parameter of each batch.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 dtype</td><td class="doc"><p><strong>stdevs</strong>: The standard deviation parameter of each batch. Must be greater than 0.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 dtype</td><td class="doc"><p><strong>minvals</strong>: The minimum cutoff. May be -infinity.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 dtype</td><td class="doc"><p><strong>maxvals</strong>: The maximum cutoff. May be +infinity, and must be more than the minval
|
|
for each batch.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>output</strong>: A matrix of shape num_batches x samples_per_batch, filled with random
|
|
truncated normal values using the parameters for each row.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:parseExample" class="def">parseExample</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` sparse_types, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tdense)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>serialized</strong>: A vector containing a batch of binary serialized Example protos.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>names</strong>: A vector containing the names of the serialized protos.
|
|
May contain, for example, table key (descriptive) names for the
|
|
corresponding serialized protos. These are purely useful for debugging
|
|
purposes, and the presence of values here has no effect on the output.
|
|
May also be an empty vector if no names are available.
|
|
If non-empty, this vector must be the same length as "serialized".</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>]</td><td class="doc"><p><strong>sparse_keys</strong>: A list of Nsparse string Tensors (scalars).
|
|
The keys expected in the Examples' features associated with sparse values.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>]</td><td class="doc"><p><strong>dense_keys</strong>: A list of Ndense string Tensors (scalars).
|
|
The keys expected in the Examples' features associated with dense values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'5 tdense</td><td class="doc"><p><strong>dense_defaults</strong>: A list of Ndense Tensors (some may be empty).
|
|
dense_defaults[j] provides default values
|
|
when the example's feature_map lacks dense_key[j]. If an empty Tensor is
|
|
provided for dense_defaults[j], then the Feature dense_keys[j] is required.
|
|
The input type is inferred from dense_defaults[j], even when it's empty.
|
|
If dense_defaults[j] is not empty, its shape must match dense_shapes[j].</p></td></tr><tr><td class="src">-> ([<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> sparse_types, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tdense)</td><td class="doc"><p>(<strong>sparse_indices</strong>, <strong>sparse_values</strong>, <strong>sparse_shapes</strong>, <strong>dense_values</strong>)</p><ul><li><strong>sparse_indices</strong></li><li><strong>sparse_values</strong></li><li><strong>sparse_shapes</strong></li><li><strong>dense_values</strong></li></ul></td></tr></table></div><div class="doc"><p>Transforms a vector of brain.Example protos (as strings) into typed tensors.</p></div></div><div class="top"><p class="src"><a name="v:parseExample-39-" class="def">parseExample'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` sparse_types, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tdense)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>serialized</strong>: A vector containing a batch of binary serialized Example protos.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>names</strong>: A vector containing the names of the serialized protos.
|
|
May contain, for example, table key (descriptive) names for the
|
|
corresponding serialized protos. These are purely useful for debugging
|
|
purposes, and the presence of values here has no effect on the output.
|
|
May also be an empty vector if no names are available.
|
|
If non-empty, this vector must be the same length as "serialized".</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>]</td><td class="doc"><p><strong>sparse_keys</strong>: A list of Nsparse string Tensors (scalars).
|
|
The keys expected in the Examples' features associated with sparse values.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>]</td><td class="doc"><p><strong>dense_keys</strong>: A list of Ndense string Tensors (scalars).
|
|
The keys expected in the Examples' features associated with dense values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'5 tdense</td><td class="doc"><p><strong>dense_defaults</strong>: A list of Ndense Tensors (some may be empty).
|
|
dense_defaults[j] provides default values
|
|
when the example's feature_map lacks dense_key[j]. If an empty Tensor is
|
|
provided for dense_defaults[j], then the Feature dense_keys[j] is required.
|
|
The input type is inferred from dense_defaults[j], even when it's empty.
|
|
If dense_defaults[j] is not empty, its shape must match dense_shapes[j].</p></td></tr><tr><td class="src">-> ([<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> sparse_types, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tdense)</td><td class="doc"><p>(<strong>sparse_indices</strong>, <strong>sparse_values</strong>, <strong>sparse_shapes</strong>, <strong>dense_values</strong>)</p><ul><li><strong>sparse_indices</strong></li><li><strong>sparse_values</strong></li><li><strong>sparse_shapes</strong></li><li><strong>dense_values</strong></li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:parseSingleSequenceExample" class="def">parseSingleSequenceExample</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` context_sparse_types, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tcontext_dense, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` feature_list_dense_types, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` feature_list_sparse_types)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>serialized</strong>: A scalar containing a binary serialized SequenceExample proto.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>feature_list_dense_missing_assumed_empty</strong>: A vector listing the
|
|
FeatureList keys which may be missing from the SequenceExample. If the
|
|
associated FeatureList is missing, it is treated as empty. By default,
|
|
any FeatureList not listed in this vector must exist in the SequenceExample.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>]</td><td class="doc"><p><strong>context_sparse_keys</strong>: A list of Ncontext_sparse string Tensors (scalars).
|
|
The keys expected in the Examples' features associated with context_sparse
|
|
values.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>]</td><td class="doc"><p><strong>context_dense_keys</strong>: A list of Ncontext_dense string Tensors (scalars).
|
|
The keys expected in the SequenceExamples' context features associated with
|
|
dense values.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>]</td><td class="doc"><p><strong>feature_list_sparse_keys</strong>: A list of Nfeature_list_sparse string Tensors
|
|
(scalars). The keys expected in the FeatureLists associated with sparse
|
|
values.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>]</td><td class="doc"><p><strong>feature_list_dense_keys</strong>: A list of Nfeature_list_dense string Tensors (scalars).
|
|
The keys expected in the SequenceExamples' feature_lists associated
|
|
with lists of dense values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'7 tcontext_dense</td><td class="doc"><p><strong>context_dense_defaults</strong>: A list of Ncontext_dense Tensors (some may be empty).
|
|
context_dense_defaults[j] provides default values
|
|
when the SequenceExample's context map lacks context_dense_key[j].
|
|
If an empty Tensor is provided for context_dense_defaults[j],
|
|
then the Feature context_dense_keys[j] is required.
|
|
The input type is inferred from context_dense_defaults[j], even when it's
|
|
empty. If context_dense_defaults[j] is not empty, its shape must match
|
|
context_dense_shapes[j].</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>debug_name</strong>: A scalar containing the name of the serialized proto.
|
|
May contain, for example, table key (descriptive) name for the
|
|
corresponding serialized proto. This is purely useful for debugging
|
|
purposes, and the presence of values here has no effect on the output.
|
|
May also be an empty scalar if no name is available.</p></td></tr><tr><td class="src">-> ([<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> context_sparse_types, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tcontext_dense, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> feature_list_sparse_types, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> feature_list_dense_types)</td><td class="doc"><p>(<strong>context_sparse_indices</strong>, <strong>context_sparse_values</strong>, <strong>context_sparse_shapes</strong>, <strong>context_dense_values</strong>, <strong>feature_list_sparse_indices</strong>, <strong>feature_list_sparse_values</strong>, <strong>feature_list_sparse_shapes</strong>, <strong>feature_list_dense_values</strong>)</p><ul><li><strong>context_sparse_indices</strong></li><li><strong>context_sparse_values</strong></li><li><strong>context_sparse_shapes</strong></li><li><strong>context_dense_values</strong></li><li><strong>feature_list_sparse_indices</strong></li><li><strong>feature_list_sparse_values</strong></li><li><strong>feature_list_sparse_shapes</strong></li><li><strong>feature_list_dense_values</strong></li></ul></td></tr></table></div><div class="doc"><p>Transforms a scalar brain.SequenceExample proto (as strings) into typed tensors.</p></div></div><div class="top"><p class="src"><a name="v:parseSingleSequenceExample-39-" class="def">parseSingleSequenceExample'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` context_sparse_types, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tcontext_dense, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` feature_list_dense_types, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOfs">OneOfs</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` feature_list_sparse_types)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>serialized</strong>: A scalar containing a binary serialized SequenceExample proto.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>feature_list_dense_missing_assumed_empty</strong>: A vector listing the
|
|
FeatureList keys which may be missing from the SequenceExample. If the
|
|
associated FeatureList is missing, it is treated as empty. By default,
|
|
any FeatureList not listed in this vector must exist in the SequenceExample.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>]</td><td class="doc"><p><strong>context_sparse_keys</strong>: A list of Ncontext_sparse string Tensors (scalars).
|
|
The keys expected in the Examples' features associated with context_sparse
|
|
values.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>]</td><td class="doc"><p><strong>context_dense_keys</strong>: A list of Ncontext_dense string Tensors (scalars).
|
|
The keys expected in the SequenceExamples' context features associated with
|
|
dense values.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>]</td><td class="doc"><p><strong>feature_list_sparse_keys</strong>: A list of Nfeature_list_sparse string Tensors
|
|
(scalars). The keys expected in the FeatureLists associated with sparse
|
|
values.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>]</td><td class="doc"><p><strong>feature_list_dense_keys</strong>: A list of Nfeature_list_dense string Tensors (scalars).
|
|
The keys expected in the SequenceExamples' feature_lists associated
|
|
with lists of dense values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'7 tcontext_dense</td><td class="doc"><p><strong>context_dense_defaults</strong>: A list of Ncontext_dense Tensors (some may be empty).
|
|
context_dense_defaults[j] provides default values
|
|
when the SequenceExample's context map lacks context_dense_key[j].
|
|
If an empty Tensor is provided for context_dense_defaults[j],
|
|
then the Feature context_dense_keys[j] is required.
|
|
The input type is inferred from context_dense_defaults[j], even when it's
|
|
empty. If context_dense_defaults[j] is not empty, its shape must match
|
|
context_dense_shapes[j].</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>debug_name</strong>: A scalar containing the name of the serialized proto.
|
|
May contain, for example, table key (descriptive) name for the
|
|
corresponding serialized proto. This is purely useful for debugging
|
|
purposes, and the presence of values here has no effect on the output.
|
|
May also be an empty scalar if no name is available.</p></td></tr><tr><td class="src">-> ([<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> context_sparse_types, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tcontext_dense, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> feature_list_sparse_types, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> feature_list_dense_types)</td><td class="doc"><p>(<strong>context_sparse_indices</strong>, <strong>context_sparse_values</strong>, <strong>context_sparse_shapes</strong>, <strong>context_dense_values</strong>, <strong>feature_list_sparse_indices</strong>, <strong>feature_list_sparse_values</strong>, <strong>feature_list_sparse_shapes</strong>, <strong>feature_list_dense_values</strong>)</p><ul><li><strong>context_sparse_indices</strong></li><li><strong>context_sparse_values</strong></li><li><strong>context_sparse_shapes</strong></li><li><strong>context_dense_values</strong></li><li><strong>feature_list_sparse_indices</strong></li><li><strong>feature_list_sparse_values</strong></li><li><strong>feature_list_sparse_shapes</strong></li><li><strong>feature_list_dense_values</strong></li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:parseTensor" class="def">parseTensor</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> out_type</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>serialized</strong>: A scalar string containing a serialized TensorProto proto.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</td><td class="doc"><p><strong>output</strong>: A Tensor of type <code>out_type</code>.</p></td></tr></table></div><div class="doc"><p>Transforms a serialized tensorflow.TensorProto proto into a Tensor.</p></div></div><div class="top"><p class="src"><a name="v:parseTensor-39-" class="def">parseTensor'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> out_type</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>serialized</strong>: A scalar string containing a serialized TensorProto proto.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</td><td class="doc"><p><strong>output</strong>: A Tensor of type <code>out_type</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:placeholder" class="def">placeholder</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</td><td class="doc"><p><strong>output</strong>: A placeholder tensor that must be replaced using the feed mechanism.</p></td></tr></table></div><div class="doc"><p>A placeholder op for a value that will be fed into the computation.</p><p>N.B. This operation will fail with an error if it is executed. It is
|
|
intended as a way to represent a value that will always be fed, and to
|
|
provide attrs that enable the fed value to be checked at runtime.</p></div></div><div class="top"><p class="src"><a name="v:placeholder-39-" class="def">placeholder'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</td><td class="doc"><p><strong>output</strong>: A placeholder tensor that must be replaced using the feed mechanism.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:placeholderV2" class="def">placeholderV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: The shape of the tensor. The shape can be any partially-specified
|
|
shape. To be unconstrained, pass in a shape with unknown rank.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</td><td class="doc"><p><strong>output</strong>: A placeholder tensor that must be replaced using the feed mechanism.</p></td></tr></table></div><div class="doc"><p>A placeholder op for a value that will be fed into the computation.</p><p>N.B. This operation will fail with an error if it is executed. It is
|
|
intended as a way to represent a value that will always be fed, and to
|
|
provide attrs that enable the fed value to be checked at runtime.</p></div></div><div class="top"><p class="src"><a name="v:placeholderV2-39-" class="def">placeholderV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: The shape of the tensor. The shape can be any partially-specified
|
|
shape. To be unconstrained, pass in a shape with unknown rank.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</td><td class="doc"><p><strong>output</strong>: A placeholder tensor that must be replaced using the feed mechanism.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:placeholderWithDefault" class="def">placeholderWithDefault</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: The (possibly partial) shape of the tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 dtype</td><td class="doc"><p><strong>input</strong>: The default value to produce when <code>output</code> is not fed.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</td><td class="doc"><p><strong>output</strong>: A placeholder tensor that defaults to <code>input</code> if it is not fed.</p></td></tr></table></div><div class="doc"><p>A placeholder op that passes through <code>input</code> when its output is not fed.</p></div></div><div class="top"><p class="src"><a name="v:placeholderWithDefault-39-" class="def">placeholderWithDefault'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: The (possibly partial) shape of the tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 dtype</td><td class="doc"><p><strong>input</strong>: The default value to produce when <code>output</code> is not fed.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</td><td class="doc"><p><strong>output</strong>: A placeholder tensor that defaults to <code>input</code> if it is not fed.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:polygamma" class="def">polygamma</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>a</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Compute the polygamma function \(psi^{(n)}(x)\).</p><p>The polygamma function is defined as:</p><p>```
|
|
psi^{(n)}(x) = frac{d^n}{dx^n} psi(x)
|
|
```
|
|
where \(psi(x)\) is the digamma function.</p></div></div><div class="top"><p class="src"><a name="v:polygamma-39-" class="def">polygamma'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>a</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:pow" class="def">pow</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Computes the power of one value to another.</p><p>Given a tensor <code>x</code> and a tensor <code>y</code>, this operation computes \(x^y\) for
|
|
corresponding elements in <code>x</code> and <code>y</code>. For example:</p><p>```
|
|
# tensor <code>x</code> is [[2, 2]], [3, 3]]
|
|
# tensor <code>y</code> is [[8, 16], [2, 3]]
|
|
tf.pow(x, y) ==> [[256, 65536], [9, 27]]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:pow-39-" class="def">pow'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:preventGradient" class="def">preventGradient</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>An identity op that triggers an error if a gradient is requested.</p><p>When executed in a graph, this op outputs its input tensor as-is.</p><p>When building ops to compute gradients, the TensorFlow gradient system
|
|
will return an error when trying to lookup the gradient of this op,
|
|
because no gradient must ever be registered for this function. This
|
|
op exists to prevent subtle bugs from silently returning unimplemented
|
|
gradients in some corner cases.</p></div></div><div class="top"><p class="src"><a name="v:preventGradient-39-" class="def">preventGradient'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:print" class="def">print</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> u)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The tensor passed to <code>output</code></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 u</td><td class="doc"><p><strong>data</strong>: A list of tensors to print out when op is evaluated.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</td><td class="doc"><p><strong>output</strong>: = The unmodified <code>input</code> tensor</p></td></tr></table></div><div class="doc"><p>Prints a list of tensors.</p><p>Passes <code>input</code> through to <code>output</code> and prints `data` when evaluating.</p></div></div><div class="top"><p class="src"><a name="v:print-39-" class="def">print'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> u)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The tensor passed to <code>output</code></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 u</td><td class="doc"><p><strong>data</strong>: A list of tensors to print out when op is evaluated.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</td><td class="doc"><p><strong>output</strong>: = The unmodified <code>input</code> tensor</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:priorityQueue" class="def">priorityQueue</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong>: The handle to the queue.</p></td></tr></table></div><div class="doc"><p>A queue that produces elements sorted by the first component value.</p><p>Note that the PriorityQueue requires the first component of any element
|
|
to be a scalar int64, in addition to the other elements declared by
|
|
component_types. Therefore calls to Enqueue and EnqueueMany (resp. Dequeue
|
|
and DequeueMany) on a PriorityQueue will all require (resp. output) one extra
|
|
entry in their input (resp. output) lists.</p></div></div><div class="top"><p class="src"><a name="v:priorityQueue-39-" class="def">priorityQueue'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong>: The handle to the queue.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:priorityQueueV2" class="def">priorityQueueV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to the queue.</p></td></tr></table></div><div class="doc"><p>A queue that produces elements sorted by the first component value.</p><p>Note that the PriorityQueue requires the first component of any element
|
|
to be a scalar int64, in addition to the other elements declared by
|
|
component_types. Therefore calls to Enqueue and EnqueueMany (resp. Dequeue
|
|
and DequeueMany) on a PriorityQueue will all require (resp. output) one extra
|
|
entry in their input (resp. output) lists.</p></div></div><div class="top"><p class="src"><a name="v:priorityQueueV2-39-" class="def">priorityQueueV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to the queue.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:prod" class="def">prod</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The tensor to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>reduction_indices</strong>: The dimensions to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The reduced tensor.</p></td></tr></table></div><div class="doc"><p>Computes the product of elements across dimensions of a tensor.</p><p>Reduces <code>input</code> along the dimensions given in <code>reduction_indices</code>. Unless
|
|
<code>keep_dims</code> is true, the rank of the tensor is reduced by 1 for each entry in
|
|
<code>reduction_indices</code>. If <code>keep_dims</code> is true, the reduced dimensions are
|
|
retained with length 1.</p></div></div><div class="top"><p class="src"><a name="v:prod-39-" class="def">prod'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The tensor to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>reduction_indices</strong>: The dimensions to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The reduced tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:qr" class="def">qr</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: A tensor of shape `[..., M, N]` whose inner-most 2 dimensions
|
|
form matrices of size `[M, N]`. Let <code>P</code> be the minimum of <code>M</code> and <code>N</code>.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>q</strong>, <strong>r</strong>)</p><ul><li><strong>q</strong>: Orthonormal basis for range of <code>a</code>. If <code>full_matrices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:False">False</a></code> then
|
|
shape is `[..., M, P]`; if <code>full_matrices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code> then shape is
|
|
`[..., M, M]`.</li><li><strong>r</strong>: Triangular factor. If <code>full_matrices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:False">False</a></code> then shape is
|
|
`[..., P, N]`. If <code>full_matrices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code> then shape is `[..., M, N]`.</li></ul></td></tr></table></div><div class="doc"><p>Computes the QR decompositions of one or more matrices.</p><p>Computes the QR decomposition of each inner matrix in <code>tensor</code> such that
|
|
`tensor[..., :, :] = q[..., :, :] * r[..., :,:])`</p><p>```prettyprint
|
|
# a is a tensor.
|
|
# q is a tensor of orthonormal matrices.
|
|
# r is a tensor of upper triangular matrices.
|
|
q, r = qr(a)
|
|
q_full, r_full = qr(a, full_matrices=True)
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:qr-39-" class="def">qr'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: A tensor of shape `[..., M, N]` whose inner-most 2 dimensions
|
|
form matrices of size `[M, N]`. Let <code>P</code> be the minimum of <code>M</code> and <code>N</code>.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>q</strong>, <strong>r</strong>)</p><ul><li><strong>q</strong>: Orthonormal basis for range of <code>a</code>. If <code>full_matrices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:False">False</a></code> then
|
|
shape is `[..., M, P]`; if <code>full_matrices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code> then shape is
|
|
`[..., M, M]`.</li><li><strong>r</strong>: Triangular factor. If <code>full_matrices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:False">False</a></code> then shape is
|
|
`[..., P, N]`. If <code>full_matrices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code> then shape is `[..., M, N]`.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:quantizeAndDequantize" class="def">quantizeAndDequantize</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Tensor to quantize and then dequantize.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Quantizes then dequantizes a tensor.</p><p>This op simulates the precision loss from the quantized forward pass by:
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|
1. Quantizing the tensor to fixed point numbers, which should match the target
|
|
quantization method when it is used in inference.
|
|
2. Dequantizing it back to floating point numbers for the following ops, most
|
|
likely matmul.</p><p>There are different ways to quantize. This version does not use the full range
|
|
of the output type, choosing to elide the lowest possible value for symmetry
|
|
(e.g., output range is -127 to 127, not -128 to 127 for signed 8 bit
|
|
quantization), so that 0.0 maps to 0.</p><p>To perform this op, we first find the range of values in our tensor. The range
|
|
we use is always centered on 0, so we find m such that</p><ol><li>m = max(abs(input_min), abs(input_max)) if range_given is true,</li><li>m = max(max(abs(min_elem(input)), abs(max_elem(input))) otherwise.</li></ol><p>Our input tensor range is then [-m, m].</p><p>Next, we choose our fixed-point quantization buckets, [min_fixed, max_fixed].
|
|
If signed_input is true, this is</p><dl><dt>min_fixed, max_fixed </dt><dd>=</dd><dt>-(1 << (num_bits - 1) - 1), (1 << (num_bits - 1)) - 1</dt><dd>.</dd></dl><p>Otherwise, if signed_input is false, the fixed-point range is</p><dl><dt>min_fixed, max_fixed</dt><dd>= [0, (1 << num_bits) - 1].</dd></dl><p>From this we compute our scaling factor, s:</p><p>s = (max_fixed - min_fixed) / (2 * m).</p><p>Now we can quantize and dequantize the elements of our tensor. An element e
|
|
is transformed into e':</p><p>e' = (e * s).round_to_nearest() / s.</p><p>Note that we have a different number of buckets in the signed vs. unsigned
|
|
cases. For example, if num_bits == 8, we get 254 buckets in the signed case
|
|
vs. 255 in the unsigned case.</p><p>For example, suppose num_bits = 8 and m = 1. Then</p><dl><dt>min_fixed, max_fixed</dt><dd>= [-127, 127], and
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|
s = (127 + 127) / 2 = 127.</dd></dl><p>Given the vector {-1, -0.5, 0, 0.3}, this is quantized to
|
|
{-127, -63, 0, 38}, and dequantized to {-1, -63.0<em>127, 0, 38.0</em>127}.</p></div></div><div class="top"><p class="src"><a name="v:quantizeAndDequantize-39-" class="def">quantizeAndDequantize'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Tensor to quantize and then dequantize.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:quantizeDownAndShrinkRange" class="def">quantizeDownAndShrinkRange</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input_min</strong>: The float value that the minimum quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input_max</strong>: The float value that the maximum quantized input value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>output_min</strong>, <strong>output_max</strong>)</p><ul><li><strong>output</strong></li><li><strong>output_min</strong>: The float value that the minimum quantized output value represents.</li><li><strong>output_max</strong>: The float value that the maximum quantized output value represents.</li></ul></td></tr></table></div><div class="doc"><p>Convert the quantized <code>input</code> tensor into a lower-precision <code>output</code>, using the</p><p>actual distribution of the values to maximize the usage of the lower bit depth
|
|
and adjusting the output min and max ranges accordingly.</p><dl><dt>input_min, input_max</dt><dd>are scalar floats that specify the range for the float
|
|
interpretation of the <code>input</code> data. For example, if input_min is -1.0f and
|
|
input_max is 1.0f, and we are dealing with quint16 quantized data, then a 0
|
|
value in the 16-bit data should be interpreted as -1.0f, and a 65535 means 1.0f.</dd></dl><p>This operator tries to squeeze as much precision as possible into an output with
|
|
a lower bit depth by calculating the actual min and max values found in the
|
|
data. For example, maybe that quint16 input has no values lower than 16,384 and
|
|
none higher than 49,152. That means only half the range is actually needed, all
|
|
the float interpretations are between -0.5f and 0.5f, so if we want to compress
|
|
the data into a quint8 output, we can use that range rather than the theoretical
|
|
-1.0f to 1.0f that is suggested by the input min and max.</p><p>In practice, this is most useful for taking output from operations like
|
|
QuantizedMatMul that can produce higher bit-depth outputs than their inputs and
|
|
may have large potential output ranges, but in practice have a distribution of
|
|
input values that only uses a small fraction of the possible range. By feeding
|
|
that output into this operator, we can reduce it from 32 bits down to 8 with
|
|
minimal loss of accuracy.</p></div></div><div class="top"><p class="src"><a name="v:quantizeDownAndShrinkRange-39-" class="def">quantizeDownAndShrinkRange'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input_min</strong>: The float value that the minimum quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input_max</strong>: The float value that the maximum quantized input value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>output_min</strong>, <strong>output_max</strong>)</p><ul><li><strong>output</strong></li><li><strong>output_min</strong>: The float value that the minimum quantized output value represents.</li><li><strong>output_max</strong>: The float value that the maximum quantized output value represents.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:quantizeV2" class="def">quantizeV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_range</strong>: The minimum scalar value possibly produced for the input.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_range</strong>: The maximum scalar value possibly produced for the input.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>output_min</strong>, <strong>output_max</strong>)</p><ul><li><strong>output</strong>: The quantized data produced from the float input.</li><li><strong>output_min</strong>: The actual minimum scalar value used for the output.</li><li><strong>output_max</strong>: The actual maximum scalar value used for the output.</li></ul></td></tr></table></div><div class="doc"><p>Quantize the <code>input</code> tensor of type float to <code>output</code> tensor of type <code>T</code>.</p><dl><dt>min_range, max_range</dt><dd>are scalar floats that specify the range for
|
|
the <code>input</code> data. The <code>mode</code> attribute controls exactly which calculations are
|
|
used to convert the float values to their quantized equivalents.</dd></dl><p>In <code>MIN_COMBINED</code> mode, each value of the tensor will undergo the following:</p><p>```
|
|
out[i] = (in[i] - min_range) * range(T) / (max_range - min_range)
|
|
if T == qint8, out[i] -= (range(T) + 1) / 2.0
|
|
```
|
|
here `range(T) = numeric_limits<a href="T">T</a>::max() - numeric_limits<a href="T">T</a>::min()`</p><ul><li>MIN_COMBINED Mode Example*</li></ul><p>Assume the input is type float and has a possible range of [0.0, 6.0] and the
|
|
output type is quint8 ([0, 255]). The min_range and max_range values should be
|
|
specified as 0.0 and 6.0. Quantizing from float to quint8 will multiply each
|
|
value of the input by 255/6 and cast to quint8.</p><p>If the output type was qint8 ([-128, 127]), the operation will additionally
|
|
subtract each value by 128 prior to casting, so that the range of values aligns
|
|
with the range of qint8.</p><p>If the mode is <code>MIN_FIRST</code>, then this approach is used:</p><p>```
|
|
number_of_steps = 1 << (# of bits in T)
|
|
range_adjust = number_of_steps / (number_of_steps - 1)
|
|
range = (range_max - range_min) * range_adjust
|
|
range_scale = number_of_steps / range
|
|
quantized = round(input * range_scale) - round(range_min * range_scale) +
|
|
numeric_limits<a href="T">T</a>::min()
|
|
quantized = max(quantized, numeric_limits<a href="T">T</a>::min())
|
|
quantized = min(quantized, numeric_limits<a href="T">T</a>::max())
|
|
```</p><p>The biggest difference between this and MIN_COMBINED is that the minimum range
|
|
is rounded first, before it's subtracted from the rounded value. With
|
|
MIN_COMBINED, a small bias is introduced where repeated iterations of quantizing
|
|
and dequantizing will introduce a larger and larger error.</p><p>One thing to watch out for is that the operator may choose to adjust the
|
|
requested minimum and maximum values slightly during the quantization process,
|
|
so you should always use the output ports as the range for further calculations.
|
|
For example, if the requested minimum and maximum values are close to equal,
|
|
they will be separated by a small epsilon value to prevent ill-formed quantized
|
|
buffers from being created. Otherwise, you can end up with buffers where all the
|
|
quantized values map to the same float value, which causes problems for
|
|
operations that have to perform further calculations on them.</p></div></div><div class="top"><p class="src"><a name="v:quantizeV2-39-" class="def">quantizeV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_range</strong>: The minimum scalar value possibly produced for the input.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_range</strong>: The maximum scalar value possibly produced for the input.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>output_min</strong>, <strong>output_max</strong>)</p><ul><li><strong>output</strong>: The quantized data produced from the float input.</li><li><strong>output_min</strong>: The actual minimum scalar value used for the output.</li><li><strong>output_max</strong>: The actual maximum scalar value used for the output.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:quantizedAvgPool" class="def">quantizedAvgPool</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_input</strong>: The float value that the lowest quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_input</strong>: The float value that the highest quantized input value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>min_output</strong>, <strong>max_output</strong>)</p><ul><li><strong>output</strong></li><li><strong>min_output</strong>: The float value that the lowest quantized output value represents.</li><li><strong>max_output</strong>: The float value that the highest quantized output value represents.</li></ul></td></tr></table></div><div class="doc"><p>Produces the average pool of the input tensor for quantized types.</p></div></div><div class="top"><p class="src"><a name="v:quantizedAvgPool-39-" class="def">quantizedAvgPool'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_input</strong>: The float value that the lowest quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_input</strong>: The float value that the highest quantized input value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>min_output</strong>, <strong>max_output</strong>)</p><ul><li><strong>output</strong></li><li><strong>min_output</strong>: The float value that the lowest quantized output value represents.</li><li><strong>max_output</strong>: The float value that the highest quantized output value represents.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:quantizedBatchNormWithGlobalNormalization" class="def">quantizedBatchNormWithGlobalNormalization</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>scale_after_normalization</strong>: A bool indicating whether the resulted tensor
|
|
needs to be multiplied with gamma.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>variance_epsilon</strong>: A small float number to avoid dividing by 0.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput</td><td class="doc"><p><strong>t</strong>: A 4D input Tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>t_min</strong>: The value represented by the lowest quantized input.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>t_max</strong>: The value represented by the highest quantized input.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 tinput</td><td class="doc"><p><strong>m</strong>: A 1D mean Tensor with size matching the last dimension of t.
|
|
This is the first output from tf.nn.moments,
|
|
or a saved moving average thereof.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>m_min</strong>: The value represented by the lowest quantized mean.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>m_max</strong>: The value represented by the highest quantized mean.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 tinput</td><td class="doc"><p><strong>v</strong>: A 1D variance Tensor with size matching the last dimension of t.
|
|
This is the second output from tf.nn.moments,
|
|
or a saved moving average thereof.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>v_min</strong>: The value represented by the lowest quantized variance.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>v_max</strong>: The value represented by the highest quantized variance.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 tinput</td><td class="doc"><p><strong>beta</strong>: A 1D beta Tensor with size matching the last dimension of t.
|
|
An offset to be added to the normalized tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'11 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>beta_min</strong>: The value represented by the lowest quantized offset.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'12 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>beta_max</strong>: The value represented by the highest quantized offset.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'13 tinput</td><td class="doc"><p><strong>gamma</strong>: A 1D gamma Tensor with size matching the last dimension of t.
|
|
If "scale_after_normalization" is true, this tensor will be multiplied
|
|
with the normalized tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'14 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>gamma_min</strong>: The value represented by the lowest quantized gamma.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'15 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>gamma_max</strong>: The value represented by the highest quantized gamma.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>result</strong>, <strong>result_min</strong>, <strong>result_max</strong>)</p><ul><li><strong>result</strong></li><li><strong>result_min</strong></li><li><strong>result_max</strong></li></ul></td></tr></table></div><div class="doc"><p>Quantized Batch normalization.</p><p>This op is deprecated and will be removed in the future. Prefer
|
|
`tf.nn.batch_normalization`.</p></div></div><div class="top"><p class="src"><a name="v:quantizedBatchNormWithGlobalNormalization-39-" class="def">quantizedBatchNormWithGlobalNormalization'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>scale_after_normalization</strong>: A bool indicating whether the resulted tensor
|
|
needs to be multiplied with gamma.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>variance_epsilon</strong>: A small float number to avoid dividing by 0.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput</td><td class="doc"><p><strong>t</strong>: A 4D input Tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>t_min</strong>: The value represented by the lowest quantized input.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>t_max</strong>: The value represented by the highest quantized input.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 tinput</td><td class="doc"><p><strong>m</strong>: A 1D mean Tensor with size matching the last dimension of t.
|
|
This is the first output from tf.nn.moments,
|
|
or a saved moving average thereof.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>m_min</strong>: The value represented by the lowest quantized mean.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>m_max</strong>: The value represented by the highest quantized mean.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 tinput</td><td class="doc"><p><strong>v</strong>: A 1D variance Tensor with size matching the last dimension of t.
|
|
This is the second output from tf.nn.moments,
|
|
or a saved moving average thereof.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>v_min</strong>: The value represented by the lowest quantized variance.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>v_max</strong>: The value represented by the highest quantized variance.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 tinput</td><td class="doc"><p><strong>beta</strong>: A 1D beta Tensor with size matching the last dimension of t.
|
|
An offset to be added to the normalized tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'11 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>beta_min</strong>: The value represented by the lowest quantized offset.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'12 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>beta_max</strong>: The value represented by the highest quantized offset.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'13 tinput</td><td class="doc"><p><strong>gamma</strong>: A 1D gamma Tensor with size matching the last dimension of t.
|
|
If "scale_after_normalization" is true, this tensor will be multiplied
|
|
with the normalized tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'14 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>gamma_min</strong>: The value represented by the lowest quantized gamma.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'15 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>gamma_max</strong>: The value represented by the highest quantized gamma.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>result</strong>, <strong>result_min</strong>, <strong>result_max</strong>)</p><ul><li><strong>result</strong></li><li><strong>result_min</strong></li><li><strong>result_max</strong></li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:quantizedBiasAdd" class="def">quantizedBiasAdd</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t1, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t2, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t1</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t2</td><td class="doc"><p><strong>bias</strong>: A 1D bias Tensor with size matching the last dimension of <code>input</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_input</strong>: The float value that the lowest quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_input</strong>: The float value that the highest quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_bias</strong>: The float value that the lowest quantized bias value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_bias</strong>: The float value that the highest quantized bias value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>min_out</strong>, <strong>max_out</strong>)</p><ul><li><strong>output</strong></li><li><strong>min_out</strong>: The float value that the lowest quantized output value represents.</li><li><strong>max_out</strong>: The float value that the highest quantized output value represents.</li></ul></td></tr></table></div><div class="doc"><p>Adds Tensor <code>bias</code> to Tensor <code>input</code> for Quantized types.</p><p>Broadcasts the values of bias on dimensions 0..N-2 of <code>input</code>.</p></div></div><div class="top"><p class="src"><a name="v:quantizedBiasAdd-39-" class="def">quantizedBiasAdd'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t1, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t2, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t1</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t2</td><td class="doc"><p><strong>bias</strong>: A 1D bias Tensor with size matching the last dimension of <code>input</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_input</strong>: The float value that the lowest quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_input</strong>: The float value that the highest quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_bias</strong>: The float value that the lowest quantized bias value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_bias</strong>: The float value that the highest quantized bias value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>min_out</strong>, <strong>max_out</strong>)</p><ul><li><strong>output</strong></li><li><strong>min_out</strong>: The float value that the lowest quantized output value represents.</li><li><strong>max_out</strong>: The float value that the highest quantized output value represents.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:quantizedConcat" class="def">quantizedConcat</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>concat_dim</strong>: 0-D. The dimension along which to concatenate. Must be in the
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range [0, rank(values)).</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t]</td><td class="doc"><p><strong>values</strong>: The <code>N</code> Tensors to concatenate. Their ranks and types must match,
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and their sizes must match in all dimensions except <code>concat_dim</code>.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]</td><td class="doc"><p><strong>input_mins</strong>: The minimum scalar values for each of the input tensors.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]</td><td class="doc"><p><strong>input_maxes</strong>: The maximum scalar values for each of the input tensors.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>output_min</strong>, <strong>output_max</strong>)</p><ul><li><strong>output</strong>: A <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with the concatenation of values stacked along the
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<code>concat_dim</code> dimension. This tensor's shape matches that of <code>values</code> except
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in <code>concat_dim</code> where it has the sum of the sizes.</li><li><strong>output_min</strong>: The float value that the minimum quantized output value represents.</li><li><strong>output_max</strong>: The float value that the maximum quantized output value represents.</li></ul></td></tr></table></div><div class="doc"><p>Concatenates quantized tensors along one dimension.</p></div></div><div class="top"><p class="src"><a name="v:quantizedConcat-39-" class="def">quantizedConcat'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>concat_dim</strong>: 0-D. The dimension along which to concatenate. Must be in the
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range [0, rank(values)).</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t]</td><td class="doc"><p><strong>values</strong>: The <code>N</code> Tensors to concatenate. Their ranks and types must match,
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and their sizes must match in all dimensions except <code>concat_dim</code>.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]</td><td class="doc"><p><strong>input_mins</strong>: The minimum scalar values for each of the input tensors.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]</td><td class="doc"><p><strong>input_maxes</strong>: The maximum scalar values for each of the input tensors.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>output_min</strong>, <strong>output_max</strong>)</p><ul><li><strong>output</strong>: A <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with the concatenation of values stacked along the
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|
<code>concat_dim</code> dimension. This tensor's shape matches that of <code>values</code> except
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in <code>concat_dim</code> where it has the sum of the sizes.</li><li><strong>output_min</strong>: The float value that the minimum quantized output value represents.</li><li><strong>output_max</strong>: The float value that the maximum quantized output value represents.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:quantizedConv2D" class="def">quantizedConv2D</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tfilter, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tfilter</td><td class="doc"><p><strong>filter</strong>: filter's input_depth dimension must match input's depth dimensions.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_input</strong>: The float value that the lowest quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_input</strong>: The float value that the highest quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_filter</strong>: The float value that the lowest quantized filter value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_filter</strong>: The float value that the highest quantized filter value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>min_output</strong>, <strong>max_output</strong>)</p><ul><li><strong>output</strong></li><li><strong>min_output</strong>: The float value that the lowest quantized output value represents.</li><li><strong>max_output</strong>: The float value that the highest quantized output value represents.</li></ul></td></tr></table></div><div class="doc"><p>Computes a 2D convolution given quantized 4D input and filter tensors.</p><p>The inputs are quantized tensors where the lowest value represents the real
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number of the associated minimum, and the highest represents the maximum.
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This means that you can only interpret the quantized output in the same way, by
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taking the returned minimum and maximum values into account.</p></div></div><div class="top"><p class="src"><a name="v:quantizedConv2D-39-" class="def">quantizedConv2D'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tfilter, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tfilter</td><td class="doc"><p><strong>filter</strong>: filter's input_depth dimension must match input's depth dimensions.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_input</strong>: The float value that the lowest quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_input</strong>: The float value that the highest quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_filter</strong>: The float value that the lowest quantized filter value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_filter</strong>: The float value that the highest quantized filter value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>min_output</strong>, <strong>max_output</strong>)</p><ul><li><strong>output</strong></li><li><strong>min_output</strong>: The float value that the lowest quantized output value represents.</li><li><strong>max_output</strong>: The float value that the highest quantized output value represents.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:quantizedInstanceNorm" class="def">quantizedInstanceNorm</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong>: A 4D input Tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>x_min</strong>: The value represented by the lowest quantized input.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>x_max</strong>: The value represented by the highest quantized input.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>y</strong>, <strong>y_min</strong>, <strong>y_max</strong>)</p><ul><li><strong>y</strong>: A 4D Tensor.</li><li><strong>y_min</strong>: The value represented by the lowest quantized output.</li><li><strong>y_max</strong>: The value represented by the highest quantized output.</li></ul></td></tr></table></div><div class="doc"><p>Quantized Instance normalization.</p></div></div><div class="top"><p class="src"><a name="v:quantizedInstanceNorm-39-" class="def">quantizedInstanceNorm'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong>: A 4D input Tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>x_min</strong>: The value represented by the lowest quantized input.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>x_max</strong>: The value represented by the highest quantized input.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>y</strong>, <strong>y_min</strong>, <strong>y_max</strong>)</p><ul><li><strong>y</strong>: A 4D Tensor.</li><li><strong>y_min</strong>: The value represented by the lowest quantized output.</li><li><strong>y_max</strong>: The value represented by the highest quantized output.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:quantizedMatMul" class="def">quantizedMatMul</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t1, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t2, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` toutput)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t1</td><td class="doc"><p><strong>a</strong>: Must be a two-dimensional tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t2</td><td class="doc"><p><strong>b</strong>: Must be a two-dimensional tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_a</strong>: The float value that the lowest quantized <code>a</code> value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_a</strong>: The float value that the highest quantized <code>a</code> value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_b</strong>: The float value that the lowest quantized <code>b</code> value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_b</strong>: The float value that the highest quantized <code>b</code> value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> toutput, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>out</strong>, <strong>min_out</strong>, <strong>max_out</strong>)</p><ul><li><strong>out</strong></li><li><strong>min_out</strong>: The float value that the lowest quantized output value represents.</li><li><strong>max_out</strong>: The float value that the highest quantized output value represents.</li></ul></td></tr></table></div><div class="doc"><p>Perform a quantized matrix multiplication of <code>a</code> by the matrix <code>b</code>.</p><p>The inputs must be two-dimensional matrices and the inner dimension of
|
|
<code>a</code> (after being transposed if <code>transpose_a</code> is non-zero) must match the
|
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outer dimension of <code>b</code> (after being transposed if <code>transposed_b</code> is
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|
non-zero).</p></div></div><div class="top"><p class="src"><a name="v:quantizedMatMul-39-" class="def">quantizedMatMul'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t1, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t2, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` toutput)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t1</td><td class="doc"><p><strong>a</strong>: Must be a two-dimensional tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t2</td><td class="doc"><p><strong>b</strong>: Must be a two-dimensional tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_a</strong>: The float value that the lowest quantized <code>a</code> value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_a</strong>: The float value that the highest quantized <code>a</code> value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_b</strong>: The float value that the lowest quantized <code>b</code> value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_b</strong>: The float value that the highest quantized <code>b</code> value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> toutput, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>out</strong>, <strong>min_out</strong>, <strong>max_out</strong>)</p><ul><li><strong>out</strong></li><li><strong>min_out</strong>: The float value that the lowest quantized output value represents.</li><li><strong>max_out</strong>: The float value that the highest quantized output value represents.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:quantizedMaxPool" class="def">quantizedMaxPool</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The 4D (batch x rows x cols x depth) Tensor to MaxReduce over.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_input</strong>: The float value that the lowest quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_input</strong>: The float value that the highest quantized input value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>min_output</strong>, <strong>max_output</strong>)</p><ul><li><strong>output</strong></li><li><strong>min_output</strong>: The float value that the lowest quantized output value represents.</li><li><strong>max_output</strong>: The float value that the highest quantized output value represents.</li></ul></td></tr></table></div><div class="doc"><p>Produces the max pool of the input tensor for quantized types.</p></div></div><div class="top"><p class="src"><a name="v:quantizedMaxPool-39-" class="def">quantizedMaxPool'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The 4D (batch x rows x cols x depth) Tensor to MaxReduce over.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_input</strong>: The float value that the lowest quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_input</strong>: The float value that the highest quantized input value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>min_output</strong>, <strong>max_output</strong>)</p><ul><li><strong>output</strong></li><li><strong>min_output</strong>: The float value that the lowest quantized output value represents.</li><li><strong>max_output</strong>: The float value that the highest quantized output value represents.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:quantizedRelu" class="def">quantizedRelu</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput</td><td class="doc"><p><strong>features</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_features</strong>: The float value that the lowest quantized value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_features</strong>: The float value that the highest quantized value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>activations</strong>, <strong>min_activations</strong>, <strong>max_activations</strong>)</p><ul><li><strong>activations</strong>: Has the same output shape as "features".</li><li><strong>min_activations</strong>: The float value that the lowest quantized value represents.</li><li><strong>max_activations</strong>: The float value that the highest quantized value represents.</li></ul></td></tr></table></div><div class="doc"><p>Computes Quantized Rectified Linear: `max(features, 0)`</p></div></div><div class="top"><p class="src"><a name="v:quantizedRelu-39-" class="def">quantizedRelu'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput</td><td class="doc"><p><strong>features</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_features</strong>: The float value that the lowest quantized value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_features</strong>: The float value that the highest quantized value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>activations</strong>, <strong>min_activations</strong>, <strong>max_activations</strong>)</p><ul><li><strong>activations</strong>: Has the same output shape as "features".</li><li><strong>min_activations</strong>: The float value that the lowest quantized value represents.</li><li><strong>max_activations</strong>: The float value that the highest quantized value represents.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:quantizedRelu6" class="def">quantizedRelu6</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput</td><td class="doc"><p><strong>features</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_features</strong>: The float value that the lowest quantized value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_features</strong>: The float value that the highest quantized value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>activations</strong>, <strong>min_activations</strong>, <strong>max_activations</strong>)</p><ul><li><strong>activations</strong>: Has the same output shape as "features".</li><li><strong>min_activations</strong>: The float value that the lowest quantized value represents.</li><li><strong>max_activations</strong>: The float value that the highest quantized value represents.</li></ul></td></tr></table></div><div class="doc"><p>Computes Quantized Rectified Linear 6: `min(max(features, 0), 6)`</p></div></div><div class="top"><p class="src"><a name="v:quantizedRelu6-39-" class="def">quantizedRelu6'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput</td><td class="doc"><p><strong>features</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_features</strong>: The float value that the lowest quantized value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_features</strong>: The float value that the highest quantized value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>activations</strong>, <strong>min_activations</strong>, <strong>max_activations</strong>)</p><ul><li><strong>activations</strong>: Has the same output shape as "features".</li><li><strong>min_activations</strong>: The float value that the lowest quantized value represents.</li><li><strong>max_activations</strong>: The float value that the highest quantized value represents.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:quantizedReluX" class="def">quantizedReluX</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput</td><td class="doc"><p><strong>features</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_features</strong>: The float value that the lowest quantized value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_features</strong>: The float value that the highest quantized value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>activations</strong>, <strong>min_activations</strong>, <strong>max_activations</strong>)</p><ul><li><strong>activations</strong>: Has the same output shape as "features".</li><li><strong>min_activations</strong>: The float value that the lowest quantized value represents.</li><li><strong>max_activations</strong>: The float value that the highest quantized value represents.</li></ul></td></tr></table></div><div class="doc"><p>Computes Quantized Rectified Linear X: `min(max(features, 0), max_value)`</p></div></div><div class="top"><p class="src"><a name="v:quantizedReluX-39-" class="def">quantizedReluX'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput</td><td class="doc"><p><strong>features</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>min_features</strong>: The float value that the lowest quantized value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>max_features</strong>: The float value that the highest quantized value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>activations</strong>, <strong>min_activations</strong>, <strong>max_activations</strong>)</p><ul><li><strong>activations</strong>: Has the same output shape as "features".</li><li><strong>min_activations</strong>: The float value that the lowest quantized value represents.</li><li><strong>max_activations</strong>: The float value that the highest quantized value represents.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:quantizedReshape" class="def">quantizedReshape</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tshape)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>tensor</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tshape</td><td class="doc"><p><strong>shape</strong>: Defines the shape of the output tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input_min</strong>: The minimum value of the input.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input_max</strong>: The maximum value of the input.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>output_min</strong>, <strong>output_max</strong>)</p><ul><li><strong>output</strong></li><li><strong>output_min</strong>: This value is copied from input_min.</li><li><strong>output_max</strong>: This value is copied from input_max.</li></ul></td></tr></table></div><div class="doc"><p>Reshapes a quantized tensor as per the Reshape op.</p><p>```</p></div></div><div class="top"><p class="src"><a name="v:quantizedReshape-39-" class="def">quantizedReshape'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tshape)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>tensor</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tshape</td><td class="doc"><p><strong>shape</strong>: Defines the shape of the output tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input_min</strong>: The minimum value of the input.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input_max</strong>: The maximum value of the input.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>output_min</strong>, <strong>output_max</strong>)</p><ul><li><strong>output</strong></li><li><strong>output_min</strong>: This value is copied from input_min.</li><li><strong>output_max</strong>: This value is copied from input_max.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:queueClose" class="def">queueClose</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Closes the given queue.</p><p>This operation signals that no more elements will be enqueued in the
|
|
given queue. Subsequent Enqueue(Many) operations will fail.
|
|
Subsequent Dequeue(Many) operations will continue to succeed if
|
|
sufficient elements remain in the queue. Subsequent Dequeue(Many)
|
|
operations that would block will fail immediately.</p></div></div><div class="top"><p class="src"><a name="v:queueClose-39-" class="def">queueClose'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:queueCloseV2" class="def">queueCloseV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Closes the given queue.</p><p>This operation signals that no more elements will be enqueued in the
|
|
given queue. Subsequent Enqueue(Many) operations will fail.
|
|
Subsequent Dequeue(Many) operations will continue to succeed if
|
|
sufficient elements remain in the queue. Subsequent Dequeue(Many)
|
|
operations that would block will fail immediately.</p></div></div><div class="top"><p class="src"><a name="v:queueCloseV2-39-" class="def">queueCloseV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:queueDequeue" class="def">queueDequeue</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</td><td class="doc"><p><strong>components</strong>: One or more tensors that were dequeued as a tuple.</p></td></tr></table></div><div class="doc"><p>Dequeues a tuple of one or more tensors from the given queue.</p><p>This operation has k outputs, where k is the number of components
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|
in the tuples stored in the given queue, and output i is the ith
|
|
component of the dequeued tuple.</p><p>N.B. If the queue is empty, this operation will block until an element
|
|
has been dequeued (or <code>timeout_ms</code> elapses, if specified).</p></div></div><div class="top"><p class="src"><a name="v:queueDequeue-39-" class="def">queueDequeue'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</td><td class="doc"><p><strong>components</strong>: One or more tensors that were dequeued as a tuple.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:queueDequeueMany" class="def">queueDequeueMany</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>n</strong>: The number of tuples to dequeue.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</td><td class="doc"><p><strong>components</strong>: One or more tensors that were dequeued as a tuple.</p></td></tr></table></div><div class="doc"><p>Dequeues n tuples of one or more tensors from the given queue.</p><p>If the queue is closed and there are fewer than n elements, then an
|
|
OutOfRange error is returned.</p><p>This operation concatenates queue-element component tensors along the
|
|
0th dimension to make a single component tensor. All of the components
|
|
in the dequeued tuple will have size n in the 0th dimension.</p><p>This operation has k outputs, where k is the number of components in
|
|
the tuples stored in the given queue, and output i is the ith
|
|
component of the dequeued tuple.</p><p>N.B. If the queue is empty, this operation will block until n elements
|
|
have been dequeued (or <code>timeout_ms</code> elapses, if specified).</p></div></div><div class="top"><p class="src"><a name="v:queueDequeueMany-39-" class="def">queueDequeueMany'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>n</strong>: The number of tuples to dequeue.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</td><td class="doc"><p><strong>components</strong>: One or more tensors that were dequeued as a tuple.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:queueDequeueManyV2" class="def">queueDequeueManyV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>n</strong>: The number of tuples to dequeue.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</td><td class="doc"><p><strong>components</strong>: One or more tensors that were dequeued as a tuple.</p></td></tr></table></div><div class="doc"><p>Dequeues n tuples of one or more tensors from the given queue.</p><p>If the queue is closed and there are fewer than n elements, then an
|
|
OutOfRange error is returned.</p><p>This operation concatenates queue-element component tensors along the
|
|
0th dimension to make a single component tensor. All of the components
|
|
in the dequeued tuple will have size n in the 0th dimension.</p><p>This operation has k outputs, where k is the number of components in
|
|
the tuples stored in the given queue, and output i is the ith
|
|
component of the dequeued tuple.</p><p>N.B. If the queue is empty, this operation will block until n elements
|
|
have been dequeued (or <code>timeout_ms</code> elapses, if specified).</p></div></div><div class="top"><p class="src"><a name="v:queueDequeueManyV2-39-" class="def">queueDequeueManyV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>n</strong>: The number of tuples to dequeue.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</td><td class="doc"><p><strong>components</strong>: One or more tensors that were dequeued as a tuple.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:queueDequeueUpTo" class="def">queueDequeueUpTo</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>n</strong>: The number of tuples to dequeue.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</td><td class="doc"><p><strong>components</strong>: One or more tensors that were dequeued as a tuple.</p></td></tr></table></div><div class="doc"><p>Dequeues n tuples of one or more tensors from the given queue.</p><p>This operation is not supported by all queues. If a queue does not support
|
|
DequeueUpTo, then an Unimplemented error is returned.</p><p>If the queue is closed and there are more than 0 but less than n elements
|
|
remaining, then instead of returning an OutOfRange error like
|
|
QueueDequeueMany, less than <code>n</code> elements are returned immediately. If the queue
|
|
is closed and there are 0 elements left in the queue, then an OutOfRange
|
|
error is returned just like in QueueDequeueMany. Otherwise the behavior
|
|
is identical to QueueDequeueMany:</p><p>This operation concatenates queue-element component tensors along the
|
|
0th dimension to make a single component tensor. All of the components
|
|
in the dequeued tuple will have size n in the 0th dimension.</p><p>This operation has k outputs, where k is the number of components in
|
|
the tuples stored in the given queue, and output i is the ith
|
|
component of the dequeued tuple.</p></div></div><div class="top"><p class="src"><a name="v:queueDequeueUpTo-39-" class="def">queueDequeueUpTo'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>n</strong>: The number of tuples to dequeue.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</td><td class="doc"><p><strong>components</strong>: One or more tensors that were dequeued as a tuple.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:queueDequeueUpToV2" class="def">queueDequeueUpToV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>n</strong>: The number of tuples to dequeue.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</td><td class="doc"><p><strong>components</strong>: One or more tensors that were dequeued as a tuple.</p></td></tr></table></div><div class="doc"><p>Dequeues n tuples of one or more tensors from the given queue.</p><p>This operation is not supported by all queues. If a queue does not support
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|
DequeueUpTo, then an Unimplemented error is returned.</p><p>If the queue is closed and there are more than 0 but less than n elements
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|
remaining, then instead of returning an OutOfRange error like
|
|
QueueDequeueMany, less than <code>n</code> elements are returned immediately. If the queue
|
|
is closed and there are 0 elements left in the queue, then an OutOfRange
|
|
error is returned just like in QueueDequeueMany. Otherwise the behavior
|
|
is identical to QueueDequeueMany:</p><p>This operation concatenates queue-element component tensors along the
|
|
0th dimension to make a single component tensor. All of the components
|
|
in the dequeued tuple will have size n in the 0th dimension.</p><p>This operation has k outputs, where k is the number of components in
|
|
the tuples stored in the given queue, and output i is the ith
|
|
component of the dequeued tuple.</p></div></div><div class="top"><p class="src"><a name="v:queueDequeueUpToV2-39-" class="def">queueDequeueUpToV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>n</strong>: The number of tuples to dequeue.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</td><td class="doc"><p><strong>components</strong>: One or more tensors that were dequeued as a tuple.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:queueDequeueV2" class="def">queueDequeueV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</td><td class="doc"><p><strong>components</strong>: One or more tensors that were dequeued as a tuple.</p></td></tr></table></div><div class="doc"><p>Dequeues a tuple of one or more tensors from the given queue.</p><p>This operation has k outputs, where k is the number of components
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|
in the tuples stored in the given queue, and output i is the ith
|
|
component of the dequeued tuple.</p><p>N.B. If the queue is empty, this operation will block until an element
|
|
has been dequeued (or <code>timeout_ms</code> elapses, if specified).</p></div></div><div class="top"><p class="src"><a name="v:queueDequeueV2-39-" class="def">queueDequeueV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> component_types)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> component_types)</td><td class="doc"><p><strong>components</strong>: One or more tensors that were dequeued as a tuple.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:queueEnqueue" class="def">queueEnqueue</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tcomponents)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 tcomponents</td><td class="doc"><p><strong>components</strong>: One or more tensors from which the enqueued tensors should be taken.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Enqueues a tuple of one or more tensors in the given queue.</p><p>The components input has k elements, which correspond to the components of
|
|
tuples stored in the given queue.</p><p>N.B. If the queue is full, this operation will block until the given
|
|
element has been enqueued (or <code>timeout_ms</code> elapses, if specified).</p></div></div><div class="top"><p class="src"><a name="v:queueEnqueue-39-" class="def">queueEnqueue'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tcomponents)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 tcomponents</td><td class="doc"><p><strong>components</strong>: One or more tensors from which the enqueued tensors should be taken.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:queueEnqueueMany" class="def">queueEnqueueMany</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tcomponents)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 tcomponents</td><td class="doc"><p><strong>components</strong>: One or more tensors from which the enqueued tensors should
|
|
be taken.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Enqueues zero or more tuples of one or more tensors in the given queue.</p><p>This operation slices each component tensor along the 0th dimension to
|
|
make multiple queue elements. All of the tuple components must have the
|
|
same size in the 0th dimension.</p><p>The components input has k elements, which correspond to the components of
|
|
tuples stored in the given queue.</p><p>N.B. If the queue is full, this operation will block until the given
|
|
elements have been enqueued (or <code>timeout_ms</code> elapses, if specified).</p></div></div><div class="top"><p class="src"><a name="v:queueEnqueueMany-39-" class="def">queueEnqueueMany'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tcomponents)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 tcomponents</td><td class="doc"><p><strong>components</strong>: One or more tensors from which the enqueued tensors should
|
|
be taken.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:queueEnqueueManyV2" class="def">queueEnqueueManyV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tcomponents)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 tcomponents</td><td class="doc"><p><strong>components</strong>: One or more tensors from which the enqueued tensors should
|
|
be taken.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Enqueues zero or more tuples of one or more tensors in the given queue.</p><p>This operation slices each component tensor along the 0th dimension to
|
|
make multiple queue elements. All of the tuple components must have the
|
|
same size in the 0th dimension.</p><p>The components input has k elements, which correspond to the components of
|
|
tuples stored in the given queue.</p><p>N.B. If the queue is full, this operation will block until the given
|
|
elements have been enqueued (or <code>timeout_ms</code> elapses, if specified).</p></div></div><div class="top"><p class="src"><a name="v:queueEnqueueManyV2-39-" class="def">queueEnqueueManyV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tcomponents)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 tcomponents</td><td class="doc"><p><strong>components</strong>: One or more tensors from which the enqueued tensors should
|
|
be taken.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:queueEnqueueV2" class="def">queueEnqueueV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tcomponents)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 tcomponents</td><td class="doc"><p><strong>components</strong>: One or more tensors from which the enqueued tensors should be taken.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Enqueues a tuple of one or more tensors in the given queue.</p><p>The components input has k elements, which correspond to the components of
|
|
tuples stored in the given queue.</p><p>N.B. If the queue is full, this operation will block until the given
|
|
element has been enqueued (or <code>timeout_ms</code> elapses, if specified).</p></div></div><div class="top"><p class="src"><a name="v:queueEnqueueV2-39-" class="def">queueEnqueueV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tcomponents)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'2 tcomponents</td><td class="doc"><p><strong>components</strong>: One or more tensors from which the enqueued tensors should be taken.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:queueSize" class="def">queueSize</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p><strong>size</strong>: The number of elements in the given queue.</p></td></tr></table></div><div class="doc"><p>Computes the number of elements in the given queue.</p></div></div><div class="top"><p class="src"><a name="v:queueSize-39-" class="def">queueSize'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p><strong>size</strong>: The number of elements in the given queue.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:queueSizeV2" class="def">queueSizeV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p><strong>size</strong>: The number of elements in the given queue.</p></td></tr></table></div><div class="doc"><p>Computes the number of elements in the given queue.</p></div></div><div class="top"><p class="src"><a name="v:queueSizeV2-39-" class="def">queueSizeV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a queue.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p><strong>size</strong>: The number of elements in the given queue.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:rGBToHSV" class="def">rGBToHSV</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>images</strong>: 1-D or higher rank. RGB data to convert. Last dimension must be size 3.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: <code>images</code> converted to HSV.</p></td></tr></table></div><div class="doc"><p>Converts one or more images from RGB to HSV.</p><p>Outputs a tensor of the same shape as the <code>images</code> tensor, containing the HSV
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value of the pixels. The output is only well defined if the value in <code>images</code>
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are in `[0,1]`.</p><p>`output[..., 0]` contains hue, `output[..., 1]` contains saturation, and
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`output[..., 2]` contains value. All HSV values are in `[0,1]`. A hue of 0
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corresponds to pure red, hue 1<em>3 is pure green, and 2</em>3 is pure blue.</p></div></div><div class="top"><p class="src"><a name="v:rGBToHSV-39-" class="def">rGBToHSV'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>images</strong>: 1-D or higher rank. RGB data to convert. Last dimension must be size 3.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: <code>images</code> converted to HSV.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:randomCrop" class="def">randomCrop</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>image</strong>: 3-D of shape `[height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>size</strong>: 1-D of length 2 containing: <code>crop_height</code>, <code>crop_width</code>..</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</td><td class="doc"><p><strong>output</strong>: 3-D of shape `[crop_height, crop_width, channels].`</p></td></tr></table></div><div class="doc"><p>Randomly crop <code>image</code>.</p><p><code><a href="TensorFlow-GenOps-Core.html#v:size">size</a></code> is a 1-D int64 tensor with 2 elements representing the crop height and
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width. The values must be non negative.</p><p>This Op picks a random location in <code>image</code> and crops a <code>height</code> by <code>width</code>
|
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rectangle from that location. The random location is picked so the cropped
|
|
area will fit inside the original image.</p></div></div><div class="top"><p class="src"><a name="v:randomCrop-39-" class="def">randomCrop'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>image</strong>: 3-D of shape `[height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>size</strong>: 1-D of length 2 containing: <code>crop_height</code>, <code>crop_width</code>..</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</td><td class="doc"><p><strong>output</strong>: 3-D of shape `[crop_height, crop_width, channels].`</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:randomGamma" class="def">randomGamma</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` s, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 s</td><td class="doc"><p><strong>shape</strong>: 1-D integer tensor. Shape of independent samples to draw from each
|
|
distribution described by the shape parameters given in alpha.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>alpha</strong>: A tensor in which each scalar is a "shape" parameter describing the
|
|
associated gamma distribution.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</td><td class="doc"><p><strong>output</strong>: A tensor with shape `shape + shape(alpha)`. Each slice
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|
`[:, ..., :, i0, i1, ...iN]` contains the samples drawn for
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|
`alpha[i0, i1, ...iN]`. The dtype of the output matches the dtype of alpha.</p></td></tr></table></div><div class="doc"><p>Outputs random values from the Gamma distribution(s) described by alpha.</p><p>This op uses the algorithm by Marsaglia et al. to acquire samples via
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|
transformation-rejection from pairs of uniform and normal random variables.
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|
See <a href="http://dl.acm.org/citation.cfm?id=358414">http://dl.acm.org/citation.cfm?id=358414</a></p></div></div><div class="top"><p class="src"><a name="v:randomGamma-39-" class="def">randomGamma'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` s, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 s</td><td class="doc"><p><strong>shape</strong>: 1-D integer tensor. Shape of independent samples to draw from each
|
|
distribution described by the shape parameters given in alpha.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>alpha</strong>: A tensor in which each scalar is a "shape" parameter describing the
|
|
associated gamma distribution.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</td><td class="doc"><p><strong>output</strong>: A tensor with shape `shape + shape(alpha)`. Each slice
|
|
`[:, ..., :, i0, i1, ...iN]` contains the samples drawn for
|
|
`alpha[i0, i1, ...iN]`. The dtype of the output matches the dtype of alpha.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:randomShuffle" class="def">randomShuffle</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: The tensor to be shuffled.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</td><td class="doc"><p><strong>output</strong>: A tensor of same shape and type as <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>, shuffled along its first
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|
dimension.</p></td></tr></table></div><div class="doc"><p>Randomly shuffles a tensor along its first dimension.</p><p>The tensor is shuffled along dimension 0, such that each `value[j]` is mapped
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|
to one and only one `output[i]`. For example, a mapping that might occur for a
|
|
3x2 tensor is:</p><p>```prettyprint
|
|
[[1, 2], [[5, 6],
|
|
[3, 4], ==> [1, 2],
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|
[5, 6]] [3, 4]]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:randomShuffle-39-" class="def">randomShuffle'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: The tensor to be shuffled.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</td><td class="doc"><p><strong>output</strong>: A tensor of same shape and type as <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>, shuffled along its first
|
|
dimension.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:randomShuffleQueue" class="def">randomShuffleQueue</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>]</td><td class="doc"><p><strong>component_types</strong>: The type of each component in a value.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong>: The handle to the queue.</p></td></tr></table></div><div class="doc"><p>A queue that randomizes the order of elements.</p></div></div><div class="top"><p class="src"><a name="v:randomShuffleQueue-39-" class="def">randomShuffleQueue'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>]</td><td class="doc"><p><strong>component_types</strong>: The type of each component in a value.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong>: The handle to the queue.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:randomShuffleQueueV2" class="def">randomShuffleQueueV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>]</td><td class="doc"><p><strong>component_types</strong>: The type of each component in a value.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to the queue.</p></td></tr></table></div><div class="doc"><p>A queue that randomizes the order of elements.</p></div></div><div class="top"><p class="src"><a name="v:randomShuffleQueueV2-39-" class="def">randomShuffleQueueV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a>]</td><td class="doc"><p><strong>component_types</strong>: The type of each component in a value.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to the queue.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:randomStandardNormal" class="def">randomStandardNormal</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>shape</strong>: The shape of the output tensor.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>output</strong>: A tensor of the specified shape filled with random normal values.</p></td></tr></table></div><div class="doc"><p>Outputs random values from a normal distribution.</p><p>The generated values will have mean 0 and standard deviation 1.</p></div></div><div class="top"><p class="src"><a name="v:randomStandardNormal-39-" class="def">randomStandardNormal'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>shape</strong>: The shape of the output tensor.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>output</strong>: A tensor of the specified shape filled with random normal values.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:randomUniform" class="def">randomUniform</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>shape</strong>: The shape of the output tensor.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>output</strong>: A tensor of the specified shape filled with uniform random values.</p></td></tr></table></div><div class="doc"><p>Outputs random values from a uniform distribution.</p><p>The generated values follow a uniform distribution in the range `[0, 1)`. The
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lower bound 0 is included in the range, while the upper bound 1 is excluded.</p></div></div><div class="top"><p class="src"><a name="v:randomUniform-39-" class="def">randomUniform'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>shape</strong>: The shape of the output tensor.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>output</strong>: A tensor of the specified shape filled with uniform random values.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:randomUniformInt" class="def">randomUniformInt</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tout, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>shape</strong>: The shape of the output tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tout</td><td class="doc"><p><strong>minval</strong>: 0-D. Inclusive lower bound on the generated integers.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tout</td><td class="doc"><p><strong>maxval</strong>: 0-D. Exclusive upper bound on the generated integers.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tout)</td><td class="doc"><p><strong>output</strong>: A tensor of the specified shape filled with uniform random integers.</p></td></tr></table></div><div class="doc"><p>Outputs random integers from a uniform distribution.</p><p>The generated values are uniform integers in the range `[minval, maxval)`.
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The lower bound <code>minval</code> is included in the range, while the upper bound
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<code>maxval</code> is excluded.</p><p>The random integers are slightly biased unless `maxval - minval` is an exact
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power of two. The bias is small for values of `maxval - minval` significantly
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smaller than the range of the output (either `2^32` or `2^64`).</p></div></div><div class="top"><p class="src"><a name="v:randomUniformInt-39-" class="def">randomUniformInt'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tout, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>shape</strong>: The shape of the output tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tout</td><td class="doc"><p><strong>minval</strong>: 0-D. Inclusive lower bound on the generated integers.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tout</td><td class="doc"><p><strong>maxval</strong>: 0-D. Exclusive upper bound on the generated integers.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tout)</td><td class="doc"><p><strong>output</strong>: A tensor of the specified shape filled with uniform random integers.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:range" class="def">range</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tidx</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tidx</td><td class="doc"><p><strong>start</strong>: 0-D (scalar). First entry in the sequence.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>limit</strong>: 0-D (scalar). Upper limit of sequence, exclusive.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tidx</td><td class="doc"><p><strong>delta</strong>: 0-D (scalar). Optional. Default is 1. Number that increments <code>start</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tidx</td><td class="doc"><p><strong>output</strong>: 1-D.</p></td></tr></table></div><div class="doc"><p>Creates a sequence of numbers.</p><p>This operation creates a sequence of numbers that begins at <code>start</code> and
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extends by increments of <code>delta</code> up to but not including <code>limit</code>.</p><p>For example:</p><p>```
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# <code>start</code> is 3
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# <code>limit</code> is 18
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|
# <code>delta</code> is 3
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tf.range(start, limit, delta) ==> [3, 6, 9, 12, 15]
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```</p></div></div><div class="top"><p class="src"><a name="v:range-39-" class="def">range'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tidx</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tidx</td><td class="doc"><p><strong>start</strong>: 0-D (scalar). First entry in the sequence.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>limit</strong>: 0-D (scalar). Upper limit of sequence, exclusive.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tidx</td><td class="doc"><p><strong>delta</strong>: 0-D (scalar). Optional. Default is 1. Number that increments <code>start</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tidx</td><td class="doc"><p><strong>output</strong>: 1-D.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:rank" class="def">rank</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Returns the rank of a tensor.</p><p>This operation returns an integer representing the rank of <code>input</code>.</p><p>For example:</p><p>```prettyprint
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|
# <code>t</code> is [[[1, 1, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]]]
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# shape of tensor <code>t</code> is [2, 2, 3]
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|
rank(t) ==> 3
|
|
```</p><ul><li>*Note**: The rank of a tensor is not the same as the rank of a matrix. The rank
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|
of a tensor is the number of indices required to uniquely select each element
|
|
of the tensor. Rank is also known as "order", "degree", or "ndims."</li></ul></div></div><div class="top"><p class="src"><a name="v:rank-39-" class="def">rank'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:readFile" class="def">readFile</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>filename</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>contents</strong></p></td></tr></table></div><div class="doc"><p>Reads and outputs the entire contents of the input filename.</p></div></div><div class="top"><p class="src"><a name="v:readFile-39-" class="def">readFile'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>filename</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>contents</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:readVariableOp" class="def">readVariableOp</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>resource</strong>: handle to the resource in which to store the variable.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>value</strong></p></td></tr></table></div><div class="doc"><p>Reads the value of a variable.</p><p>The tensor returned by this operation is immutable.</p><p>The value returned by this operation is guaranteed to be influenced by all the
|
|
writes on which this operation depends directly or indirectly, and to not be
|
|
influenced by any of the writes which depend directly or indirectly on this
|
|
operation.</p></div></div><div class="top"><p class="src"><a name="v:readVariableOp-39-" class="def">readVariableOp'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>resource</strong>: handle to the resource in which to store the variable.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>value</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:readerNumRecordsProduced" class="def">readerNumRecordsProduced</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p><strong>records_produced</strong></p></td></tr></table></div><div class="doc"><p>Returns the number of records this Reader has produced.</p><p>This is the same as the number of ReaderRead executions that have
|
|
succeeded.</p></div></div><div class="top"><p class="src"><a name="v:readerNumRecordsProduced-39-" class="def">readerNumRecordsProduced'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p><strong>records_produced</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:readerNumRecordsProducedV2" class="def">readerNumRecordsProducedV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p><strong>records_produced</strong></p></td></tr></table></div><div class="doc"><p>Returns the number of records this Reader has produced.</p><p>This is the same as the number of ReaderRead executions that have
|
|
succeeded.</p></div></div><div class="top"><p class="src"><a name="v:readerNumRecordsProducedV2-39-" class="def">readerNumRecordsProducedV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p><strong>records_produced</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:readerNumWorkUnitsCompleted" class="def">readerNumWorkUnitsCompleted</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p><strong>units_completed</strong></p></td></tr></table></div><div class="doc"><p>Returns the number of work units this Reader has finished processing.</p></div></div><div class="top"><p class="src"><a name="v:readerNumWorkUnitsCompleted-39-" class="def">readerNumWorkUnitsCompleted'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p><strong>units_completed</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:readerNumWorkUnitsCompletedV2" class="def">readerNumWorkUnitsCompletedV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p><strong>units_completed</strong></p></td></tr></table></div><div class="doc"><p>Returns the number of work units this Reader has finished processing.</p></div></div><div class="top"><p class="src"><a name="v:readerNumWorkUnitsCompletedV2-39-" class="def">readerNumWorkUnitsCompletedV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p><strong>units_completed</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:readerRead" class="def">readerRead</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>queue_handle</strong>: Handle to a Queue, with string work items.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p>(<strong>key</strong>, <strong>value</strong>)</p><ul><li><strong>key</strong>: A scalar.</li><li><strong>value</strong>: A scalar.</li></ul></td></tr></table></div><div class="doc"><p>Returns the next record (key, value pair) produced by a Reader.</p><p>Will dequeue from the input queue if necessary (e.g. when the
|
|
Reader needs to start reading from a new file since it has finished
|
|
with the previous file).</p></div></div><div class="top"><p class="src"><a name="v:readerRead-39-" class="def">readerRead'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>queue_handle</strong>: Handle to a Queue, with string work items.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p>(<strong>key</strong>, <strong>value</strong>)</p><ul><li><strong>key</strong>: A scalar.</li><li><strong>value</strong>: A scalar.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:readerReadUpTo" class="def">readerReadUpTo</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a <code>Reader</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>queue_handle</strong>: Handle to a <code>Queue</code>, with string work items.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_records</strong>: number of records to read from <code>Reader</code>.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p>(<strong>keys</strong>, <strong>values</strong>)</p><ul><li><strong>keys</strong>: A 1-D tensor.</li><li><strong>values</strong>: A 1-D tensor.</li></ul></td></tr></table></div><div class="doc"><p>Returns up to <code>num_records</code> (key, value) pairs produced by a Reader.</p><p>Will dequeue from the input queue if necessary (e.g. when the
|
|
Reader needs to start reading from a new file since it has finished
|
|
with the previous file).
|
|
It may return less than <code>num_records</code> even before the last batch.</p></div></div><div class="top"><p class="src"><a name="v:readerReadUpTo-39-" class="def">readerReadUpTo'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a <code>Reader</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>queue_handle</strong>: Handle to a <code>Queue</code>, with string work items.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_records</strong>: number of records to read from <code>Reader</code>.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p>(<strong>keys</strong>, <strong>values</strong>)</p><ul><li><strong>keys</strong>: A 1-D tensor.</li><li><strong>values</strong>: A 1-D tensor.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:readerReadUpToV2" class="def">readerReadUpToV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a <code>Reader</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>queue_handle</strong>: Handle to a <code>Queue</code>, with string work items.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_records</strong>: number of records to read from <code>Reader</code>.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p>(<strong>keys</strong>, <strong>values</strong>)</p><ul><li><strong>keys</strong>: A 1-D tensor.</li><li><strong>values</strong>: A 1-D tensor.</li></ul></td></tr></table></div><div class="doc"><p>Returns up to <code>num_records</code> (key, value) pairs produced by a Reader.</p><p>Will dequeue from the input queue if necessary (e.g. when the
|
|
Reader needs to start reading from a new file since it has finished
|
|
with the previous file).
|
|
It may return less than <code>num_records</code> even before the last batch.</p></div></div><div class="top"><p class="src"><a name="v:readerReadUpToV2-39-" class="def">readerReadUpToV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a <code>Reader</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>queue_handle</strong>: Handle to a <code>Queue</code>, with string work items.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_records</strong>: number of records to read from <code>Reader</code>.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p>(<strong>keys</strong>, <strong>values</strong>)</p><ul><li><strong>keys</strong>: A 1-D tensor.</li><li><strong>values</strong>: A 1-D tensor.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:readerReadV2" class="def">readerReadV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>queue_handle</strong>: Handle to a Queue, with string work items.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p>(<strong>key</strong>, <strong>value</strong>)</p><ul><li><strong>key</strong>: A scalar.</li><li><strong>value</strong>: A scalar.</li></ul></td></tr></table></div><div class="doc"><p>Returns the next record (key, value pair) produced by a Reader.</p><p>Will dequeue from the input queue if necessary (e.g. when the
|
|
Reader needs to start reading from a new file since it has finished
|
|
with the previous file).</p></div></div><div class="top"><p class="src"><a name="v:readerReadV2-39-" class="def">readerReadV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>queue_handle</strong>: Handle to a Queue, with string work items.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p>(<strong>key</strong>, <strong>value</strong>)</p><ul><li><strong>key</strong>: A scalar.</li><li><strong>value</strong>: A scalar.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:readerReset" class="def">readerReset</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Restore a Reader to its initial clean state.</p></div></div><div class="top"><p class="src"><a name="v:readerReset-39-" class="def">readerReset'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:readerResetV2" class="def">readerResetV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Restore a Reader to its initial clean state.</p></div></div><div class="top"><p class="src"><a name="v:readerResetV2-39-" class="def">readerResetV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:readerRestoreState" class="def">readerRestoreState</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>state</strong>: Result of a ReaderSerializeState of a Reader with type
|
|
matching reader_handle.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Restore a reader to a previously saved state.</p><p>Not all Readers support being restored, so this can produce an
|
|
Unimplemented error.</p></div></div><div class="top"><p class="src"><a name="v:readerRestoreState-39-" class="def">readerRestoreState'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>state</strong>: Result of a ReaderSerializeState of a Reader with type
|
|
matching reader_handle.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:readerRestoreStateV2" class="def">readerRestoreStateV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>state</strong>: Result of a ReaderSerializeState of a Reader with type
|
|
matching reader_handle.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Restore a reader to a previously saved state.</p><p>Not all Readers support being restored, so this can produce an
|
|
Unimplemented error.</p></div></div><div class="top"><p class="src"><a name="v:readerRestoreStateV2-39-" class="def">readerRestoreStateV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>state</strong>: Result of a ReaderSerializeState of a Reader with type
|
|
matching reader_handle.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:readerSerializeState" class="def">readerSerializeState</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>state</strong></p></td></tr></table></div><div class="doc"><p>Produce a string tensor that encodes the state of a Reader.</p><p>Not all Readers support being serialized, so this can produce an
|
|
Unimplemented error.</p></div></div><div class="top"><p class="src"><a name="v:readerSerializeState-39-" class="def">readerSerializeState'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>state</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:readerSerializeStateV2" class="def">readerSerializeStateV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>state</strong></p></td></tr></table></div><div class="doc"><p>Produce a string tensor that encodes the state of a Reader.</p><p>Not all Readers support being serialized, so this can produce an
|
|
Unimplemented error.</p></div></div><div class="top"><p class="src"><a name="v:readerSerializeStateV2-39-" class="def">readerSerializeStateV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: Handle to a Reader.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>state</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:real" class="def">real</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tout)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tout</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Returns the real part of a complex number.</p><p>Given a tensor <code>input</code> of complex numbers, this operation returns a tensor of
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|
type <code>float</code> that is the real part of each element in <code>input</code>. All elements in
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|
<code>input</code> must be complex numbers of the form \(a + bj\), where *a* is the real
|
|
part returned by this operation and *b* is the imaginary part.</p><p>For example:</p><p>```
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|
# tensor <code>input</code> is [-2.25 + 4.75j, 3.25 + 5.75j]
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|
tf.real(input) ==> [-2.25, 3.25]
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|
```</p></div></div><div class="top"><p class="src"><a name="v:real-39-" class="def">real'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tout)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> tout</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:realDiv" class="def">realDiv</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns x / y element-wise for real types.</p><p>If <code>x</code> and <code>y</code> are reals, this will return the floating-point division.</p><ul><li>NOTE*: <code>Div</code> supports broadcasting. More about broadcasting
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|
<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:realDiv-39-" class="def">realDiv'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:reciprocal" class="def">reciprocal</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes the reciprocal of x element-wise.</p><p>I.e., \(y = 1 / x\).</p></div></div><div class="top"><p class="src"><a name="v:reciprocal-39-" class="def">reciprocal'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:reciprocalGrad" class="def">reciprocalGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Computes the gradient for the inverse of <code>x</code> wrt its input.</p><p>Specifically, `grad = -dy * y*y`, where `y = 1/x`, and <code>dy</code>
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is the corresponding input gradient.</p></div></div><div class="top"><p class="src"><a name="v:reciprocalGrad-39-" class="def">reciprocalGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:recordInput" class="def">recordInput</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>records</strong>: A tensor of shape [batch_size].</p></td></tr></table></div><div class="doc"><p>Emits randomized records.</p></div></div><div class="top"><p class="src"><a name="v:recordInput-39-" class="def">recordInput'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>records</strong>: A tensor of shape [batch_size].</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:reduceJoin" class="def">reduceJoin</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>inputs</strong>: The input to be joined. All reduced indices must have non-zero size.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>reduction_indices</strong>: The dimensions to reduce over. Dimensions are reduced in the
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order specified. Omitting <code>reduction_indices</code> is equivalent to passing
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`[n-1, n-2, ..., 0]`. Negative indices from `-n` to `-1` are supported.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>output</strong>: Has shape equal to that of the input with reduced dimensions removed or
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set to `1` depending on <code>keep_dims</code>.</p></td></tr></table></div><div class="doc"><p>Joins a string Tensor across the given dimensions.</p><p>Computes the string join across dimensions in the given string Tensor of shape
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`[d_0, d_1, ..., d_n-1]`. Returns a new Tensor created by joining the input
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|
strings with the given separator (default: empty string). Negative indices are
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|
counted backwards from the end, with `-1` being equivalent to `n - 1`.</p><p>For example:</p><p>```
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# tensor <code>a</code> is [["a", "b"], ["c", "d"]]
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tf.reduce_join(a, 0) ==> ["ac", "bd"]
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tf.reduce_join(a, 1) ==> ["ab", "cd"]
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tf.reduce_join(a, -2) = tf.reduce_join(a, 0) ==> ["ac", "bd"]
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tf.reduce_join(a, -1) = tf.reduce_join(a, 1) ==> ["ab", "cd"]
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tf.reduce_join(a, 0, keep_dims=True) ==> [["ac", "bd"]]
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tf.reduce_join(a, 1, keep_dims=True) ==> [["ab"], ["cd"]]
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tf.reduce_join(a, 0, separator=".") ==> ["a.c", "b.d"]
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tf.reduce_join(a, [0, 1]) ==> ["acbd"]
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tf.reduce_join(a, [1, 0]) ==> ["abcd"]
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tf.reduce_join(a, []) ==> ["abcd"]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:reduceJoin-39-" class="def">reduceJoin'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>inputs</strong>: The input to be joined. All reduced indices must have non-zero size.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>reduction_indices</strong>: The dimensions to reduce over. Dimensions are reduced in the
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|
order specified. Omitting <code>reduction_indices</code> is equivalent to passing
|
|
`[n-1, n-2, ..., 0]`. Negative indices from `-n` to `-1` are supported.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>output</strong>: Has shape equal to that of the input with reduced dimensions removed or
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|
set to `1` depending on <code>keep_dims</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:refEnter" class="def">refEnter</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>data</strong>: The tensor to be made available to the child frame.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output</strong>: The same tensor as `data`.</p></td></tr></table></div><div class="doc"><p>Creates or finds a child frame, and makes `data` available to the child frame.</p><p>The unique <code>frame_name</code> is used by the <code>Executor</code> to identify frames. If
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<code>is_constant</code> is true, <code>output</code> is a constant in the child frame; otherwise
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|
it may be changed in the child frame. At most <code>parallel_iterations</code> iterations
|
|
are run in parallel in the child frame.</p></div></div><div class="top"><p class="src"><a name="v:refEnter-39-" class="def">refEnter'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>data</strong>: The tensor to be made available to the child frame.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output</strong>: The same tensor as `data`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:refExit" class="def">refExit</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>data</strong>: The tensor to be made available to the parent frame.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output</strong>: The same tensor as `data`.</p></td></tr></table></div><div class="doc"><p>Exits the current frame to its parent frame.</p><p>Exit makes its input `data` available to the parent frame.</p></div></div><div class="top"><p class="src"><a name="v:refExit-39-" class="def">refExit'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>data</strong>: The tensor to be made available to the parent frame.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output</strong>: The same tensor as `data`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:refIdentity" class="def">refIdentity</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Return the same ref tensor as the input ref tensor.</p></div></div><div class="top"><p class="src"><a name="v:refIdentity-39-" class="def">refIdentity'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:refMerge" class="def">refMerge</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t]</td><td class="doc"><p><strong>inputs</strong>: The input tensors, exactly one of which will become available.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>value_index</strong>)</p><ul><li><strong>output</strong>: Will be set to the available input tensor.</li><li><strong>value_index</strong>: The index of the chosen input tensor in <code>inputs</code>.</li></ul></td></tr></table></div><div class="doc"><p>Forwards the value of an available tensor from <code>inputs</code> to <code>output</code>.</p><p><code>Merge</code> waits for at least one of the tensors in <code>inputs</code> to become available.
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It is usually combined with <code>Switch</code> to implement branching.</p><p><code>Merge</code> forwards the first tensor for become available to <code>output</code>, and sets
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<code>value_index</code> to its index in <code>inputs</code>.</p></div></div><div class="top"><p class="src"><a name="v:refMerge-39-" class="def">refMerge'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t]</td><td class="doc"><p><strong>inputs</strong>: The input tensors, exactly one of which will become available.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>value_index</strong>)</p><ul><li><strong>output</strong>: Will be set to the available input tensor.</li><li><strong>value_index</strong>: The index of the chosen input tensor in <code>inputs</code>.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:refNextIteration" class="def">refNextIteration</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>data</strong>: The tensor to be made available to the next iteration.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output</strong>: The same tensor as `data`.</p></td></tr></table></div><div class="doc"><p>Makes its input available to the next iteration.</p></div></div><div class="top"><p class="src"><a name="v:refNextIteration-39-" class="def">refNextIteration'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>data</strong>: The tensor to be made available to the next iteration.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output</strong>: The same tensor as `data`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:refSelect" class="def">refSelect</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>index</strong>: A scalar that determines the input that gets selected.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t]</td><td class="doc"><p><strong>inputs</strong>: A list of ref tensors, one of which will be forwarded to <code>output</code>.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output</strong>: The forwarded tensor.</p></td></tr></table></div><div class="doc"><p>Forwards the <code>index</code>th element of <code>inputs</code> to <code>output</code>.</p></div></div><div class="top"><p class="src"><a name="v:refSelect-39-" class="def">refSelect'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>index</strong>: A scalar that determines the input that gets selected.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t]</td><td class="doc"><p><strong>inputs</strong>: A list of ref tensors, one of which will be forwarded to <code>output</code>.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output</strong>: The forwarded tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:refSwitch" class="def">refSwitch</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>data</strong>: The ref tensor to be forwarded to the appropriate output.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>pred</strong>: A scalar that specifies which output port will receive data.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p>(<strong>output_false</strong>, <strong>output_true</strong>)</p><ul><li><strong>output_false</strong>: If <code><a href="../base-4.8.2.0/Prelude.html#v:pred">pred</a></code> is false, data will be forwarded to this output.</li><li><strong>output_true</strong>: If <code><a href="../base-4.8.2.0/Prelude.html#v:pred">pred</a></code> is true, data will be forwarded to this output.</li></ul></td></tr></table></div><div class="doc"><p>Forwards the ref tensor `data` to the output port determined by <code><a href="../base-4.8.2.0/Prelude.html#v:pred">pred</a></code>.</p><p>If <code><a href="../base-4.8.2.0/Prelude.html#v:pred">pred</a></code> is true, the `data` input is forwarded to <code>output_true</code>. Otherwise,
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the data goes to <code>output_false</code>.</p><p>See also <code>Switch</code> and <code>Merge</code>.</p></div></div><div class="top"><p class="src"><a name="v:refSwitch-39-" class="def">refSwitch'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>data</strong>: The ref tensor to be forwarded to the appropriate output.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>pred</strong>: A scalar that specifies which output port will receive data.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p>(<strong>output_false</strong>, <strong>output_true</strong>)</p><ul><li><strong>output_false</strong>: If <code><a href="../base-4.8.2.0/Prelude.html#v:pred">pred</a></code> is false, data will be forwarded to this output.</li><li><strong>output_true</strong>: If <code><a href="../base-4.8.2.0/Prelude.html#v:pred">pred</a></code> is true, data will be forwarded to this output.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:relu" class="def">relu</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>features</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>activations</strong></p></td></tr></table></div><div class="doc"><p>Computes rectified linear: `max(features, 0)`.</p></div></div><div class="top"><p class="src"><a name="v:relu-39-" class="def">relu'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>features</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>activations</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:relu6" class="def">relu6</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>features</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>activations</strong></p></td></tr></table></div><div class="doc"><p>Computes rectified linear 6: `min(max(features, 0), 6)`.</p></div></div><div class="top"><p class="src"><a name="v:relu6-39-" class="def">relu6'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>features</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>activations</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:relu6Grad" class="def">relu6Grad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>gradients</strong>: The backpropagated gradients to the corresponding Relu6 operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>features</strong>: The features passed as input to the corresponding Relu6 operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>backprops</strong>: The gradients:
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`gradients * (features > 0) * (features < 6)`.</p></td></tr></table></div><div class="doc"><p>Computes rectified linear 6 gradients for a Relu6 operation.</p></div></div><div class="top"><p class="src"><a name="v:relu6Grad-39-" class="def">relu6Grad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>gradients</strong>: The backpropagated gradients to the corresponding Relu6 operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>features</strong>: The features passed as input to the corresponding Relu6 operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>backprops</strong>: The gradients:
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`gradients * (features > 0) * (features < 6)`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:reluGrad" class="def">reluGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>gradients</strong>: The backpropagated gradients to the corresponding Relu operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>features</strong>: The features passed as input to the corresponding Relu operation, OR
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|
the outputs of that operation (both work equivalently).</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>backprops</strong>: `gradients * (features > 0)`.</p></td></tr></table></div><div class="doc"><p>Computes rectified linear gradients for a Relu operation.</p></div></div><div class="top"><p class="src"><a name="v:reluGrad-39-" class="def">reluGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>gradients</strong>: The backpropagated gradients to the corresponding Relu operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>features</strong>: The features passed as input to the corresponding Relu operation, OR
|
|
the outputs of that operation (both work equivalently).</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>backprops</strong>: `gradients * (features > 0)`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:requantizationRange" class="def">requantizationRange</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input_min</strong>: The float value that the minimum quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input_max</strong>: The float value that the maximum quantized input value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output_min</strong>, <strong>output_max</strong>)</p><ul><li><strong>output_min</strong>: The computed min output.</li><li><strong>output_max</strong>: the computed max output.</li></ul></td></tr></table></div><div class="doc"><p>Given a quantized tensor described by (input, input_min, input_max), outputs a</p><p>range that covers the actual values present in that tensor. This op is
|
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typically used to produce the requested_output_min and requested_output_max for
|
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Requantize.</p></div></div><div class="top"><p class="src"><a name="v:requantizationRange-39-" class="def">requantizationRange'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input_min</strong>: The float value that the minimum quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input_max</strong>: The float value that the maximum quantized input value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output_min</strong>, <strong>output_max</strong>)</p><ul><li><strong>output_min</strong>: The computed min output.</li><li><strong>output_max</strong>: the computed max output.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:requantize" class="def">requantize</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input_min</strong>: The float value that the minimum quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input_max</strong>: The float value that the maximum quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>requested_output_min</strong>: The float value that the minimum quantized output value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>requested_output_max</strong>: The float value that the maximum quantized output value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>output_min</strong>, <strong>output_max</strong>)</p><ul><li><strong>output</strong></li><li><strong>output_min</strong>: The requested_output_min value is copied into this output.</li><li><strong>output_max</strong>: The requested_output_max value is copied into this output.</li></ul></td></tr></table></div><div class="doc"><p>Convert the quantized <code>input</code> tensor into a lower-precision <code>output</code>, using the</p><p>output range specified with <code>requested_output_min</code> and <code>requested_output_max</code>.</p><dl><dt>input_min, input_max</dt><dd>are scalar floats that specify the range for the float
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interpretation of the <code>input</code> data. For example, if input_min is -1.0f and
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input_max is 1.0f, and we are dealing with quint16 quantized data, then a 0
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value in the 16-bit data should be interpreted as -1.0f, and a 65535 means 1.0f.</dd></dl></div></div><div class="top"><p class="src"><a name="v:requantize-39-" class="def">requantize'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` tinput, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tinput</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input_min</strong>: The float value that the minimum quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>input_max</strong>: The float value that the maximum quantized input value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>requested_output_min</strong>: The float value that the minimum quantized output value represents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>requested_output_max</strong>: The float value that the maximum quantized output value represents.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>output</strong>, <strong>output_min</strong>, <strong>output_max</strong>)</p><ul><li><strong>output</strong></li><li><strong>output_min</strong>: The requested_output_min value is copied into this output.</li><li><strong>output_max</strong>: The requested_output_max value is copied into this output.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:reshape" class="def">reshape</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tshape)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>tensor</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tshape</td><td class="doc"><p><strong>shape</strong>: Defines the shape of the output tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Reshapes a tensor.</p><p>Given <code>tensor</code>, this operation returns a tensor that has the same values
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as <code>tensor</code> with shape <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code>.</p><p>If one component of <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> is the special value -1, the size of that dimension
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is computed so that the total size remains constant. In particular, a <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code>
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of `[-1]` flattens into 1-D. At most one component of <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> can be -1.</p><p>If <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> is 1-D or higher, then the operation returns a tensor with shape
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<code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> filled with the values of <code>tensor</code>. In this case, the number of elements
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implied by <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> must be the same as the number of elements in <code>tensor</code>.</p><p>For example:</p><p>```prettyprint
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# tensor <code>t</code> is [1, 2, 3, 4, 5, 6, 7, 8, 9]
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# tensor <code>t</code> has shape [9]
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reshape(t, [3, 3]) ==> [[1, 2, 3],
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[4, 5, 6],
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[7, 8, 9]]</p><p># tensor <code>t</code> is [[[1, 1], [2, 2]],
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# [[3, 3], [4, 4]]]
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# tensor <code>t</code> has shape [2, 2, 2]
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reshape(t, [2, 4]) ==> [[1, 1, 2, 2],
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[3, 3, 4, 4]]</p><p># tensor <code>t</code> is [[[1, 1, 1],
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# [2, 2, 2]],
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# [[3, 3, 3],
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# [4, 4, 4]],
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# [[5, 5, 5],
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# [6, 6, 6]]]
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# tensor <code>t</code> has shape [3, 2, 3]
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# pass '[-1]' to flatten <code>t</code>
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reshape(t, [-1]) ==> [1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6]</p><p># -1 can also be used to infer the shape</p><p># -1 is inferred to be 9:
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reshape(t, [2, -1]) ==> [[1, 1, 1, 2, 2, 2, 3, 3, 3],
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[4, 4, 4, 5, 5, 5, 6, 6, 6]]
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# -1 is inferred to be 2:
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reshape(t, [-1, 9]) ==> [[1, 1, 1, 2, 2, 2, 3, 3, 3],
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[4, 4, 4, 5, 5, 5, 6, 6, 6]]
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# -1 is inferred to be 3:
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reshape(t, [ 2, -1, 3]) ==> [[[1, 1, 1],
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[2, 2, 2],
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[3, 3, 3]],
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[[4, 4, 4],
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[5, 5, 5],
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[6, 6, 6]]]</p><p># tensor <code>t</code> is [7]
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# shape `[]` reshapes to a scalar
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reshape(t, []) ==> 7
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```</p></div></div><div class="top"><p class="src"><a name="v:reshape-39-" class="def">reshape'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tshape)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>tensor</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tshape</td><td class="doc"><p><strong>shape</strong>: Defines the shape of the output tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:resizeArea" class="def">resizeArea</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>images</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong>: = A 1-D int32 Tensor of 2 elements: `new_height, new_width`. The
|
|
new size for the images.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>resized_images</strong>: 4-D with shape
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`[batch, new_height, new_width, channels]`.</p></td></tr></table></div><div class="doc"><p>Resize <code>images</code> to <code><a href="TensorFlow-GenOps-Core.html#v:size">size</a></code> using area interpolation.</p><p>Input images can be of different types but output images are always float.</p></div></div><div class="top"><p class="src"><a name="v:resizeArea-39-" class="def">resizeArea'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>images</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong>: = A 1-D int32 Tensor of 2 elements: `new_height, new_width`. The
|
|
new size for the images.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>resized_images</strong>: 4-D with shape
|
|
`[batch, new_height, new_width, channels]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:resizeBicubic" class="def">resizeBicubic</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>images</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong>: = A 1-D int32 Tensor of 2 elements: `new_height, new_width`. The
|
|
new size for the images.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>resized_images</strong>: 4-D with shape
|
|
`[batch, new_height, new_width, channels]`.</p></td></tr></table></div><div class="doc"><p>Resize <code>images</code> to <code><a href="TensorFlow-GenOps-Core.html#v:size">size</a></code> using bicubic interpolation.</p><p>Input images can be of different types but output images are always float.</p></div></div><div class="top"><p class="src"><a name="v:resizeBicubic-39-" class="def">resizeBicubic'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>images</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong>: = A 1-D int32 Tensor of 2 elements: `new_height, new_width`. The
|
|
new size for the images.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>resized_images</strong>: 4-D with shape
|
|
`[batch, new_height, new_width, channels]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:resizeBilinear" class="def">resizeBilinear</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>images</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong>: = A 1-D int32 Tensor of 2 elements: `new_height, new_width`. The
|
|
new size for the images.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>resized_images</strong>: 4-D with shape
|
|
`[batch, new_height, new_width, channels]`.</p></td></tr></table></div><div class="doc"><p>Resize <code>images</code> to <code><a href="TensorFlow-GenOps-Core.html#v:size">size</a></code> using bilinear interpolation.</p><p>Input images can be of different types but output images are always float.</p></div></div><div class="top"><p class="src"><a name="v:resizeBilinear-39-" class="def">resizeBilinear'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>images</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong>: = A 1-D int32 Tensor of 2 elements: `new_height, new_width`. The
|
|
new size for the images.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>resized_images</strong>: 4-D with shape
|
|
`[batch, new_height, new_width, channels]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:resizeBilinearGrad" class="def">resizeBilinearGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>grads</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>original_image</strong>: 4-D with shape `[batch, orig_height, orig_width, channels]`,
|
|
The image tensor that was resized.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D with shape `[batch, orig_height, orig_width, channels]`.
|
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Gradients with respect to the input image. Input image must have been
|
|
float or double.</p></td></tr></table></div><div class="doc"><p>Computes the gradient of bilinear interpolation.</p></div></div><div class="top"><p class="src"><a name="v:resizeBilinearGrad-39-" class="def">resizeBilinearGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>grads</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>original_image</strong>: 4-D with shape `[batch, orig_height, orig_width, channels]`,
|
|
The image tensor that was resized.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D with shape `[batch, orig_height, orig_width, channels]`.
|
|
Gradients with respect to the input image. Input image must have been
|
|
float or double.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:resizeNearestNeighbor" class="def">resizeNearestNeighbor</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>images</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong>: = A 1-D int32 Tensor of 2 elements: `new_height, new_width`. The
|
|
new size for the images.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>resized_images</strong>: 4-D with shape
|
|
`[batch, new_height, new_width, channels]`.</p></td></tr></table></div><div class="doc"><p>Resize <code>images</code> to <code><a href="TensorFlow-GenOps-Core.html#v:size">size</a></code> using nearest neighbor interpolation.</p></div></div><div class="top"><p class="src"><a name="v:resizeNearestNeighbor-39-" class="def">resizeNearestNeighbor'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>images</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong>: = A 1-D int32 Tensor of 2 elements: `new_height, new_width`. The
|
|
new size for the images.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>resized_images</strong>: 4-D with shape
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`[batch, new_height, new_width, channels]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:resizeNearestNeighborGrad" class="def">resizeNearestNeighborGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>grads</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong>: = A 1-D int32 Tensor of 2 elements: `orig_height, orig_width`. The
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original input size.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D with shape `[batch, orig_height, orig_width, channels]`. Gradients
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with respect to the input image.</p></td></tr></table></div><div class="doc"><p>Computes the gradient of nearest neighbor interpolation.</p></div></div><div class="top"><p class="src"><a name="v:resizeNearestNeighborGrad-39-" class="def">resizeNearestNeighborGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>grads</strong>: 4-D with shape `[batch, height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong>: = A 1-D int32 Tensor of 2 elements: `orig_height, orig_width`. The
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original input size.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 4-D with shape `[batch, orig_height, orig_width, channels]`. Gradients
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with respect to the input image.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceApplyAdadelta" class="def">resourceApplyAdadelta</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum_update</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>rho</strong>: Decay factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>epsilon</strong>: Constant factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Update '*var' according to the adadelta scheme.</p><p>accum = rho() * accum + (1 - rho()) * grad.square();
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update = (update_accum + epsilon).sqrt() * (accum + epsilon()).rsqrt() * grad;
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update_accum = rho() * update_accum + (1 - rho()) * update.square();
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var -= update;</p></div></div><div class="top"><p class="src"><a name="v:resourceApplyAdadelta-39-" class="def">resourceApplyAdadelta'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum_update</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>rho</strong>: Decay factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>epsilon</strong>: Constant factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceApplyAdagrad" class="def">resourceApplyAdagrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Update '*var' according to the adagrad scheme.</p><p>accum += grad * grad
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var -= lr * grad * (1 / sqrt(accum))</p></div></div><div class="top"><p class="src"><a name="v:resourceApplyAdagrad-39-" class="def">resourceApplyAdagrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceApplyAdagradDA" class="def">resourceApplyAdagradDA</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>gradient_accumulator</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>gradient_squared_accumulator</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>global_step</strong>: Training step number. Must be a scalar.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Update '*var' according to the proximal adagrad scheme.</p></div></div><div class="top"><p class="src"><a name="v:resourceApplyAdagradDA-39-" class="def">resourceApplyAdagradDA'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>gradient_accumulator</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>gradient_squared_accumulator</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>global_step</strong>: Training step number. Must be a scalar.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceApplyAdam" class="def">resourceApplyAdam</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>m</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>v</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>beta1_power</strong>: Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>beta2_power</strong>: Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>beta1</strong>: Momentum factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>beta2</strong>: Momentum factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Update '*var' according to the Adam algorithm.</p><p>lr_t <- learning_rate * sqrt(1 - beta2^t) / (1 - beta1^t)
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m_t <- beta1 * m_{t-1} + (1 - beta1) * g_t
|
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v_t <- beta2 * v_{t-1} + (1 - beta2) * g_t * g_t
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variable <- variable - lr_t * m_t / (sqrt(v_t) + epsilon)</p></div></div><div class="top"><p class="src"><a name="v:resourceApplyAdam-39-" class="def">resourceApplyAdam'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>m</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>v</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>beta1_power</strong>: Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>beta2_power</strong>: Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>beta1</strong>: Momentum factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>beta2</strong>: Momentum factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceApplyCenteredRMSProp" class="def">resourceApplyCenteredRMSProp</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>mg</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>ms</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>mom</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>rho</strong>: Decay rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>momentum</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Update '*var' according to the centered RMSProp algorithm.</p><p>The centered RMSProp algorithm uses an estimate of the centered second moment
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(i.e., the variance) for normalization, as opposed to regular RMSProp, which
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|
uses the (uncentered) second moment. This often helps with training, but is
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slightly more expensive in terms of computation and memory.</p><p>Note that in dense implementation of this algorithm, mg, ms, and mom will
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update even if the grad is zero, but in this sparse implementation, mg, ms,
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and mom will not update in iterations during which the grad is zero.</p><p>mean_square = decay * mean_square + (1-decay) * gradient ** 2
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mean_grad = decay * mean_grad + (1-decay) * gradient</p><p>Delta = learning_rate * gradient / sqrt(mean_square + epsilon - mean_grad ** 2)</p><p>mg <- rho * mg_{t-1} + (1-rho) * grad
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ms <- rho * ms_{t-1} + (1-rho) * grad * grad
|
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mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms - mg * mg + epsilon)
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var <- var - mom</p></div></div><div class="top"><p class="src"><a name="v:resourceApplyCenteredRMSProp-39-" class="def">resourceApplyCenteredRMSProp'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>mg</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>ms</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>mom</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>rho</strong>: Decay rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>momentum</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceApplyFtrl" class="def">resourceApplyFtrl</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>linear</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>l1</strong>: L1 regulariation. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>l2</strong>: L2 regulariation. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>lr_power</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Update '*var' according to the Ftrl-proximal scheme.</p><p>accum_new = accum + grad * grad
|
|
linear += grad + (accum_new^(-lr_power) - accum^(-lr_power)) / lr * var
|
|
quadratic = 1.0 / (accum_new^(lr_power) * lr) + 2 * l2
|
|
var = (sign(linear) * l1 - linear) / quadratic if |linear| > l1 else 0.0
|
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accum = accum_new</p></div></div><div class="top"><p class="src"><a name="v:resourceApplyFtrl-39-" class="def">resourceApplyFtrl'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>linear</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>l1</strong>: L1 regulariation. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>l2</strong>: L2 regulariation. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>lr_power</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceApplyGradientDescent" class="def">resourceApplyGradientDescent</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>alpha</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>delta</strong>: The change.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Update '*var' by subtracting <code>alpha</code> * <code>delta</code> from it.</p></div></div><div class="top"><p class="src"><a name="v:resourceApplyGradientDescent-39-" class="def">resourceApplyGradientDescent'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>alpha</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>delta</strong>: The change.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceApplyMomentum" class="def">resourceApplyMomentum</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>momentum</strong>: Momentum. Must be a scalar.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Update '*var' according to the momentum scheme. Set use_nesterov = True if you</p><p>want to use Nesterov momentum.</p><p>accum = accum * momentum + grad
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var -= lr * accum</p></div></div><div class="top"><p class="src"><a name="v:resourceApplyMomentum-39-" class="def">resourceApplyMomentum'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>momentum</strong>: Momentum. Must be a scalar.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceApplyProximalAdagrad" class="def">resourceApplyProximalAdagrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Update '*var' and '*accum' according to FOBOS with Adagrad learning rate.</p><p>accum += grad * grad
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prox_v = var - lr * grad * (1 / sqrt(accum))
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var = sign(prox_v)/(1+lr*l2) * max{|prox_v|-lr*l1,0}</p></div></div><div class="top"><p class="src"><a name="v:resourceApplyProximalAdagrad-39-" class="def">resourceApplyProximalAdagrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceApplyProximalGradientDescent" class="def">resourceApplyProximalGradientDescent</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>alpha</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>delta</strong>: The change.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Update '*var' as FOBOS algorithm with fixed learning rate.</p><p>prox_v = var - alpha * delta
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var = sign(prox_v)/(1+alpha*l2) * max{|prox_v|-alpha*l1,0}</p></div></div><div class="top"><p class="src"><a name="v:resourceApplyProximalGradientDescent-39-" class="def">resourceApplyProximalGradientDescent'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>alpha</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>delta</strong>: The change.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceApplyRMSProp" class="def">resourceApplyRMSProp</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>ms</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>mom</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>rho</strong>: Decay rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>momentum</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Update '*var' according to the RMSProp algorithm.</p><p>Note that in dense implementation of this algorithm, ms and mom will
|
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update even if the grad is zero, but in this sparse implementation, ms
|
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and mom will not update in iterations during which the grad is zero.</p><p>mean_square = decay * mean_square + (1-decay) * gradient ** 2
|
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Delta = learning_rate * gradient / sqrt(mean_square + epsilon)</p><p>ms <- rho * ms_{t-1} + (1-rho) * grad * grad
|
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mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon)
|
|
var <- var - mom</p></div></div><div class="top"><p class="src"><a name="v:resourceApplyRMSProp-39-" class="def">resourceApplyRMSProp'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>ms</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>mom</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>rho</strong>: Decay rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>momentum</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceGather" class="def">resourceGather</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>resource</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Gather slices from the variable pointed to by <code>resource</code> according to <code>indices</code>.</p><p><code>indices</code> must be an integer tensor of any dimension (usually 0-D or 1-D).
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Produces an output tensor with shape `indices.shape + params.shape[1:]` where:</p><p>```python
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|
# Scalar indices
|
|
output[:, ..., :] = params[indices, :, ... :]</p><p># Vector indices
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|
output[i, :, ..., :] = params[indices[i], :, ... :]</p><p># Higher rank indices
|
|
output[i, ..., j, :, ... :] = params[indices[i, ..., j], :, ..., :]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:resourceGather-39-" class="def">resourceGather'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>resource</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceScatterAdd" class="def">resourceScatterAdd</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>resource</strong>: Should be from a <code>Variable</code> node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: A tensor of indices into the first dimension of <code>ref</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 dtype</td><td class="doc"><p><strong>updates</strong>: A tensor of updated values to add to <code>ref</code>.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Adds sparse updates to the variable referenced by <code>resource</code>.</p><p>This operation computes</p><p># Scalar indices
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ref[indices, ...] += updates[...]</p><p># Vector indices (for each i)
|
|
ref[indices[i], ...] += updates[i, ...]</p><p># High rank indices (for each i, ..., j)
|
|
ref[indices[i, ..., j], ...] += updates[i, ..., j, ...]</p><p>Duplicate entries are handled correctly: if multiple <code>indices</code> reference
|
|
the same location, their contributions add.</p><p>Requires `updates.shape = indices.shape + ref.shape[1:]`.</p><p><a href="div">style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;"</a>
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<a href="img">style="width:100%" src="../../images/ScatterAdd.png" alt</a>
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<a href="/div">/div</a></p></div></div><div class="top"><p class="src"><a name="v:resourceScatterAdd-39-" class="def">resourceScatterAdd'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>resource</strong>: Should be from a <code>Variable</code> node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: A tensor of indices into the first dimension of <code>ref</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 dtype</td><td class="doc"><p><strong>updates</strong>: A tensor of updated values to add to <code>ref</code>.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceSparseApplyAdadelta" class="def">resourceSparseApplyAdadelta</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum_update</strong>: : Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>rho</strong>: Decay factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>epsilon</strong>: Constant factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>var: Should be from a Variable().</p></div></div><div class="top"><p class="src"><a name="v:resourceSparseApplyAdadelta-39-" class="def">resourceSparseApplyAdadelta'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum_update</strong>: : Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>rho</strong>: Decay factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>epsilon</strong>: Constant factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceSparseApplyAdagrad" class="def">resourceSparseApplyAdagrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Update relevant entries in '*var' and '*accum' according to the adagrad scheme.</p><p>That is for rows we have grad for, we update var and accum as follows:
|
|
accum += grad * grad
|
|
var -= lr * grad * (1 / sqrt(accum))</p></div></div><div class="top"><p class="src"><a name="v:resourceSparseApplyAdagrad-39-" class="def">resourceSparseApplyAdagrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceSparseApplyAdagradDA" class="def">resourceSparseApplyAdagradDA</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>gradient_accumulator</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>gradient_squared_accumulator</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>global_step</strong>: Training step number. Must be a scalar.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Update entries in '*var' and '*accum' according to the proximal adagrad scheme.</p></div></div><div class="top"><p class="src"><a name="v:resourceSparseApplyAdagradDA-39-" class="def">resourceSparseApplyAdagradDA'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>gradient_accumulator</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>gradient_squared_accumulator</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>global_step</strong>: Training step number. Must be a scalar.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceSparseApplyCenteredRMSProp" class="def">resourceSparseApplyCenteredRMSProp</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>mg</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>ms</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>mom</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>rho</strong>: Decay rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>momentum</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var, ms and mom.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Update '*var' according to the centered RMSProp algorithm.</p><p>The centered RMSProp algorithm uses an estimate of the centered second moment
|
|
(i.e., the variance) for normalization, as opposed to regular RMSProp, which
|
|
uses the (uncentered) second moment. This often helps with training, but is
|
|
slightly more expensive in terms of computation and memory.</p><p>Note that in dense implementation of this algorithm, mg, ms, and mom will
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|
update even if the grad is zero, but in this sparse implementation, mg, ms,
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|
and mom will not update in iterations during which the grad is zero.</p><p>mean_square = decay * mean_square + (1-decay) * gradient ** 2
|
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mean_grad = decay * mean_grad + (1-decay) * gradient
|
|
Delta = learning_rate * gradient / sqrt(mean_square + epsilon - mean_grad ** 2)</p><p>ms <- rho * ms_{t-1} + (1-rho) * grad * grad
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|
mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon)
|
|
var <- var - mom</p></div></div><div class="top"><p class="src"><a name="v:resourceSparseApplyCenteredRMSProp-39-" class="def">resourceSparseApplyCenteredRMSProp'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>mg</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>ms</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>mom</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>rho</strong>: Decay rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>momentum</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var, ms and mom.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceSparseApplyFtrl" class="def">resourceSparseApplyFtrl</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>linear</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t</td><td class="doc"><p><strong>lr_power</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Update relevant entries in '*var' according to the Ftrl-proximal scheme.</p><p>That is for rows we have grad for, we update var, accum and linear as follows:
|
|
accum_new = accum + grad * grad
|
|
linear += grad + (accum_new^(-lr_power) - accum^(-lr_power)) / lr * var
|
|
quadratic = 1.0 / (accum_new^(lr_power) * lr) + 2 * l2
|
|
var = (sign(linear) * l1 - linear) / quadratic if |linear| > l1 else 0.0
|
|
accum = accum_new</p></div></div><div class="top"><p class="src"><a name="v:resourceSparseApplyFtrl-39-" class="def">resourceSparseApplyFtrl'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>linear</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t</td><td class="doc"><p><strong>lr_power</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceSparseApplyMomentum" class="def">resourceSparseApplyMomentum</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>momentum</strong>: Momentum. Must be a scalar.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Update relevant entries in '*var' and '*accum' according to the momentum scheme.</p><p>Set use_nesterov = True if you want to use Nesterov momentum.</p><p>That is for rows we have grad for, we update var and accum as follows:</p><p>accum = accum * momentum + grad
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var -= lr * accum</p></div></div><div class="top"><p class="src"><a name="v:resourceSparseApplyMomentum-39-" class="def">resourceSparseApplyMomentum'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>momentum</strong>: Momentum. Must be a scalar.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceSparseApplyProximalAdagrad" class="def">resourceSparseApplyProximalAdagrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Sparse update entries in '*var' and '*accum' according to FOBOS algorithm.</p><p>That is for rows we have grad for, we update var and accum as follows:
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accum += grad * grad
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prox_v = var
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prox_v -= lr * grad * (1 / sqrt(accum))
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var = sign(prox_v)/(1+lr*l2) * max{|prox_v|-lr*l1,0}</p></div></div><div class="top"><p class="src"><a name="v:resourceSparseApplyProximalAdagrad-39-" class="def">resourceSparseApplyProximalAdagrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceSparseApplyProximalGradientDescent" class="def">resourceSparseApplyProximalGradientDescent</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>alpha</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Sparse update '*var' as FOBOS algorithm with fixed learning rate.</p><p>That is for rows we have grad for, we update var as follows:
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prox_v = var - alpha * grad
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var = sign(prox_v)/(1+alpha*l2) * max{|prox_v|-alpha*l1,0}</p></div></div><div class="top"><p class="src"><a name="v:resourceSparseApplyProximalGradientDescent-39-" class="def">resourceSparseApplyProximalGradientDescent'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>alpha</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:resourceSparseApplyRMSProp" class="def">resourceSparseApplyRMSProp</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>ms</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>mom</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>rho</strong>: Decay rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>momentum</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var, ms and mom.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Update '*var' according to the RMSProp algorithm.</p><p>Note that in dense implementation of this algorithm, ms and mom will
|
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update even if the grad is zero, but in this sparse implementation, ms
|
|
and mom will not update in iterations during which the grad is zero.</p><p>mean_square = decay * mean_square + (1-decay) * gradient ** 2
|
|
Delta = learning_rate * gradient / sqrt(mean_square + epsilon)</p><p>ms <- rho * ms_{t-1} + (1-rho) * grad * grad
|
|
mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon)
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var <- var - mom</p></div></div><div class="top"><p class="src"><a name="v:resourceSparseApplyRMSProp-39-" class="def">resourceSparseApplyRMSProp'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>ms</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>mom</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>rho</strong>: Decay rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>momentum</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var, ms and mom.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:restore" class="def">restore</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dt</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>file_pattern</strong>: Must have a single element. The pattern of the files from
|
|
which we read the tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tensor_name</strong>: Must have a single element. The name of the tensor to be
|
|
restored.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dt</td><td class="doc"><p><strong>tensor</strong>: The restored tensor.</p></td></tr></table></div><div class="doc"><p>Restores a tensor from checkpoint files.</p><p>Reads a tensor stored in one or several files. If there are several files (for
|
|
instance because a tensor was saved as slices), <code>file_pattern</code> may contain
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|
wildcard symbols (<code><a href="../base-4.8.2.0/Prelude.html#v:-42-">*</a></code> and <code>?</code>) in the filename portion only, not in the
|
|
directory portion.</p><p>If a <code>file_pattern</code> matches several files, <code>preferred_shard</code> can be used to hint
|
|
in which file the requested tensor is likely to be found. This op will first
|
|
open the file at index <code>preferred_shard</code> in the list of matching files and try
|
|
to restore tensors from that file. Only if some tensors or tensor slices are
|
|
not found in that first file, then the Op opens all the files. Setting
|
|
<code>preferred_shard</code> to match the value passed as the <code>shard</code> input
|
|
of a matching <code>Save</code> Op may speed up Restore. This attribute only affects
|
|
performance, not correctness. The default value -1 means files are processed in
|
|
order.</p><p>See also <code>RestoreSlice</code>.</p></div></div><div class="top"><p class="src"><a name="v:restore-39-" class="def">restore'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dt</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>file_pattern</strong>: Must have a single element. The pattern of the files from
|
|
which we read the tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tensor_name</strong>: Must have a single element. The name of the tensor to be
|
|
restored.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dt</td><td class="doc"><p><strong>tensor</strong>: The restored tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:restoreSlice" class="def">restoreSlice</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dt</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>file_pattern</strong>: Must have a single element. The pattern of the files from
|
|
which we read the tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tensor_name</strong>: Must have a single element. The name of the tensor to be
|
|
restored.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>shape_and_slice</strong>: Scalar. The shapes and slice specifications to use when
|
|
restoring a tensors.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dt</td><td class="doc"><p><strong>tensor</strong>: The restored tensor.</p></td></tr></table></div><div class="doc"><p>Restores a tensor from checkpoint files.</p><p>This is like <code>Restore</code> except that restored tensor can be listed as filling
|
|
only a slice of a larger tensor. <code>shape_and_slice</code> specifies the shape of the
|
|
larger tensor and the slice that the restored tensor covers.</p><p>The <code>shape_and_slice</code> input has the same format as the
|
|
elements of the <code>shapes_and_slices</code> input of the <code>SaveSlices</code> op.</p></div></div><div class="top"><p class="src"><a name="v:restoreSlice-39-" class="def">restoreSlice'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dt</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>file_pattern</strong>: Must have a single element. The pattern of the files from
|
|
which we read the tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tensor_name</strong>: Must have a single element. The name of the tensor to be
|
|
restored.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>shape_and_slice</strong>: Scalar. The shapes and slice specifications to use when
|
|
restoring a tensors.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dt</td><td class="doc"><p><strong>tensor</strong>: The restored tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:restoreV2" class="def">restoreV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> dtypes</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>prefix</strong>: Must have a single element. The prefix of a V2 checkpoint.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tensor_names</strong>: shape {N}. The names of the tensors to be restored.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>shape_and_slices</strong>: shape {N}. The slice specs of the tensors to be restored.
|
|
Empty strings indicate that they are non-partitioned tensors.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtypes</td><td class="doc"><p><strong>tensors</strong>: shape {N}. The restored tensors, whose shapes are read from the
|
|
checkpoint directly.</p></td></tr></table></div><div class="doc"><p>Restores tensors from a V2 checkpoint.</p><p>For backward compatibility with the V1 format, this Op currently allows
|
|
restoring from a V1 checkpoint as well:
|
|
- This Op first attempts to find the V2 index file pointed to by "prefix", and
|
|
if found proceed to read it as a V2 checkpoint;
|
|
- Otherwise the V1 read path is invoked.
|
|
Relying on this behavior is not recommended, as the ability to fall back to read
|
|
V1 might be deprecated and eventually removed.</p><p>By default, restores the named tensors in full. If the caller wishes to restore
|
|
specific slices of stored tensors, "shape_and_slices" should be non-empty
|
|
strings and correspondingly well-formed.</p><p>Callers must ensure all the named tensors are indeed stored in the checkpoint.</p></div></div><div class="top"><p class="src"><a name="v:restoreV2-39-" class="def">restoreV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> dtypes</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>prefix</strong>: Must have a single element. The prefix of a V2 checkpoint.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tensor_names</strong>: shape {N}. The names of the tensors to be restored.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>shape_and_slices</strong>: shape {N}. The slice specs of the tensors to be restored.
|
|
Empty strings indicate that they are non-partitioned tensors.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtypes</td><td class="doc"><p><strong>tensors</strong>: shape {N}. The restored tensors, whose shapes are read from the
|
|
checkpoint directly.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:reverse" class="def">reverse</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>tensor</strong>: Up to 8-D.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>dims</strong>: 1-D. The dimensions to reverse.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The same shape as <code>tensor</code>.</p></td></tr></table></div><div class="doc"><p>Reverses specific dimensions of a tensor.</p><p>Given a <code>tensor</code>, and a <code>bool</code> tensor <code>dims</code> representing the dimensions
|
|
of <code>tensor</code>, this operation reverses each dimension i of <code>tensor</code> where
|
|
`dims[i]` is <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code>.</p><p><code>tensor</code> can have up to 8 dimensions. The number of dimensions
|
|
of <code>tensor</code> must equal the number of elements in <code>dims</code>. In other words:</p><p>`rank(tensor) = size(dims)`</p><p>For example:</p><p>```prettyprint
|
|
# tensor <code>t</code> is [[[[ 0, 1, 2, 3],
|
|
# [ 4, 5, 6, 7],
|
|
# [ 8, 9, 10, 11]],
|
|
# [[12, 13, 14, 15],
|
|
# [16, 17, 18, 19],
|
|
# [20, 21, 22, 23]]]]
|
|
# tensor <code>t</code> shape is [1, 2, 3, 4]</p><p># <code>dims</code> is [False, False, False, True]
|
|
reverse(t, dims) ==> [[[[ 3, 2, 1, 0],
|
|
[ 7, 6, 5, 4],
|
|
[ 11, 10, 9, 8]],
|
|
[[15, 14, 13, 12],
|
|
[19, 18, 17, 16],
|
|
[23, 22, 21, 20]]]]</p><p># <code>dims</code> is [False, True, False, False]
|
|
reverse(t, dims) ==> [[[[12, 13, 14, 15],
|
|
[16, 17, 18, 19],
|
|
[20, 21, 22, 23]
|
|
[[ 0, 1, 2, 3],
|
|
[ 4, 5, 6, 7],
|
|
[ 8, 9, 10, 11]]]]</p><p># <code>dims</code> is [False, False, True, False]
|
|
reverse(t, dims) ==> [[[[8, 9, 10, 11],
|
|
[4, 5, 6, 7],
|
|
[0, 1, 2, 3]]
|
|
[[20, 21, 22, 23],
|
|
[16, 17, 18, 19],
|
|
[12, 13, 14, 15]]]]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:reverse-39-" class="def">reverse'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>tensor</strong>: Up to 8-D.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>dims</strong>: 1-D. The dimensions to reverse.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The same shape as <code>tensor</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:reverseSequence" class="def">reverseSequence</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tlen)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>seq_dim</strong>: The dimension which is partially reversed.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The input to reverse.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tlen</td><td class="doc"><p><strong>seq_lengths</strong>: 1-D with length `input.dims(batch_dim)` and
|
|
`max(seq_lengths) < input.dims(seq_dim)`</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The partially reversed input. It has the same shape as <code>input</code>.</p></td></tr></table></div><div class="doc"><p>Reverses variable length slices.</p><p>This op first slices <code>input</code> along the dimension <code>batch_dim</code>, and for each
|
|
slice <code>i</code>, reverses the first `seq_lengths[i]` elements along
|
|
the dimension <code>seq_dim</code>.</p><p>The elements of <code>seq_lengths</code> must obey `seq_lengths[i] < input.dims[seq_dim]`,
|
|
and <code>seq_lengths</code> must be a vector of length `input.dims[batch_dim]`.</p><p>The output slice <code>i</code> along dimension <code>batch_dim</code> is then given by input
|
|
slice <code>i</code>, with the first `seq_lengths[i]` slices along dimension
|
|
<code>seq_dim</code> reversed.</p><p>For example:</p><p>```prettyprint
|
|
# Given this:
|
|
batch_dim = 0
|
|
seq_dim = 1
|
|
input.dims = (4, 8, ...)
|
|
seq_lengths = [7, 2, 3, 5]</p><p># then slices of input are reversed on seq_dim, but only up to seq_lengths:
|
|
output[0, 0:7, :, ...] = input[0, 7:0:-1, :, ...]
|
|
output[1, 0:2, :, ...] = input[1, 2:0:-1, :, ...]
|
|
output[2, 0:3, :, ...] = input[2, 3:0:-1, :, ...]
|
|
output[3, 0:5, :, ...] = input[3, 5:0:-1, :, ...]</p><p># while entries past seq_lens are copied through:
|
|
output[0, 7:, :, ...] = input[0, 7:, :, ...]
|
|
output[1, 2:, :, ...] = input[1, 2:, :, ...]
|
|
output[2, 3:, :, ...] = input[2, 3:, :, ...]
|
|
output[3, 2:, :, ...] = input[3, 2:, :, ...]
|
|
```</p><p>In contrast, if:</p><p>```prettyprint
|
|
# Given this:
|
|
batch_dim = 2
|
|
seq_dim = 0
|
|
input.dims = (8, ?, 4, ...)
|
|
seq_lengths = [7, 2, 3, 5]</p><p># then slices of input are reversed on seq_dim, but only up to seq_lengths:
|
|
output[0:7, :, 0, :, ...] = input[7:0:-1, :, 0, :, ...]
|
|
output[0:2, :, 1, :, ...] = input[2:0:-1, :, 1, :, ...]
|
|
output[0:3, :, 2, :, ...] = input[3:0:-1, :, 2, :, ...]
|
|
output[0:5, :, 3, :, ...] = input[5:0:-1, :, 3, :, ...]</p><p># while entries past seq_lens are copied through:
|
|
output[7:, :, 0, :, ...] = input[7:, :, 0, :, ...]
|
|
output[2:, :, 1, :, ...] = input[2:, :, 1, :, ...]
|
|
output[3:, :, 2, :, ...] = input[3:, :, 2, :, ...]
|
|
output[2:, :, 3, :, ...] = input[2:, :, 3, :, ...]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:reverseSequence-39-" class="def">reverseSequence'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tlen)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>seq_dim</strong>: The dimension which is partially reversed.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The input to reverse.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tlen</td><td class="doc"><p><strong>seq_lengths</strong>: 1-D with length `input.dims(batch_dim)` and
|
|
`max(seq_lengths) < input.dims(seq_dim)`</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The partially reversed input. It has the same shape as <code>input</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:reverseV2" class="def">reverseV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>tensor</strong>: Up to 8-D.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>axis</strong>: 1-D. The indices of the dimensions to reverse.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The same shape as <code>tensor</code>.</p></td></tr></table></div><div class="doc"><p>Reverses specific dimensions of a tensor.</p><p>NOTE `tf.reverse` has now changed behavior in preparation for 1.0.
|
|
`tf.reverse_v2` is currently an alias that will be deprecated before TF 1.0.</p><p>Given a <code>tensor</code>, and a <code>int32</code> tensor <code>axis</code> representing the set of
|
|
dimensions of <code>tensor</code> to reverse. This operation reverses each dimension
|
|
<code>i</code> for which there exists <code>j</code> s.t. `axis[j] == i`.</p><p><code>tensor</code> can have up to 8 dimensions. The number of dimensions specified
|
|
in <code>axis</code> may be 0 or more entries. If an index is specified more than
|
|
once, a InvalidArgument error is raised.</p><p>For example:</p><p>```prettyprint
|
|
# tensor <code>t</code> is [[[[ 0, 1, 2, 3],
|
|
# [ 4, 5, 6, 7],
|
|
# [ 8, 9, 10, 11]],
|
|
# [[12, 13, 14, 15],
|
|
# [16, 17, 18, 19],
|
|
# [20, 21, 22, 23]]]]
|
|
# tensor <code>t</code> shape is [1, 2, 3, 4]</p><p># <code>dims</code> is [3] or <code>dims</code> is -1
|
|
reverse(t, dims) ==> [[[[ 3, 2, 1, 0],
|
|
[ 7, 6, 5, 4],
|
|
[ 11, 10, 9, 8]],
|
|
[[15, 14, 13, 12],
|
|
[19, 18, 17, 16],
|
|
[23, 22, 21, 20]]]]</p><p># <code>dims</code> is '[1]' (or <code>dims</code> is '[-3]')
|
|
reverse(t, dims) ==> [[[[12, 13, 14, 15],
|
|
[16, 17, 18, 19],
|
|
[20, 21, 22, 23]
|
|
[[ 0, 1, 2, 3],
|
|
[ 4, 5, 6, 7],
|
|
[ 8, 9, 10, 11]]]]</p><p># <code>dims</code> is '[2]' (or <code>dims</code> is '[-2]')
|
|
reverse(t, dims) ==> [[[[8, 9, 10, 11],
|
|
[4, 5, 6, 7],
|
|
[0, 1, 2, 3]]
|
|
[[20, 21, 22, 23],
|
|
[16, 17, 18, 19],
|
|
[12, 13, 14, 15]]]]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:reverseV2-39-" class="def">reverseV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>tensor</strong>: Up to 8-D.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>axis</strong>: 1-D. The indices of the dimensions to reverse.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The same shape as <code>tensor</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:rint" class="def">rint</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Returns element-wise integer closest to x.</p><p>If the result is midway between two representable values,
|
|
the even representable is chosen.
|
|
For example:</p><p>```
|
|
rint(-1.5) ==> -2.0
|
|
rint(0.5000001) ==> 1.0
|
|
rint([-1.7, -1.5, -0.2, 0.2, 1.5, 1.7, 2.0]) ==> [-2., -2., -0., 0., 2., 2., 2.]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:rint-39-" class="def">rint'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:round" class="def">round</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Rounds the values of a tensor to the nearest integer, element-wise.</p><p>Rounds half to even. Also known as bankers rounding. If you want to round
|
|
according to the current system rounding mode use std::cint.</p></div></div><div class="top"><p class="src"><a name="v:round-39-" class="def">round'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:rsqrt" class="def">rsqrt</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes reciprocal of square root of x element-wise.</p><p>I.e., \(y = 1 / sqrt{x}\).</p></div></div><div class="top"><p class="src"><a name="v:rsqrt-39-" class="def">rsqrt'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:rsqrtGrad" class="def">rsqrtGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Computes the gradient for the rsqrt of <code>x</code> wrt its input.</p><p>Specifically, `grad = dy * -0.5 * y^3`, where `y = rsqrt(x)`, and <code>dy</code>
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|
is the corresponding input gradient.</p></div></div><div class="top"><p class="src"><a name="v:rsqrtGrad-39-" class="def">rsqrtGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sampleDistortedBoundingBox" class="def">sampleDistortedBoundingBox</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>image_size</strong>: 1-D, containing `[height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>bounding_boxes</strong>: 3-D with shape `[batch, N, 4]` describing the N bounding boxes
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|
associated with the image.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>begin</strong>, <strong>size</strong>, <strong>bboxes</strong>)</p><ul><li><strong>begin</strong>: 1-D, containing `[offset_height, offset_width, 0]`. Provide as input to
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`tf.slice`.</li><li><strong>size</strong>: 1-D, containing `[target_height, target_width, -1]`. Provide as input to
|
|
`tf.slice`.</li><li><strong>bboxes</strong>: 3-D with shape `[1, 1, 4]` containing the distorted bounding box.
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Provide as input to `tf.image.draw_bounding_boxes`.</li></ul></td></tr></table></div><div class="doc"><p>Generate a single randomly distorted bounding box for an image.</p><p>Bounding box annotations are often supplied in addition to ground-truth labels
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|
in image recognition or object localization tasks. A common technique for
|
|
training such a system is to randomly distort an image while preserving
|
|
its content, i.e. *data augmentation*. This Op outputs a randomly distorted
|
|
localization of an object, i.e. bounding box, given an <code>image_size</code>,
|
|
<code>bounding_boxes</code> and a series of constraints.</p><p>The output of this Op is a single bounding box that may be used to crop the
|
|
original image. The output is returned as 3 tensors: <code>begin</code>, <code><a href="TensorFlow-GenOps-Core.html#v:size">size</a></code> and
|
|
<code>bboxes</code>. The first 2 tensors can be fed directly into `tf.slice` to crop the
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|
image. The latter may be supplied to `tf.image.draw_bounding_boxes` to visualize
|
|
what the bounding box looks like.</p><p>Bounding boxes are supplied and returned as `[y_min, x_min, y_max, x_max]`. The
|
|
bounding box coordinates are floats in `[0.0, 1.0]` relative to the width and
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|
height of the underlying image.</p><p>For example,</p><p>```python
|
|
# Generate a single distorted bounding box.
|
|
begin, size, bbox_for_draw = tf.image.sample_distorted_bounding_box(
|
|
tf.shape(image),
|
|
bounding_boxes=bounding_boxes)</p><p># Draw the bounding box in an image summary.
|
|
image_with_box = tf.image.draw_bounding_boxes(tf.expand_dims(image, 0),
|
|
bbox_for_draw)
|
|
tf.image_summary(<code>images_with_box</code>, image_with_box)</p><p># Employ the bounding box to distort the image.
|
|
distorted_image = tf.slice(image, begin, size)
|
|
```</p><p>Note that if no bounding box information is available, setting
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|
`use_image_if_no_bounding_boxes = true` will assume there is a single implicit
|
|
bounding box covering the whole image. If <code>use_image_if_no_bounding_boxes</code> is
|
|
false and no bounding boxes are supplied, an error is raised.</p></div></div><div class="top"><p class="src"><a name="v:sampleDistortedBoundingBox-39-" class="def">sampleDistortedBoundingBox'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>image_size</strong>: 1-D, containing `[height, width, channels]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>bounding_boxes</strong>: 3-D with shape `[batch, N, 4]` describing the N bounding boxes
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|
associated with the image.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>begin</strong>, <strong>size</strong>, <strong>bboxes</strong>)</p><ul><li><strong>begin</strong>: 1-D, containing `[offset_height, offset_width, 0]`. Provide as input to
|
|
`tf.slice`.</li><li><strong>size</strong>: 1-D, containing `[target_height, target_width, -1]`. Provide as input to
|
|
`tf.slice`.</li><li><strong>bboxes</strong>: 3-D with shape `[1, 1, 4]` containing the distorted bounding box.
|
|
Provide as input to `tf.image.draw_bounding_boxes`.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:save" class="def">save</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>filename</strong>: Must have a single element. The name of the file to which we write
|
|
the tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tensor_names</strong>: Shape `[N]`. The names of the tensors to be saved.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'3 t</td><td class="doc"><p><strong>data</strong>: <code>N</code> tensors to save.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Saves the input tensors to disk.</p><p>The size of <code>tensor_names</code> must match the number of tensors in `data`. `data[i]`
|
|
is written to <code>filename</code> with name `tensor_names[i]`.</p><p>See also <code>SaveSlices</code>.</p></div></div><div class="top"><p class="src"><a name="v:save-39-" class="def">save'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>filename</strong>: Must have a single element. The name of the file to which we write
|
|
the tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tensor_names</strong>: Shape `[N]`. The names of the tensors to be saved.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'3 t</td><td class="doc"><p><strong>data</strong>: <code>N</code> tensors to save.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:saveSlices" class="def">saveSlices</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>filename</strong>: Must have a single element. The name of the file to which we write the
|
|
tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tensor_names</strong>: Shape `[N]`. The names of the tensors to be saved.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>shapes_and_slices</strong>: Shape `[N]`. The shapes and slice specifications to use when
|
|
saving the tensors.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'4 t</td><td class="doc"><p><strong>data</strong>: <code>N</code> tensors to save.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Saves input tensors slices to disk.</p><p>This is like <code>Save</code> except that tensors can be listed in the saved file as being
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a slice of a larger tensor. <code>shapes_and_slices</code> specifies the shape of the
|
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larger tensor and the slice that this tensor covers. <code>shapes_and_slices</code> must
|
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have as many elements as <code>tensor_names</code>.</p><p>Elements of the <code>shapes_and_slices</code> input must either be:</p><ul><li>The empty string, in which case the corresponding tensor is
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|
saved normally.</li><li>A string of the form `dim0 dim1 ... dimN-1 slice-spec` where the
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<code>dimI</code> are the dimensions of the larger tensor and `slice-spec`
|
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specifies what part is covered by the tensor to save.</li></ul><p>`slice-spec` itself is a <code>:</code>-separated list: `slice0:slice1:...:sliceN-1`
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where each <code>sliceI</code> is either:</p><ul><li>The string <code><a href="../base-4.8.2.0/Prelude.html#v:-45-">-</a></code> meaning that the slice covers all indices of this dimension</li><li>`start,length` where <code>start</code> and <code><a href="../base-4.8.2.0/Data-Foldable.html#v:length">length</a></code> are integers. In that
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case the slice covers <code><a href="../base-4.8.2.0/Data-Foldable.html#v:length">length</a></code> indices starting at <code>start</code>.</li></ul><p>See also <code>Save</code>.</p></div></div><div class="top"><p class="src"><a name="v:saveSlices-39-" class="def">saveSlices'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>filename</strong>: Must have a single element. The name of the file to which we write the
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tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tensor_names</strong>: Shape `[N]`. The names of the tensors to be saved.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>shapes_and_slices</strong>: Shape `[N]`. The shapes and slice specifications to use when
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saving the tensors.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'4 t</td><td class="doc"><p><strong>data</strong>: <code>N</code> tensors to save.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:saveV2" class="def">saveV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> dtypes)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>prefix</strong>: Must have a single element. The prefix of the V2 checkpoint to which we
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write the tensors.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tensor_names</strong>: shape {N}. The names of the tensors to be saved.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>shape_and_slices</strong>: shape {N}. The slice specs of the tensors to be saved.
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Empty strings indicate that they are non-partitioned tensors.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'4 dtypes</td><td class="doc"><p><strong>tensors</strong>: <code>N</code> tensors to save.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Saves tensors in V2 checkpoint format.</p><p>By default, saves the named tensors in full. If the caller wishes to save
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specific slices of full tensors, "shape_and_slices" should be non-empty strings
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|
and correspondingly well-formed.</p></div></div><div class="top"><p class="src"><a name="v:saveV2-39-" class="def">saveV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> dtypes)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>prefix</strong>: Must have a single element. The prefix of the V2 checkpoint to which we
|
|
write the tensors.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tensor_names</strong>: shape {N}. The names of the tensors to be saved.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>shape_and_slices</strong>: shape {N}. The slice specs of the tensors to be saved.
|
|
Empty strings indicate that they are non-partitioned tensors.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'4 dtypes</td><td class="doc"><p><strong>tensors</strong>: <code>N</code> tensors to save.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:scalarSummary" class="def">scalarSummary</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tags</strong>: Tags for the summary.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>values</strong>: Same shape as `tags. Values for the summary.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>summary</strong>: Scalar. Serialized <code>Summary</code> protocol buffer.</p></td></tr></table></div><div class="doc"><p>Outputs a <code>Summary</code> protocol buffer with scalar values.</p><p>The input <code>tags</code> and <code>values</code> must have the same shape. The generated summary
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has a summary value for each tag-value pair in <code>tags</code> and <code>values</code>.</p></div></div><div class="top"><p class="src"><a name="v:scalarSummary-39-" class="def">scalarSummary'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>tags</strong>: Tags for the summary.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>values</strong>: Same shape as `tags. Values for the summary.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>summary</strong>: Scalar. Serialized <code>Summary</code> protocol buffer.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:scatterAdd" class="def">scatterAdd</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: Should be from a <code>Variable</code> node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: A tensor of indices into the first dimension of <code>ref</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>updates</strong>: A tensor of updated values to add to <code>ref</code>.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: = Same as <code>ref</code>. Returned as a convenience for operations that want
|
|
to use the updated values after the update is done.</p></td></tr></table></div><div class="doc"><p>Adds sparse updates to a variable reference.</p><p>This operation computes</p><p># Scalar indices
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ref[indices, ...] += updates[...]</p><p># Vector indices (for each i)
|
|
ref[indices[i], ...] += updates[i, ...]</p><p># High rank indices (for each i, ..., j)
|
|
ref[indices[i, ..., j], ...] += updates[i, ..., j, ...]</p><p>This operation outputs <code>ref</code> after the update is done.
|
|
This makes it easier to chain operations that need to use the reset value.</p><p>Duplicate entries are handled correctly: if multiple <code>indices</code> reference
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|
the same location, their contributions add.</p><p>Requires `updates.shape = indices.shape + ref.shape[1:]`.</p><p><a href="div">style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;"</a>
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<a href="img">style="width:100%" src="../../images/ScatterAdd.png" alt</a>
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<a href="/div">/div</a></p></div></div><div class="top"><p class="src"><a name="v:scatterAdd-39-" class="def">scatterAdd'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: Should be from a <code>Variable</code> node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: A tensor of indices into the first dimension of <code>ref</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>updates</strong>: A tensor of updated values to add to <code>ref</code>.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: = Same as <code>ref</code>. Returned as a convenience for operations that want
|
|
to use the updated values after the update is done.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:scatterDiv" class="def">scatterDiv</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: Should be from a <code>Variable</code> node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: A tensor of indices into the first dimension of <code>ref</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>updates</strong>: A tensor of values that <code>ref</code> is divided by.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: = Same as <code>ref</code>. Returned as a convenience for operations that want
|
|
to use the updated values after the update is done.</p></td></tr></table></div><div class="doc"><p>Divides a variable reference by sparse updates.</p><p>This operation computes</p><p># Scalar indices
|
|
ref[indices, ...] /= updates[...]</p><p># Vector indices (for each i)
|
|
ref[indices[i], ...] /= updates[i, ...]</p><p># High rank indices (for each i, ..., j)
|
|
ref[indices[i, ..., j], ...] /= updates[i, ..., j, ...]</p><p>This operation outputs <code>ref</code> after the update is done.
|
|
This makes it easier to chain operations that need to use the reset value.</p><p>Duplicate entries are handled correctly: if multiple <code>indices</code> reference
|
|
the same location, their contributions divide.</p><p>Requires `updates.shape = indices.shape + ref.shape[1:]`.</p></div></div><div class="top"><p class="src"><a name="v:scatterDiv-39-" class="def">scatterDiv'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: Should be from a <code>Variable</code> node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: A tensor of indices into the first dimension of <code>ref</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>updates</strong>: A tensor of values that <code>ref</code> is divided by.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: = Same as <code>ref</code>. Returned as a convenience for operations that want
|
|
to use the updated values after the update is done.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:scatterMul" class="def">scatterMul</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: Should be from a <code>Variable</code> node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: A tensor of indices into the first dimension of <code>ref</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>updates</strong>: A tensor of updated values to multiply to <code>ref</code>.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: = Same as <code>ref</code>. Returned as a convenience for operations that want
|
|
to use the updated values after the update is done.</p></td></tr></table></div><div class="doc"><p>Multiplies sparse updates into a variable reference.</p><p>This operation computes</p><p># Scalar indices
|
|
ref[indices, ...] *= updates[...]</p><p># Vector indices (for each i)
|
|
ref[indices[i], ...] *= updates[i, ...]</p><p># High rank indices (for each i, ..., j)
|
|
ref[indices[i, ..., j], ...] *= updates[i, ..., j, ...]</p><p>This operation outputs <code>ref</code> after the update is done.
|
|
This makes it easier to chain operations that need to use the reset value.</p><p>Duplicate entries are handled correctly: if multiple <code>indices</code> reference
|
|
the same location, their contributions multiply.</p><p>Requires `updates.shape = indices.shape + ref.shape[1:]`.</p></div></div><div class="top"><p class="src"><a name="v:scatterMul-39-" class="def">scatterMul'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: Should be from a <code>Variable</code> node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: A tensor of indices into the first dimension of <code>ref</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>updates</strong>: A tensor of updated values to multiply to <code>ref</code>.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: = Same as <code>ref</code>. Returned as a convenience for operations that want
|
|
to use the updated values after the update is done.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:scatterNd" class="def">scatterNd</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tindices</td><td class="doc"><p><strong>indices</strong>: A Tensor. Must be one of the following types: int32, int64.
|
|
A tensor of indices into ref.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>updates</strong>: A Tensor. Must have the same type as tensor. A tensor of updated values
|
|
to store in ref.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tindices</td><td class="doc"><p><strong>shape</strong>: A vector. The shape of the resulting tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: A new tensor with the given shape and updates applied according
|
|
to the indices.</p></td></tr></table></div><div class="doc"><p>Creates a new tensor by applying sparse <code>updates</code> to individual</p><p>values or slices within a zero tensor of the given <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> tensor according to
|
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indices. This operator is the inverse of the <a href="#gather_nd">tf.gather_nd</a>
|
|
operator which extracts values or slices from a given tensor.</p><p>TODO(simister): Add a link to Variable.<strong>getitem</strong> documentation on slice
|
|
syntax.</p><p><code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> is a <code>TensorShape</code> with rank <code>P</code> and <code>indices</code> is a <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> of rank
|
|
<code>Q</code>.</p><p><code>indices</code> must be integer tensor, containing indices into <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code>.
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It must be shape `[d_0, ..., d_{Q-2}, K]` where `0 < K <= P`.</p><p>The innermost dimension of <code>indices</code> (with length <code>K</code>) corresponds to
|
|
indices into elements (if `K = P`) or slices (if `K < P`) along the <code>K</code>th
|
|
dimension of <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code>.</p><p><code>updates</code> is Tensor of rank `Q-1+P-K` with shape:</p><p>```
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|
[d_0, ..., d_{Q-2}, shape[K], ..., shape[P-1]].
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|
```</p><p>The simplest form of scatter is to insert individual elements in a tensor by
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index. For example, say we want to insert 4 scattered elements in a rank-1
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|
tensor with 8 elements.</p><p><a href="div">style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;"</a>
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<a href="img">style="width:100%" src="../../images/ScatterNd1.png" alt</a>
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<a href="/div">/div</a></p><p>In Python, this scatter operation would look like this:</p><p>indices = tf.constant([[4], [3], [1], [7]])
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updates = tf.constant([9, 10, 11, 12])
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shape = tf.constant([8])
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|
scatter = tf.scatter_nd(indices, updates, shape)
|
|
with tf.Session() as sess:
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print sess.run(scatter)</p><p>The resulting tensor would look like this:</p><dl><dt>0, 11, 0, 10, 9, 0, 0, 12</dt><dd></dd></dl><p>We can also, insert entire slices of a higher rank tensor all at once. For
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|
example, if we wanted to insert two slices in the first dimension of a
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|
rank-3 tensor with two matrices of new values.</p><p><a href="div">style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;"</a>
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<a href="img">style="width:100%" src="../../images/ScatterNd2.png" alt</a>
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<a href="/div">/div</a></p><p>In Python, this scatter operation would look like this:</p><p>indices = tf.constant([[0], [2]])
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updates = tf.constant([[[5, 5, 5, 5], [6, 6, 6, 6],
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[7, 7, 7, 7], [8, 8, 8, 8]],
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[[5, 5, 5, 5], [6, 6, 6, 6],
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[7, 7, 7, 7], [8, 8, 8, 8]]])
|
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shape = tf.constant([4, 4, 4])
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scatter = tf.scatter_nd(indices, updates, shape)
|
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with tf.Session() as sess:
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print sess.run(scatter)</p><p>The resulting tensor would look like this:</p><dl><dt>[[5, 5, 5, 5</dt><dd>, [6, 6, 6, 6], [7, 7, 7, 7], [8, 8, 8, 8]],</dd><dt>[0, 0, 0, 0</dt><dd>, [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]],</dd><dt>[5, 5, 5, 5</dt><dd>, [6, 6, 6, 6], [7, 7, 7, 7], [8, 8, 8, 8]],</dd><dt>[0, 0, 0, 0</dt><dd>, [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]]</dd></dl></div></div><div class="top"><p class="src"><a name="v:scatterNd-39-" class="def">scatterNd'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tindices</td><td class="doc"><p><strong>indices</strong>: A Tensor. Must be one of the following types: int32, int64.
|
|
A tensor of indices into ref.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>updates</strong>: A Tensor. Must have the same type as tensor. A tensor of updated values
|
|
to store in ref.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tindices</td><td class="doc"><p><strong>shape</strong>: A vector. The shape of the resulting tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: A new tensor with the given shape and updates applied according
|
|
to the indices.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:scatterNdAdd" class="def">scatterNdAdd</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: A mutable Tensor. Should be from a Variable node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: A Tensor. Must be one of the following types: int32, int64.
|
|
A tensor of indices into ref.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>updates</strong>: A Tensor. Must have the same type as ref. A tensor of updated values
|
|
to add to ref.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: Same as ref. Returned as a convenience for operations that want
|
|
to use the updated values after the update is done.</p></td></tr></table></div><div class="doc"><p>Applies sparse addition between <code>updates</code> and individual values or slices</p><p>within a given variable according to <code>indices</code>.</p><p><code>ref</code> is a <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with rank <code>P</code> and <code>indices</code> is a <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> of rank <code>Q</code>.</p><p><code>indices</code> must be integer tensor, containing indices into <code>ref</code>.
|
|
It must be shape `[d_0, ..., d_{Q-2}, K]` where `0 < K <= P`.</p><p>The innermost dimension of <code>indices</code> (with length <code>K</code>) corresponds to
|
|
indices into elements (if `K = P`) or slices (if `K < P`) along the <code>K</code>th
|
|
dimension of <code>ref</code>.</p><p><code>updates</code> is <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> of rank `Q-1+P-K` with shape:</p><p>```
|
|
[d_0, ..., d_{Q-2}, ref.shape[K], ..., ref.shape[P-1]].
|
|
```</p><p>For example, say we want to add 4 scattered elements to a rank-1 tensor to 8
|
|
elements. In Python, that addition would look like this:</p><p>ref = tf.Variable([1, 2, 3, 4, 5, 6, 7, 8])
|
|
indices = tf.constant([[4], [3], [1], [7]])
|
|
updates = tf.constant([9, 10, 11, 12])
|
|
add = tf.scatter_nd_add(ref, indices, updates)
|
|
with tf.Session() as sess:
|
|
print sess.run(add)</p><p>The resulting update to ref would look like this:</p><dl><dt>1, 13, 3, 14, 14, 6, 7, 20</dt><dd></dd></dl><p>See <a href="#scatter_nd">tf.scatter_nd</a> for more details about how to make updates to
|
|
slices.</p></div></div><div class="top"><p class="src"><a name="v:scatterNdAdd-39-" class="def">scatterNdAdd'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: A mutable Tensor. Should be from a Variable node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: A Tensor. Must be one of the following types: int32, int64.
|
|
A tensor of indices into ref.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>updates</strong>: A Tensor. Must have the same type as ref. A tensor of updated values
|
|
to add to ref.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: Same as ref. Returned as a convenience for operations that want
|
|
to use the updated values after the update is done.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:scatterNdSub" class="def">scatterNdSub</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: A mutable Tensor. Should be from a Variable node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: A Tensor. Must be one of the following types: int32, int64.
|
|
A tensor of indices into ref.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>updates</strong>: A Tensor. Must have the same type as ref. A tensor of updated values
|
|
to subtract from ref.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: Same as ref. Returned as a convenience for operations that want
|
|
to use the updated values after the update is done.</p></td></tr></table></div><div class="doc"><p>Applies sparse subtraction between <code>updates</code> and individual values or slices</p><p>within a given variable according to <code>indices</code>.</p><p><code>ref</code> is a <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with rank <code>P</code> and <code>indices</code> is a <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> of rank <code>Q</code>.</p><p><code>indices</code> must be integer tensor, containing indices into <code>ref</code>.
|
|
It must be shape `[d_0, ..., d_{Q-2}, K]` where `0 < K <= P`.</p><p>The innermost dimension of <code>indices</code> (with length <code>K</code>) corresponds to
|
|
indices into elements (if `K = P`) or slices (if `K < P`) along the <code>K</code>th
|
|
dimension of <code>ref</code>.</p><p><code>updates</code> is <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> of rank `Q-1+P-K` with shape:</p><p>```
|
|
[d_0, ..., d_{Q-2}, ref.shape[K], ..., ref.shape[P-1]].
|
|
```</p><p>For example, say we want to subtract 4 scattered elements from a rank-1 tensor
|
|
with 8 elements. In Python, that subtraction would look like this:</p><p>ref = tf.Variable([1, 2, 3, 4, 5, 6, 7, 8])
|
|
indices = tf.constant([[4], [3], [1], [7]])
|
|
updates = tf.constant([9, 10, 11, 12])
|
|
sub = tf.scatter_nd_sub(ref, indices, updates)
|
|
with tf.Session() as sess:
|
|
print sess.run(sub)</p><p>The resulting update to ref would look like this:</p><dl><dt>1, -9, 3, -6, -4, 6, 7, -4</dt><dd></dd></dl><p>See <a href="#scatter_nd">tf.scatter_nd</a> for more details about how to make updates to
|
|
slices.</p></div></div><div class="top"><p class="src"><a name="v:scatterNdSub-39-" class="def">scatterNdSub'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: A mutable Tensor. Should be from a Variable node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: A Tensor. Must be one of the following types: int32, int64.
|
|
A tensor of indices into ref.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>updates</strong>: A Tensor. Must have the same type as ref. A tensor of updated values
|
|
to subtract from ref.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: Same as ref. Returned as a convenience for operations that want
|
|
to use the updated values after the update is done.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:scatterNdUpdate" class="def">scatterNdUpdate</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: A mutable Tensor. Should be from a Variable node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: A Tensor. Must be one of the following types: int32, int64.
|
|
A tensor of indices into ref.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>updates</strong>: A Tensor. Must have the same type as ref. A tensor of updated
|
|
values to add to ref.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: Same as ref. Returned as a convenience for operations that want to
|
|
use the updated values after the update is done.</p></td></tr></table></div><div class="doc"><p>Applies sparse <code>updates</code> to individual values or slices within a given</p><p>variable according to <code>indices</code>.</p><p><code>ref</code> is a <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with rank <code>P</code> and <code>indices</code> is a <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> of rank <code>Q</code>.</p><p><code>indices</code> must be integer tensor, containing indices into <code>ref</code>.
|
|
It must be shape `[d_0, ..., d_{Q-2}, K]` where `0 < K <= P`.</p><p>The innermost dimension of <code>indices</code> (with length <code>K</code>) corresponds to
|
|
indices into elements (if `K = P`) or slices (if `K < P`) along the <code>K</code>th
|
|
dimension of <code>ref</code>.</p><p><code>updates</code> is <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> of rank `Q-1+P-K` with shape:</p><p>```
|
|
[d_0, ..., d_{Q-2}, ref.shape[K], ..., ref.shape[P-1]].
|
|
```</p><p>For example, say we want to update 4 scattered elements to a rank-1 tensor to
|
|
8 elements. In Python, that update would look like this:</p><p>ref = tf.Variable([1, 2, 3, 4, 5, 6, 7, 8])
|
|
indices = tf.constant([[4], [3], [1] ,[7]])
|
|
updates = tf.constant([9, 10, 11, 12])
|
|
update = tf.scatter_nd_update(ref, indices, updates)
|
|
with tf.Session() as sess:
|
|
print sess.run(update)</p><p>The resulting update to ref would look like this:</p><dl><dt>1, 11, 3, 10, 9, 6, 7, 12</dt><dd></dd></dl><p>See <a href="#scatter_nd">tf.scatter_nd</a> for more details about how to make updates to
|
|
slices.</p></div></div><div class="top"><p class="src"><a name="v:scatterNdUpdate-39-" class="def">scatterNdUpdate'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: A mutable Tensor. Should be from a Variable node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: A Tensor. Must be one of the following types: int32, int64.
|
|
A tensor of indices into ref.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>updates</strong>: A Tensor. Must have the same type as ref. A tensor of updated
|
|
values to add to ref.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: Same as ref. Returned as a convenience for operations that want to
|
|
use the updated values after the update is done.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:scatterSub" class="def">scatterSub</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: Should be from a <code>Variable</code> node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: A tensor of indices into the first dimension of <code>ref</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>updates</strong>: A tensor of updated values to subtract from <code>ref</code>.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: = Same as <code>ref</code>. Returned as a convenience for operations that want
|
|
to use the updated values after the update is done.</p></td></tr></table></div><div class="doc"><p>Subtracts sparse updates to a variable reference.</p><p># Scalar indices
|
|
ref[indices, ...] -= updates[...]</p><p># Vector indices (for each i)
|
|
ref[indices[i], ...] -= updates[i, ...]</p><p># High rank indices (for each i, ..., j)
|
|
ref[indices[i, ..., j], ...] -= updates[i, ..., j, ...]</p><p>This operation outputs <code>ref</code> after the update is done.
|
|
This makes it easier to chain operations that need to use the reset value.</p><p>Duplicate entries are handled correctly: if multiple <code>indices</code> reference
|
|
the same location, their (negated) contributions add.</p><p>Requires `updates.shape = indices.shape + ref.shape[1:]`.</p><p><a href="div">style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;"</a>
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<a href="img">style="width:100%" src="../../images/ScatterSub.png" alt</a>
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<a href="/div">/div</a></p></div></div><div class="top"><p class="src"><a name="v:scatterSub-39-" class="def">scatterSub'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: Should be from a <code>Variable</code> node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: A tensor of indices into the first dimension of <code>ref</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>updates</strong>: A tensor of updated values to subtract from <code>ref</code>.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: = Same as <code>ref</code>. Returned as a convenience for operations that want
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|
to use the updated values after the update is done.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:scatterUpdate" class="def">scatterUpdate</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: Should be from a <code>Variable</code> node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: A tensor of indices into the first dimension of <code>ref</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>updates</strong>: A tensor of updated values to store in <code>ref</code>.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: = Same as <code>ref</code>. Returned as a convenience for operations that want
|
|
to use the updated values after the update is done.</p></td></tr></table></div><div class="doc"><p>Applies sparse updates to a variable reference.</p><p>This operation computes</p><p># Scalar indices
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ref[indices, ...] = updates[...]</p><p># Vector indices (for each i)
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ref[indices[i], ...] = updates[i, ...]</p><p># High rank indices (for each i, ..., j)
|
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ref[indices[i, ..., j], ...] = updates[i, ..., j, ...]</p><p>This operation outputs <code>ref</code> after the update is done.
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This makes it easier to chain operations that need to use the reset value.</p><p>If values in <code>ref</code> is to be updated more than once, because there are
|
|
duplicate entries in <code>indices</code>, the order at which the updates happen
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for each value is undefined.</p><p>Requires `updates.shape = indices.shape + ref.shape[1:]`.</p><p><a href="div">style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;"</a>
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<a href="img">style="width:100%" src="../../images/ScatterUpdate.png" alt</a>
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<a href="/div">/div</a></p></div></div><div class="top"><p class="src"><a name="v:scatterUpdate-39-" class="def">scatterUpdate'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong>: Should be from a <code>Variable</code> node.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>indices</strong>: A tensor of indices into the first dimension of <code>ref</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>updates</strong>: A tensor of updated values to store in <code>ref</code>.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong>: = Same as <code>ref</code>. Returned as a convenience for operations that want
|
|
to use the updated values after the update is done.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sdcaFprint" class="def">sdcaFprint</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>input</strong>: vector of strings to compute fingerprints on.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>output</strong>: a (N,2) shaped matrix where N is the number of elements in the input
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vector. Each row contains the low and high parts of the fingerprint.</p></td></tr></table></div><div class="doc"><p>Computes fingerprints of the input strings.</p></div></div><div class="top"><p class="src"><a name="v:sdcaFprint-39-" class="def">sdcaFprint'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>input</strong>: vector of strings to compute fingerprints on.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>output</strong>: a (N,2) shaped matrix where N is the number of elements in the input
|
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vector. Each row contains the low and high parts of the fingerprint.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sdcaOptimizer" class="def">sdcaOptimizer</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>l1</strong>: Symmetric l1 regularization strength.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>l2</strong>: Symmetric l2 regularization strength.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_inner_iterations</strong>: Number of iterations per mini-batch.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_loss_partitions</strong>: Number of partitions of the global loss function.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]</td><td class="doc"><p><strong>sparse_example_indices</strong>: a list of vectors which contain example indices.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]</td><td class="doc"><p><strong>sparse_feature_indices</strong>: a list of vectors which contain feature indices.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]</td><td class="doc"><p><strong>sparse_feature_values</strong>: a list of vectors which contains feature value
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associated with each feature group.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]</td><td class="doc"><p><strong>dense_features</strong>: a list of matrices which contains the dense feature values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>example_weights</strong>: a vector which contains the weight associated with each
|
|
example.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>example_labels</strong>: a vector which contains the label/target associated with each
|
|
example.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]</td><td class="doc"><p><strong>sparse_indices</strong>: a list of vectors where each value is the indices which has
|
|
corresponding weights in sparse_weights. This field maybe ommitted for the
|
|
dense approach.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]</td><td class="doc"><p><strong>sparse_weights</strong>: a list of vectors where each value is the weight associated with
|
|
a sparse feature group.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]</td><td class="doc"><p><strong>dense_weights</strong>: a list of vectors where the values are the weights associated
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|
with a dense feature group.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>example_state_data</strong>: a list of vectors containing the example state data.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>])</td><td class="doc"><p>(<strong>out_example_state_data</strong>, <strong>out_delta_sparse_weights</strong>, <strong>out_delta_dense_weights</strong>)</p><ul><li><strong>out_example_state_data</strong>: a list of vectors containing the updated example state
|
|
data.</li><li><strong>out_delta_sparse_weights</strong>: a list of vectors where each value is the delta
|
|
weights associated with a sparse feature group.</li><li><strong>out_delta_dense_weights</strong>: a list of vectors where the values are the delta
|
|
weights associated with a dense feature group.</li></ul></td></tr></table></div><div class="doc"><p>Distributed version of Stochastic Dual Coordinate Ascent (SDCA) optimizer for</p><p>linear models with L1 + L2 regularization. As global optimization objective is
|
|
strongly-convex, the optimizer optimizes the dual objective at each step. The
|
|
optimizer applies each update one example at a time. Examples are sampled
|
|
uniformly, and the optimizer is learning rate free and enjoys linear convergence
|
|
rate.</p><p>Proximal Stochastic Dual Coordinate Ascent, Shalev-Shwartz, Shai; Zhang, Tong.
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|
2012 arXiv1211.2717S: <a href="http://arxiv.org/pdf/1211.2717v1.pdf">http://arxiv.org/pdf/1211.2717v1.pdf</a></p><p>Loss objective = sum f_{i}(wx_{i}) + (l2 / 2) * |w|^2 + l1 * |w|</p><p>Adding vs. Averaging in Distributed Primal-Dual Optimization.
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|
Chenxin Ma, Virginia Smith, Martin Jaggi, Michael I. Jordan, Peter Richtarik,
|
|
Martin Takac <a href="http://arxiv.org/abs/1502.03508">http://arxiv.org/abs/1502.03508</a></p><p>Stochastic Dual Coordinate Ascent with Adaptive Probabilities
|
|
Dominik Csiba, Zheng Qu, Peter Richtarik <a href="https://arxiv.org/abs/1502.08053">https://arxiv.org/abs/1502.08053</a></p></div></div><div class="top"><p class="src"><a name="v:sdcaOptimizer-39-" class="def">sdcaOptimizer'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>l1</strong>: Symmetric l1 regularization strength.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>l2</strong>: Symmetric l2 regularization strength.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_inner_iterations</strong>: Number of iterations per mini-batch.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_loss_partitions</strong>: Number of partitions of the global loss function.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]</td><td class="doc"><p><strong>sparse_example_indices</strong>: a list of vectors which contain example indices.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]</td><td class="doc"><p><strong>sparse_feature_indices</strong>: a list of vectors which contain feature indices.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]</td><td class="doc"><p><strong>sparse_feature_values</strong>: a list of vectors which contains feature value
|
|
associated with each feature group.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]</td><td class="doc"><p><strong>dense_features</strong>: a list of matrices which contains the dense feature values.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>example_weights</strong>: a vector which contains the weight associated with each
|
|
example.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>example_labels</strong>: a vector which contains the label/target associated with each
|
|
example.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]</td><td class="doc"><p><strong>sparse_indices</strong>: a list of vectors where each value is the indices which has
|
|
corresponding weights in sparse_weights. This field maybe ommitted for the
|
|
dense approach.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]</td><td class="doc"><p><strong>sparse_weights</strong>: a list of vectors where each value is the weight associated with
|
|
a sparse feature group.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]</td><td class="doc"><p><strong>dense_weights</strong>: a list of vectors where the values are the weights associated
|
|
with a dense feature group.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>example_state_data</strong>: a list of vectors containing the example state data.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>])</td><td class="doc"><p>(<strong>out_example_state_data</strong>, <strong>out_delta_sparse_weights</strong>, <strong>out_delta_dense_weights</strong>)</p><ul><li><strong>out_example_state_data</strong>: a list of vectors containing the updated example state
|
|
data.</li><li><strong>out_delta_sparse_weights</strong>: a list of vectors where each value is the delta
|
|
weights associated with a sparse feature group.</li><li><strong>out_delta_dense_weights</strong>: a list of vectors where the values are the delta
|
|
weights associated with a dense feature group.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sdcaShrinkL1" class="def">sdcaShrinkL1</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>l1</strong>: Symmetric l1 regularization strength.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>l2</strong>: Symmetric l2 regularization strength. Should be a positive float.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]</td><td class="doc"><p><strong>weights</strong>: a list of vectors where each value is the weight associated with a
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|
feature group.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Applies L1 regularization shrink step on the parameters.</p></div></div><div class="top"><p class="src"><a name="v:sdcaShrinkL1-39-" class="def">sdcaShrinkL1'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>l1</strong>: Symmetric l1 regularization strength.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>l2</strong>: Symmetric l2 regularization strength. Should be a positive float.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]</td><td class="doc"><p><strong>weights</strong>: a list of vectors where each value is the weight associated with a
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|
feature group.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:segmentMax" class="def">segmentMax</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>segment_ids</strong>: A 1-D tensor whose rank is equal to the rank of `data`'s
|
|
first dimension. Values should be sorted and can be repeated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Has same shape as data, except for dimension 0 which
|
|
has size <code>k</code>, the number of segments.</p></td></tr></table></div><div class="doc"><p>Computes the maximum along segments of a tensor.</p><p>Read <a href="../../api_docs/python/math_ops.md#segmentation">the section on Segmentation</a>
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|
for an explanation of segments.</p><p>Computes a tensor such that
|
|
\(output_i = max_j(data_j)\) where <code><a href="../base-4.8.2.0/Data-Ord.html#v:max">max</a></code> is over <code>j</code> such
|
|
that `segment_ids[j] == i`.</p><p><a href="div">style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;"</a>
|
|
<a href="img">style="width:100%" src="../../images/SegmentMax.png" alt</a>
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<a href="/div">/div</a></p></div></div><div class="top"><p class="src"><a name="v:segmentMax-39-" class="def">segmentMax'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>segment_ids</strong>: A 1-D tensor whose rank is equal to the rank of `data`'s
|
|
first dimension. Values should be sorted and can be repeated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Has same shape as data, except for dimension 0 which
|
|
has size <code>k</code>, the number of segments.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:segmentMean" class="def">segmentMean</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>segment_ids</strong>: A 1-D tensor whose rank is equal to the rank of `data`'s
|
|
first dimension. Values should be sorted and can be repeated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Has same shape as data, except for dimension 0 which
|
|
has size <code>k</code>, the number of segments.</p></td></tr></table></div><div class="doc"><p>Computes the mean along segments of a tensor.</p><p>Read <a href="../../api_docs/python/math_ops.md#segmentation">the section on
|
|
Segmentation</a> for an explanation
|
|
of segments.</p><p>Computes a tensor such that
|
|
\(output_i = frac{sum_j data_j}{N}\) where <code><a href="TensorFlow-GenOps-Core.html#v:mean">mean</a></code> is
|
|
over <code>j</code> such that `segment_ids[j] == i` and <code>N</code> is the total number of
|
|
values summed.</p><p><a href="div">style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;"</a>
|
|
<a href="img">style="width:100%" src="../../images/SegmentMean.png" alt</a>
|
|
<a href="/div">/div</a></p></div></div><div class="top"><p class="src"><a name="v:segmentMean-39-" class="def">segmentMean'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>segment_ids</strong>: A 1-D tensor whose rank is equal to the rank of `data`'s
|
|
first dimension. Values should be sorted and can be repeated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Has same shape as data, except for dimension 0 which
|
|
has size <code>k</code>, the number of segments.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:segmentMin" class="def">segmentMin</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>segment_ids</strong>: A 1-D tensor whose rank is equal to the rank of `data`'s
|
|
first dimension. Values should be sorted and can be repeated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Has same shape as data, except for dimension 0 which
|
|
has size <code>k</code>, the number of segments.</p></td></tr></table></div><div class="doc"><p>Computes the minimum along segments of a tensor.</p><p>Read <a href="../../api_docs/python/math_ops.md#segmentation">the section on
|
|
Segmentation</a> for an explanation
|
|
of segments.</p><p>Computes a tensor such that
|
|
\(output_i = min_j(data_j)\) where <code><a href="../base-4.8.2.0/Data-Ord.html#v:min">min</a></code> is over <code>j</code> such
|
|
that `segment_ids[j] == i`.</p><p><a href="div">style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;"</a>
|
|
<a href="img">style="width:100%" src="../../images/SegmentMin.png" alt</a>
|
|
<a href="/div">/div</a></p></div></div><div class="top"><p class="src"><a name="v:segmentMin-39-" class="def">segmentMin'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>segment_ids</strong>: A 1-D tensor whose rank is equal to the rank of `data`'s
|
|
first dimension. Values should be sorted and can be repeated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Has same shape as data, except for dimension 0 which
|
|
has size <code>k</code>, the number of segments.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:segmentProd" class="def">segmentProd</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>segment_ids</strong>: A 1-D tensor whose rank is equal to the rank of `data`'s
|
|
first dimension. Values should be sorted and can be repeated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Has same shape as data, except for dimension 0 which
|
|
has size <code>k</code>, the number of segments.</p></td></tr></table></div><div class="doc"><p>Computes the product along segments of a tensor.</p><p>Read <a href="../../api_docs/python/math_ops.md#segmentation">the section on
|
|
Segmentation</a> for an explanation
|
|
of segments.</p><p>Computes a tensor such that
|
|
\(output_i = prod_j data_j\) where the product is over <code>j</code> such
|
|
that `segment_ids[j] == i`.</p><p><a href="div">style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;"</a>
|
|
<a href="img">style="width:100%" src="../../images/SegmentProd.png" alt</a>
|
|
<a href="/div">/div</a></p></div></div><div class="top"><p class="src"><a name="v:segmentProd-39-" class="def">segmentProd'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>segment_ids</strong>: A 1-D tensor whose rank is equal to the rank of `data`'s
|
|
first dimension. Values should be sorted and can be repeated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Has same shape as data, except for dimension 0 which
|
|
has size <code>k</code>, the number of segments.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:segmentSum" class="def">segmentSum</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>segment_ids</strong>: A 1-D tensor whose rank is equal to the rank of `data`'s
|
|
first dimension. Values should be sorted and can be repeated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Has same shape as data, except for dimension 0 which
|
|
has size <code>k</code>, the number of segments.</p></td></tr></table></div><div class="doc"><p>Computes the sum along segments of a tensor.</p><p>Read <a href="../../api_docs/python/math_ops.md#segmentation">the section on Segmentation</a>
|
|
for an explanation of segments.</p><p>Computes a tensor such that
|
|
\(output_i = sum_j data_j\) where sum is over <code>j</code> such
|
|
that `segment_ids[j] == i`.</p><p><a href="div">style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;"</a>
|
|
<a href="img">style="width:100%" src="../../images/SegmentSum.png" alt</a>
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<a href="/div">/div</a></p></div></div><div class="top"><p class="src"><a name="v:segmentSum-39-" class="def">segmentSum'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>segment_ids</strong>: A 1-D tensor whose rank is equal to the rank of `data`'s
|
|
first dimension. Values should be sorted and can be repeated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Has same shape as data, except for dimension 0 which
|
|
has size <code>k</code>, the number of segments.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:select" class="def">select</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>condition</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>t</strong>: = A <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> which may have the same shape as <code>condition</code>.
|
|
If <code>condition</code> is rank 1, <code>t</code> may have higher rank,
|
|
but its first dimension must match the size of <code>condition</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>e</strong>: = A <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with the same type and shape as <code>t</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: = A <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with the same type and shape as <code>t</code> and <code>e</code>.</p></td></tr></table></div><div class="doc"><p>Selects elements from <code>t</code> or <code>e</code>, depending on <code>condition</code>.</p><p>The <code>t</code>, and <code>e</code> tensors must all have the same shape, and the
|
|
output will also have that shape.</p><p>The <code>condition</code> tensor must be a scalar if <code>t</code> and <code>e</code> are scalars.
|
|
If <code>t</code> and <code>e</code> are vectors or higher rank, then <code>condition</code> must be either a
|
|
scalar, a vector with size matching the first dimension of <code>t</code>, or must have
|
|
the same shape as <code>t</code>.</p><p>The <code>condition</code> tensor acts as a mask that chooses, based on the value at each
|
|
element, whether the corresponding element / row in the output should be
|
|
taken from <code>t</code> (if true) or <code>e</code> (if false).</p><p>If <code>condition</code> is a vector and <code>t</code> and <code>e</code> are higher rank matrices, then
|
|
it chooses which row (outer dimension) to copy from <code>t</code> and <code>e</code>.
|
|
If <code>condition</code> has the same shape as <code>t</code> and <code>e</code>, then it chooses which
|
|
element to copy from <code>t</code> and <code>e</code>.</p><p>For example:</p><p>```prettyprint
|
|
# <code>condition</code> tensor is [[True, False]
|
|
# [False, True]]
|
|
# <code>t</code> is [[1, 2],
|
|
# [3, 4]]
|
|
# <code>e</code> is [[5, 6],
|
|
# [7, 8]]
|
|
select(condition, t, e) ==> [[1, 6],
|
|
[7, 4]]</p><p># <code>condition</code> tensor is [True, False]
|
|
# <code>t</code> is [[1, 2],
|
|
# [3, 4]]
|
|
# <code>e</code> is [[5, 6],
|
|
# [7, 8]]
|
|
select(condition, t, e) ==> [[1, 2],
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|
[7, 8]]</p><p>```</p></div></div><div class="top"><p class="src"><a name="v:select-39-" class="def">select'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>condition</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>t</strong>: = A <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> which may have the same shape as <code>condition</code>.
|
|
If <code>condition</code> is rank 1, <code>t</code> may have higher rank,
|
|
but its first dimension must match the size of <code>condition</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>e</strong>: = A <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with the same type and shape as <code>t</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: = A <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with the same type and shape as <code>t</code> and <code>e</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:selfAdjointEig" class="def">selfAdjointEig</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape is `[..., M, M]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Shape is `[..., M+1, M]`.</p></td></tr></table></div><div class="doc"><p>Computes the Eigen Decomposition of a batch of square self-adjoint matrices.</p><p>The input is a tensor of shape `[..., M, M]` whose inner-most 2 dimensions
|
|
form square matrices, with the same constraints as the single matrix
|
|
SelfAdjointEig.</p><p>The result is a [..., M+1, M] matrix with [..., 0,:] containing the
|
|
eigenvalues, and subsequent [...,1:, :] containing the eigenvectors.</p></div></div><div class="top"><p class="src"><a name="v:selfAdjointEig-39-" class="def">selfAdjointEig'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: Shape is `[..., M, M]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Shape is `[..., M+1, M]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:selfAdjointEigV2" class="def">selfAdjointEigV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> input of shape `[N, N]`.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>e</strong>, <strong>v</strong>)</p><ul><li><strong>e</strong>: Eigenvalues. Shape is `[N]`.</li><li><strong>v</strong>: Eigenvectors. Shape is `[N, N]`.</li></ul></td></tr></table></div><div class="doc"><p>Computes the eigen decomposition of one or more square self-adjoint matrices.</p><p>Computes the eigenvalues and (optionally) eigenvectors of each inner matrix in
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|
<code>input</code> such that `input[..., :, :] = v[..., :, :] * diag(e[..., :])`.</p><p>```prettyprint
|
|
# a is a tensor.
|
|
# e is a tensor of eigenvalues.
|
|
# v is a tensor of eigenvectors.
|
|
e, v = self_adjoint_eig(a)
|
|
e = self_adjoint_eig(a, compute_v=False)
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:selfAdjointEigV2-39-" class="def">selfAdjointEigV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> input of shape `[N, N]`.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>e</strong>, <strong>v</strong>)</p><ul><li><strong>e</strong>: Eigenvalues. Shape is `[N]`.</li><li><strong>v</strong>: Eigenvectors. Shape is `[N, N]`.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:serializeManySparse" class="def">serializeManySparse</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sparse_indices</strong>: 2-D. The <code>indices</code> of the minibatch <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>sparse_values</strong>: 1-D. The <code>values</code> of the minibatch <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sparse_shape</strong>: 1-D. The <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> of the minibatch <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>serialized_sparse</strong></p></td></tr></table></div><div class="doc"><p>Serialize an <code>N</code>-minibatch <code>SparseTensor</code> into an `[N, 3]` string <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>.</p><p>The <code>SparseTensor</code> must have rank <code>R</code> greater than 1, and the first dimension
|
|
is treated as the minibatch dimension. Elements of the <code>SparseTensor</code>
|
|
must be sorted in increasing order of this first dimension. The serialized
|
|
<code>SparseTensor</code> objects going into each row of <code>serialized_sparse</code> will have
|
|
rank `R-1`.</p><p>The minibatch size <code>N</code> is extracted from `sparse_shape[0]`.</p></div></div><div class="top"><p class="src"><a name="v:serializeManySparse-39-" class="def">serializeManySparse'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sparse_indices</strong>: 2-D. The <code>indices</code> of the minibatch <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>sparse_values</strong>: 1-D. The <code>values</code> of the minibatch <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sparse_shape</strong>: 1-D. The <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> of the minibatch <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>serialized_sparse</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:serializeSparse" class="def">serializeSparse</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sparse_indices</strong>: 2-D. The <code>indices</code> of the <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>sparse_values</strong>: 1-D. The <code>values</code> of the <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sparse_shape</strong>: 1-D. The <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> of the <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>serialized_sparse</strong></p></td></tr></table></div><div class="doc"><p>Serialize a <code>SparseTensor</code> into a string 3-vector (1-D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>) object.</p></div></div><div class="top"><p class="src"><a name="v:serializeSparse-39-" class="def">serializeSparse'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sparse_indices</strong>: 2-D. The <code>indices</code> of the <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>sparse_values</strong>: 1-D. The <code>values</code> of the <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sparse_shape</strong>: 1-D. The <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> of the <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>serialized_sparse</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:setSize" class="def">setSize</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>set_indices</strong>: 2D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, indices of a <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>set_values</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, values of a <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>set_shape</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, shape of a <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong>: For <code>set</code> ranked <code>n</code>, this is a <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with rank `n-1`, and the same 1st
|
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`n-1` dimensions as <code>set</code>. Each value is the number of unique elements in
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|
the corresponding `[0...n-1]` dimension of <code>set</code>.</p></td></tr></table></div><div class="doc"><p>Number of unique elements along last dimension of input <code>set</code>.</p><p>Input <code>set</code> is a <code>SparseTensor</code> represented by <code>set_indices</code>, <code>set_values</code>,
|
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and <code>set_shape</code>. The last dimension contains values in a set, duplicates are
|
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allowed but ignored.</p><p>If <code>validate_indices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code>, this op validates the order and range of <code>set</code>
|
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indices.</p></div></div><div class="top"><p class="src"><a name="v:setSize-39-" class="def">setSize'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>set_indices</strong>: 2D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, indices of a <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>set_values</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, values of a <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>set_shape</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, shape of a <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong>: For <code>set</code> ranked <code>n</code>, this is a <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> with rank `n-1`, and the same 1st
|
|
`n-1` dimensions as <code>set</code>. Each value is the number of unique elements in
|
|
the corresponding `[0...n-1]` dimension of <code>set</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:shape" class="def">shape</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Returns the shape of a tensor.</p><p>This operation returns a 1-D integer tensor representing the shape of <code>input</code>.</p><p>For example:</p><p>```prettyprint
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# <code>t</code> is [[[1, 1, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]]]
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shape(t) ==> [2, 2, 3]
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```</p></div></div><div class="top"><p class="src"><a name="v:shape-39-" class="def">shape'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:shapeN" class="def">shapeN</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t]</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type]</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Returns shape of tensors.</p><p>This operation returns N 1-D integer tensors representing shape of `input[i]s`.</p></div></div><div class="top"><p class="src"><a name="v:shapeN-39-" class="def">shapeN'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t]</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type]</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:shardedFilename" class="def">shardedFilename</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>basename</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>shard</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>num_shards</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>filename</strong></p></td></tr></table></div><div class="doc"><p>Generate a sharded filename. The filename is printf formatted as</p><p>%s-%05d-of-%05d, basename, shard, num_shards.</p></div></div><div class="top"><p class="src"><a name="v:shardedFilename-39-" class="def">shardedFilename'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>basename</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>shard</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>num_shards</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>filename</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:shardedFilespec" class="def">shardedFilespec</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>basename</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>num_shards</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>filename</strong></p></td></tr></table></div><div class="doc"><p>Generate a glob pattern matching all sharded file names.</p></div></div><div class="top"><p class="src"><a name="v:shardedFilespec-39-" class="def">shardedFilespec'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>basename</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>num_shards</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>filename</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sigmoid" class="def">sigmoid</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes sigmoid of <code>x</code> element-wise.</p><p>Specifically, `y = 1 / (1 + exp(-x))`.</p></div></div><div class="top"><p class="src"><a name="v:sigmoid-39-" class="def">sigmoid'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sigmoidGrad" class="def">sigmoidGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Computes the gradient of the sigmoid of <code>x</code> wrt its input.</p><p>Specifically, `grad = dy * y * (1 - y)`, where `y = sigmoid(x)`, and
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<code>dy</code> is the corresponding input gradient.</p></div></div><div class="top"><p class="src"><a name="v:sigmoidGrad-39-" class="def">sigmoidGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sign" class="def">sign</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Returns an element-wise indication of the sign of a number.</p><p>`y = sign(x) = -1` if `x <a href="0`;">0 if `x == 0`; 1 if `x</a> 0`.</p><p>For complex numbers, `y = sign(x) = x / |x|` if `x != 0`, otherwise `y = 0`.</p></div></div><div class="top"><p class="src"><a name="v:sign-39-" class="def">sign'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sin" class="def">sin</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes sin of x element-wise.</p></div></div><div class="top"><p class="src"><a name="v:sin-39-" class="def">sin'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:size" class="def">size</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Returns the size of a tensor.</p><p>This operation returns an integer representing the number of elements in
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<code>input</code>.</p><p>For example:</p><p>```prettyprint
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# <code>t</code> is [[[1, 1,, 1], [2, 2, 2]], [[3, 3, 3], [4, 4, 4]]]]
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size(t) ==> 12
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```</p></div></div><div class="top"><p class="src"><a name="v:size-39-" class="def">size'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:skipgram" class="def">skipgram</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>batch_size</strong>: The size of produced batch.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p>(<strong>vocab_word</strong>, <strong>vocab_freq</strong>, <strong>words_per_epoch</strong>, <strong>current_epoch</strong>, <strong>total_words_processed</strong>, <strong>examples</strong>, <strong>labels</strong>)</p><ul><li><strong>vocab_word</strong>: A vector of words in the corpus.</li><li><strong>vocab_freq</strong>: Frequencies of words. Sorted in the non-ascending order.</li><li><strong>words_per_epoch</strong>: Number of words per epoch in the data file.</li><li><strong>current_epoch</strong>: The current epoch number.</li><li><strong>total_words_processed</strong>: The total number of words processed so far.</li><li><strong>examples</strong>: A vector of word ids.</li><li><strong>labels</strong>: A vector of word ids.</li></ul></td></tr></table></div><div class="doc"><p>Parses a text file and creates a batch of examples.</p></div></div><div class="top"><p class="src"><a name="v:skipgram-39-" class="def">skipgram'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>batch_size</strong>: The size of produced batch.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p>(<strong>vocab_word</strong>, <strong>vocab_freq</strong>, <strong>words_per_epoch</strong>, <strong>current_epoch</strong>, <strong>total_words_processed</strong>, <strong>examples</strong>, <strong>labels</strong>)</p><ul><li><strong>vocab_word</strong>: A vector of words in the corpus.</li><li><strong>vocab_freq</strong>: Frequencies of words. Sorted in the non-ascending order.</li><li><strong>words_per_epoch</strong>: Number of words per epoch in the data file.</li><li><strong>current_epoch</strong>: The current epoch number.</li><li><strong>total_words_processed</strong>: The total number of words processed so far.</li><li><strong>examples</strong>: A vector of word ids.</li><li><strong>labels</strong>: A vector of word ids.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:slice" class="def">slice</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` index)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 index</td><td class="doc"><p><strong>begin</strong>: begin[i] specifies the offset into the <code>i</code>th dimension of
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<code>input</code> to slice from.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 index</td><td class="doc"><p><strong>size</strong>: size[i] specifies the number of elements of the <code>i</code>th dimension
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of <code>input</code> to slice. If size[i] is -1, all remaining elements in dimension
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i are included in the slice (i.e. this is equivalent to setting
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size[i] = input.dim_size(i) - begin[i]).</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Return a slice from <code>input</code>.</p><p>The output tensor is a tensor with dimensions described by <code><a href="TensorFlow-GenOps-Core.html#v:size">size</a></code>
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whose values are extracted from <code>input</code> starting at the offsets in
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<code>begin</code>.</p><ul><li>Requirements*:
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0 <= begin[i] <= begin[i] + size[i] <= Di for i in [0, n)</li></ul></div></div><div class="top"><p class="src"><a name="v:slice-39-" class="def">slice'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` index)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 index</td><td class="doc"><p><strong>begin</strong>: begin[i] specifies the offset into the <code>i</code>th dimension of
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<code>input</code> to slice from.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 index</td><td class="doc"><p><strong>size</strong>: size[i] specifies the number of elements of the <code>i</code>th dimension
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of <code>input</code> to slice. If size[i] is -1, all remaining elements in dimension
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i are included in the slice (i.e. this is equivalent to setting
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size[i] = input.dim_size(i) - begin[i]).</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:softmax" class="def">softmax</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>logits</strong>: 2-D with shape `[batch_size, num_classes]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>softmax</strong>: Same shape as <code>logits</code>.</p></td></tr></table></div><div class="doc"><p>Computes softmax activations.</p><p>For each batch <code>i</code> and class <code>j</code> we have</p><p>softmax[i, j] = exp(logits[i, j]) / sum_j(exp(logits[i, j]))</p></div></div><div class="top"><p class="src"><a name="v:softmax-39-" class="def">softmax'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>logits</strong>: 2-D with shape `[batch_size, num_classes]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>softmax</strong>: Same shape as <code>logits</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:softmaxCrossEntropyWithLogits" class="def">softmaxCrossEntropyWithLogits</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>features</strong>: batch_size x num_classes matrix</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>labels</strong>: batch_size x num_classes matrix
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The caller must ensure that each batch of labels represents a valid
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probability distribution.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>loss</strong>, <strong>backprop</strong>)</p><ul><li><strong>loss</strong>: Per example loss (batch_size vector).</li><li><strong>backprop</strong>: backpropagated gradients (batch_size x num_classes matrix).</li></ul></td></tr></table></div><div class="doc"><p>Computes softmax cross entropy cost and gradients to backpropagate.</p><p>Inputs are the logits, not probabilities.</p></div></div><div class="top"><p class="src"><a name="v:softmaxCrossEntropyWithLogits-39-" class="def">softmaxCrossEntropyWithLogits'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>features</strong>: batch_size x num_classes matrix</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>labels</strong>: batch_size x num_classes matrix
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The caller must ensure that each batch of labels represents a valid
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probability distribution.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>loss</strong>, <strong>backprop</strong>)</p><ul><li><strong>loss</strong>: Per example loss (batch_size vector).</li><li><strong>backprop</strong>: backpropagated gradients (batch_size x num_classes matrix).</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:softplus" class="def">softplus</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>features</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>activations</strong></p></td></tr></table></div><div class="doc"><p>Computes softplus: `log(exp(features) + 1)`.</p></div></div><div class="top"><p class="src"><a name="v:softplus-39-" class="def">softplus'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>features</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>activations</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:softplusGrad" class="def">softplusGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>gradients</strong>: The backpropagated gradients to the corresponding softplus operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>features</strong>: The features passed as input to the corresponding softplus operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>backprops</strong>: The gradients: `gradients / (1 + exp(-features))`.</p></td></tr></table></div><div class="doc"><p>Computes softplus gradients for a softplus operation.</p></div></div><div class="top"><p class="src"><a name="v:softplusGrad-39-" class="def">softplusGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>gradients</strong>: The backpropagated gradients to the corresponding softplus operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>features</strong>: The features passed as input to the corresponding softplus operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>backprops</strong>: The gradients: `gradients / (1 + exp(-features))`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:softsign" class="def">softsign</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>features</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>activations</strong></p></td></tr></table></div><div class="doc"><p>Computes softsign: `features / (abs(features) + 1)`.</p></div></div><div class="top"><p class="src"><a name="v:softsign-39-" class="def">softsign'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>features</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>activations</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:softsignGrad" class="def">softsignGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>gradients</strong>: The backpropagated gradients to the corresponding softsign operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>features</strong>: The features passed as input to the corresponding softsign operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>backprops</strong>: The gradients: `gradients / (1 + abs(-features)) ** 2`.</p></td></tr></table></div><div class="doc"><p>Computes softsign gradients for a softsign operation.</p></div></div><div class="top"><p class="src"><a name="v:softsignGrad-39-" class="def">softsignGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>gradients</strong>: The backpropagated gradients to the corresponding softsign operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>features</strong>: The features passed as input to the corresponding softsign operation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>backprops</strong>: The gradients: `gradients / (1 + abs(-features)) ** 2`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:spaceToBatch" class="def">spaceToBatch</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>block_size</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, height, width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tpaddings</td><td class="doc"><p><strong>paddings</strong>: 2-D tensor of non-negative integers with shape `[2, 2]`. It specifies
|
|
the padding of the input with zeros across the spatial dimensions as follows:</p><p>paddings = [[pad_top, pad_bottom], [pad_left, pad_right]]</p><p>The effective spatial dimensions of the zero-padded input tensor will be:</p><p>height_pad = pad_top + height + pad_bottom
|
|
width_pad = pad_left + width + pad_right</p><p>The attr <code>block_size</code> must be greater than one. It indicates the block size.</p><ul><li>Non-overlapping blocks of size `block_size x block size` in the height and
|
|
width dimensions are rearranged into the batch dimension at each location.</li><li>The batch of the output tensor is `batch * block_size * block_size`.</li><li>Both height_pad and width_pad must be divisible by block_size.</li></ul><p>The shape of the output will be:</p><p>[batch*block_size*block_size, height_pad<em>block_size, width_pad</em>block_size,
|
|
depth]</p><p>Some examples:</p><ol><li>For the following input of shape `[1, 2, 2, 1]` and block_size of 2:</li></ol><p>```prettyprint
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|
x = [[[[1], [2]], [[3], [4]]]]
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|
```</p><p>The output tensor has shape `[4, 1, 1, 1]` and value:</p><p>```prettyprint
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[[[[1]]], [[[2]]], [[[3]]], [[[4]]]]
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```</p><ol><li>For the following input of shape `[1, 2, 2, 3]` and block_size of 2:</li></ol><p>```prettyprint
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|
x = [[[[1, 2, 3], [4, 5, 6]],
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[[7, 8, 9], [10, 11, 12]]]]
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```</p><p>The output tensor has shape `[4, 1, 1, 3]` and value:</p><p>```prettyprint
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[[[1, 2, 3]], [[4, 5, 6]], [[7, 8, 9]], [[10, 11, 12]]]
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```</p><ol><li>For the following input of shape `[1, 4, 4, 1]` and block_size of 2:</li></ol><p>```prettyprint
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|
x = [[[[1], [2], [3], [4]],
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[[5], [6], [7], [8]],
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[[9], [10], [11], [12]],
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|
[[13], [14], [15], [16]]]]
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```</p><p>The output tensor has shape `[4, 2, 2, 1]` and value:</p><p>```prettyprint
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|
x = [[[[1], [3]], [[5], [7]]],
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[[[2], [4]], [[10], [12]]],
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[[[5], [7]], [[13], [15]]],
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|
[[[6], [8]], [[14], [16]]]]
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```</p><ol><li>For the following input of shape `[2, 2, 4, 1]` and block_size of 2:</li></ol><p>```prettyprint
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x = [[[[1], [2], [3], [4]],
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[[5], [6], [7], [8]]],
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[[[9], [10], [11], [12]],
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|
[[13], [14], [15], [16]]]]
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|
```</p><p>The output tensor has shape `[8, 1, 2, 1]` and value:</p><p>```prettyprint
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|
x = [[[[1], [3]]], [[[9], [11]]], [[[2], [4]]], [[[10], [12]]],
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|
[[[5], [7]]], [[[13], [15]]], [[[6], [8]]], [[[14], [16]]]]
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|
```</p><p>Among others, this operation is useful for reducing atrous convolution into
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|
regular convolution.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>SpaceToBatch for 4-D tensors of type T.</p><p>This is a legacy version of the more general SpaceToBatchND.</p><p>Zero-pads and then rearranges (permutes) blocks of spatial data into batch.
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More specifically, this op outputs a copy of the input tensor where values from
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|
the <code>height</code> and <code>width</code> dimensions are moved to the <code>batch</code> dimension. After
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|
the zero-padding, both <code>height</code> and <code>width</code> of the input must be divisible by the
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|
block size.</p></div></div><div class="top"><p class="src"><a name="v:spaceToBatch-39-" class="def">spaceToBatch'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>block_size</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 4-D with shape `[batch, height, width, depth]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tpaddings</td><td class="doc"><p><strong>paddings</strong>: 2-D tensor of non-negative integers with shape `[2, 2]`. It specifies
|
|
the padding of the input with zeros across the spatial dimensions as follows:</p><p>paddings = [[pad_top, pad_bottom], [pad_left, pad_right]]</p><p>The effective spatial dimensions of the zero-padded input tensor will be:</p><p>height_pad = pad_top + height + pad_bottom
|
|
width_pad = pad_left + width + pad_right</p><p>The attr <code>block_size</code> must be greater than one. It indicates the block size.</p><ul><li>Non-overlapping blocks of size `block_size x block size` in the height and
|
|
width dimensions are rearranged into the batch dimension at each location.</li><li>The batch of the output tensor is `batch * block_size * block_size`.</li><li>Both height_pad and width_pad must be divisible by block_size.</li></ul><p>The shape of the output will be:</p><p>[batch*block_size*block_size, height_pad<em>block_size, width_pad</em>block_size,
|
|
depth]</p><p>Some examples:</p><ol><li>For the following input of shape `[1, 2, 2, 1]` and block_size of 2:</li></ol><p>```prettyprint
|
|
x = [[[[1], [2]], [[3], [4]]]]
|
|
```</p><p>The output tensor has shape `[4, 1, 1, 1]` and value:</p><p>```prettyprint
|
|
[[[[1]]], [[[2]]], [[[3]]], [[[4]]]]
|
|
```</p><ol><li>For the following input of shape `[1, 2, 2, 3]` and block_size of 2:</li></ol><p>```prettyprint
|
|
x = [[[[1, 2, 3], [4, 5, 6]],
|
|
[[7, 8, 9], [10, 11, 12]]]]
|
|
```</p><p>The output tensor has shape `[4, 1, 1, 3]` and value:</p><p>```prettyprint
|
|
[[[1, 2, 3]], [[4, 5, 6]], [[7, 8, 9]], [[10, 11, 12]]]
|
|
```</p><ol><li>For the following input of shape `[1, 4, 4, 1]` and block_size of 2:</li></ol><p>```prettyprint
|
|
x = [[[[1], [2], [3], [4]],
|
|
[[5], [6], [7], [8]],
|
|
[[9], [10], [11], [12]],
|
|
[[13], [14], [15], [16]]]]
|
|
```</p><p>The output tensor has shape `[4, 2, 2, 1]` and value:</p><p>```prettyprint
|
|
x = [[[[1], [3]], [[5], [7]]],
|
|
[[[2], [4]], [[10], [12]]],
|
|
[[[5], [7]], [[13], [15]]],
|
|
[[[6], [8]], [[14], [16]]]]
|
|
```</p><ol><li>For the following input of shape `[2, 2, 4, 1]` and block_size of 2:</li></ol><p>```prettyprint
|
|
x = [[[[1], [2], [3], [4]],
|
|
[[5], [6], [7], [8]]],
|
|
[[[9], [10], [11], [12]],
|
|
[[13], [14], [15], [16]]]]
|
|
```</p><p>The output tensor has shape `[8, 1, 2, 1]` and value:</p><p>```prettyprint
|
|
x = [[[[1], [3]]], [[[9], [11]]], [[[2], [4]]], [[[10], [12]]],
|
|
[[[5], [7]]], [[[13], [15]]], [[[6], [8]]], [[[14], [16]]]]
|
|
```</p><p>Among others, this operation is useful for reducing atrous convolution into
|
|
regular convolution.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:spaceToBatchND" class="def">spaceToBatchND</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tblock_shape, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: N-D with shape `input_shape = [batch] + spatial_shape + remaining_shape`,
|
|
where spatial_shape has <code>M</code> dimensions.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tblock_shape</td><td class="doc"><p><strong>block_shape</strong>: 1-D with shape `[M]`, all values must be >= 1.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tpaddings</td><td class="doc"><p><strong>paddings</strong>: 2-D with shape `[M, 2]`, all values must be >= 0.
|
|
`paddings[i] = [pad_start, pad_end]` specifies the padding for input dimension
|
|
`i + 1`, which corresponds to spatial dimension <code>i</code>. It is required that
|
|
`block_shape[i]` divides `input_shape[i + 1] + pad_start + pad_end`.</p><p>This operation is equivalent to the following steps:</p><ol><li>Zero-pad the start and end of dimensions `[1, ..., M]` of the
|
|
input according to <code>paddings</code> to produce <code>padded</code> of shape <code>padded_shape</code>.</li><li>Reshape <code>padded</code> to <code>reshaped_padded</code> of shape:</li></ol><dl><dt>batch</dt><dd>+</dd><dt>padded_shape[1</dt><dd>/ block_shape[0],
|
|
block_shape[0],
|
|
...,
|
|
padded_shape[M] / block_shape[M-1],
|
|
block_shape[M-1]] +
|
|
remaining_shape</dd></dl><ol><li>Permute dimensions of <code>reshaped_padded</code> to produce
|
|
<code>permuted_reshaped_padded</code> of shape:</li></ol><p>block_shape +
|
|
[batch] +
|
|
[padded_shape[1] / block_shape[0],
|
|
...,
|
|
padded_shape[M] / block_shape[M-1]] +
|
|
remaining_shape</p><ol><li>Reshape <code>permuted_reshaped_padded</code> to flatten <code>block_shape</code> into the batch
|
|
dimension, producing an output tensor of shape:</li></ol><dl><dt>batch * prod(block_shape)</dt><dd>+</dd><dt>padded_shape[1</dt><dd>/ block_shape[0],
|
|
...,
|
|
padded_shape[M] / block_shape[M-1]] +
|
|
remaining_shape</dd></dl><p>Some examples:</p><ol><li>For the following input of shape `[1, 2, 2, 1]`, `block_shape = [2, 2]`, and
|
|
`paddings = [[0, 0], [0, 0]]`:</li></ol><p>```prettyprint
|
|
x = [[[[1], [2]], [[3], [4]]]]
|
|
```</p><p>The output tensor has shape `[4, 1, 1, 1]` and value:</p><p>```prettyprint
|
|
[[[[1]]], [[[2]]], [[[3]]], [[[4]]]]
|
|
```</p><ol><li>For the following input of shape `[1, 2, 2, 3]`, `block_shape = [2, 2]`, and
|
|
`paddings = [[0, 0], [0, 0]]`:</li></ol><p>```prettyprint
|
|
x = [[[[1, 2, 3], [4, 5, 6]],
|
|
[[7, 8, 9], [10, 11, 12]]]]
|
|
```</p><p>The output tensor has shape `[4, 1, 1, 3]` and value:</p><p>```prettyprint
|
|
[[[1, 2, 3]], [[4, 5, 6]], [[7, 8, 9]], [[10, 11, 12]]]
|
|
```</p><ol><li>For the following input of shape `[1, 4, 4, 1]`, `block_shape = [2, 2]`, and
|
|
`paddings = [[0, 0], [0, 0]]`:</li></ol><p>```prettyprint
|
|
x = [[[[1], [2], [3], [4]],
|
|
[[5], [6], [7], [8]],
|
|
[[9], [10], [11], [12]],
|
|
[[13], [14], [15], [16]]]]
|
|
```</p><p>The output tensor has shape `[4, 2, 2, 1]` and value:</p><p>```prettyprint
|
|
x = [[[[1], [3]], [[5], [7]]],
|
|
[[[2], [4]], [[10], [12]]],
|
|
[[[5], [7]], [[13], [15]]],
|
|
[[[6], [8]], [[14], [16]]]]
|
|
```</p><ol><li>For the following input of shape `[2, 2, 4, 1]`, block_shape = `[2, 2]`, and
|
|
paddings = `[[0, 0], [2, 0]]`:</li></ol><p>```prettyprint
|
|
x = [[[[1], [2], [3], [4]],
|
|
[[5], [6], [7], [8]]],
|
|
[[[9], [10], [11], [12]],
|
|
[[13], [14], [15], [16]]]]
|
|
```</p><p>The output tensor has shape `[8, 1, 3, 1]` and value:</p><p>```prettyprint
|
|
x = [[[[0], [1], [3]]], [[[0], [9], [11]]],
|
|
[[[0], [2], [4]]], [[[0], [10], [12]]],
|
|
[[[0], [5], [7]]], [[[0], [13], [15]]],
|
|
[[[0], [6], [8]]], [[[0], [14], [16]]]]
|
|
```</p><p>Among others, this operation is useful for reducing atrous convolution into
|
|
regular convolution.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>SpaceToBatch for N-D tensors of type T.</p><p>This operation divides "spatial" dimensions `[1, ..., M]` of the input into a
|
|
grid of blocks of shape <code>block_shape</code>, and interleaves these blocks with the
|
|
"batch" dimension (0) such that in the output, the spatial dimensions
|
|
`[1, ..., M]` correspond to the position within the grid, and the batch
|
|
dimension combines both the position within a spatial block and the original
|
|
batch position. Prior to division into blocks, the spatial dimensions of the
|
|
input are optionally zero padded according to <code>paddings</code>. See below for a
|
|
precise description.</p></div></div><div class="top"><p class="src"><a name="v:spaceToBatchND-39-" class="def">spaceToBatchND'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tblock_shape, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tpaddings)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: N-D with shape `input_shape = [batch] + spatial_shape + remaining_shape`,
|
|
where spatial_shape has <code>M</code> dimensions.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tblock_shape</td><td class="doc"><p><strong>block_shape</strong>: 1-D with shape `[M]`, all values must be >= 1.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tpaddings</td><td class="doc"><p><strong>paddings</strong>: 2-D with shape `[M, 2]`, all values must be >= 0.
|
|
`paddings[i] = [pad_start, pad_end]` specifies the padding for input dimension
|
|
`i + 1`, which corresponds to spatial dimension <code>i</code>. It is required that
|
|
`block_shape[i]` divides `input_shape[i + 1] + pad_start + pad_end`.</p><p>This operation is equivalent to the following steps:</p><ol><li>Zero-pad the start and end of dimensions `[1, ..., M]` of the
|
|
input according to <code>paddings</code> to produce <code>padded</code> of shape <code>padded_shape</code>.</li><li>Reshape <code>padded</code> to <code>reshaped_padded</code> of shape:</li></ol><dl><dt>batch</dt><dd>+</dd><dt>padded_shape[1</dt><dd>/ block_shape[0],
|
|
block_shape[0],
|
|
...,
|
|
padded_shape[M] / block_shape[M-1],
|
|
block_shape[M-1]] +
|
|
remaining_shape</dd></dl><ol><li>Permute dimensions of <code>reshaped_padded</code> to produce
|
|
<code>permuted_reshaped_padded</code> of shape:</li></ol><p>block_shape +
|
|
[batch] +
|
|
[padded_shape[1] / block_shape[0],
|
|
...,
|
|
padded_shape[M] / block_shape[M-1]] +
|
|
remaining_shape</p><ol><li>Reshape <code>permuted_reshaped_padded</code> to flatten <code>block_shape</code> into the batch
|
|
dimension, producing an output tensor of shape:</li></ol><dl><dt>batch * prod(block_shape)</dt><dd>+</dd><dt>padded_shape[1</dt><dd>/ block_shape[0],
|
|
...,
|
|
padded_shape[M] / block_shape[M-1]] +
|
|
remaining_shape</dd></dl><p>Some examples:</p><ol><li>For the following input of shape `[1, 2, 2, 1]`, `block_shape = [2, 2]`, and
|
|
`paddings = [[0, 0], [0, 0]]`:</li></ol><p>```prettyprint
|
|
x = [[[[1], [2]], [[3], [4]]]]
|
|
```</p><p>The output tensor has shape `[4, 1, 1, 1]` and value:</p><p>```prettyprint
|
|
[[[[1]]], [[[2]]], [[[3]]], [[[4]]]]
|
|
```</p><ol><li>For the following input of shape `[1, 2, 2, 3]`, `block_shape = [2, 2]`, and
|
|
`paddings = [[0, 0], [0, 0]]`:</li></ol><p>```prettyprint
|
|
x = [[[[1, 2, 3], [4, 5, 6]],
|
|
[[7, 8, 9], [10, 11, 12]]]]
|
|
```</p><p>The output tensor has shape `[4, 1, 1, 3]` and value:</p><p>```prettyprint
|
|
[[[1, 2, 3]], [[4, 5, 6]], [[7, 8, 9]], [[10, 11, 12]]]
|
|
```</p><ol><li>For the following input of shape `[1, 4, 4, 1]`, `block_shape = [2, 2]`, and
|
|
`paddings = [[0, 0], [0, 0]]`:</li></ol><p>```prettyprint
|
|
x = [[[[1], [2], [3], [4]],
|
|
[[5], [6], [7], [8]],
|
|
[[9], [10], [11], [12]],
|
|
[[13], [14], [15], [16]]]]
|
|
```</p><p>The output tensor has shape `[4, 2, 2, 1]` and value:</p><p>```prettyprint
|
|
x = [[[[1], [3]], [[5], [7]]],
|
|
[[[2], [4]], [[10], [12]]],
|
|
[[[5], [7]], [[13], [15]]],
|
|
[[[6], [8]], [[14], [16]]]]
|
|
```</p><ol><li>For the following input of shape `[2, 2, 4, 1]`, block_shape = `[2, 2]`, and
|
|
paddings = `[[0, 0], [2, 0]]`:</li></ol><p>```prettyprint
|
|
x = [[[[1], [2], [3], [4]],
|
|
[[5], [6], [7], [8]]],
|
|
[[[9], [10], [11], [12]],
|
|
[[13], [14], [15], [16]]]]
|
|
```</p><p>The output tensor has shape `[8, 1, 3, 1]` and value:</p><p>```prettyprint
|
|
x = [[[[0], [1], [3]]], [[[0], [9], [11]]],
|
|
[[[0], [2], [4]]], [[[0], [10], [12]]],
|
|
[[[0], [5], [7]]], [[[0], [13], [15]]],
|
|
[[[0], [6], [8]]], [[[0], [14], [16]]]]
|
|
```</p><p>Among others, this operation is useful for reducing atrous convolution into
|
|
regular convolution.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:spaceToDepth" class="def">spaceToDepth</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>block_size</strong>: The size of the spatial block.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>SpaceToDepth for tensors of type T.</p><p>Rearranges blocks of spatial data, into depth. More specifically,
|
|
this op outputs a copy of the input tensor where values from the <code>height</code>
|
|
and <code>width</code> dimensions are moved to the <code>depth</code> dimension.
|
|
The attr <code>block_size</code> indicates the input block size and how the data is moved.</p><ul><li>Non-overlapping blocks of size `block_size x block size` are rearranged
|
|
into depth at each location.</li><li>The depth of the output tensor is `input_depth * block_size * block_size`.</li><li>The input tensor's height and width must be divisible by block_size.</li></ul><p>That is, assuming the input is in the shape:
|
|
`[batch, height, width, depth]`,
|
|
the shape of the output will be:
|
|
`[batch, height<em>block_size, width</em>block_size, depth*block_size*block_size]`</p><p>This operation requires that the input tensor be of rank 4, and that
|
|
<code>block_size</code> be >=1 and a divisor of both the input <code>height</code> and <code>width</code>.</p><p>This operation is useful for resizing the activations between convolutions
|
|
(but keeping all data), e.g. instead of pooling. It is also useful for training
|
|
purely convolutional models.</p><p>For example, given this input of shape `[1, 2, 2, 1]`, and block_size of 2:</p><p>```prettyprint
|
|
x = [[[[1], [2]],
|
|
[[3], [4]]]]
|
|
```</p><p>This operation will output a tensor of shape `[1, 1, 1, 4]`:</p><p>```prettyprint
|
|
[[[[1, 2, 3, 4]]]]
|
|
```</p><p>Here, the input has a batch of 1 and each batch element has shape `[2, 2, 1]`,
|
|
the corresponding output will have a single element (i.e. width and height are
|
|
both 1) and will have a depth of 4 channels (1 * block_size * block_size).
|
|
The output element shape is `[1, 1, 4]`.</p><p>For an input tensor with larger depth, here of shape `[1, 2, 2, 3]`, e.g.</p><p>```prettyprint
|
|
x = [[[[1, 2, 3], [4, 5, 6]],
|
|
[[7, 8, 9], [10, 11, 12]]]]
|
|
```</p><p>This operation, for block_size of 2, will return the following tensor of shape
|
|
`[1, 1, 1, 12]`</p><p>```prettyprint
|
|
[[[[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]]]]
|
|
```</p><p>Similarly, for the following input of shape `[1 4 4 1]`, and a block size of 2:</p><p>```prettyprint
|
|
x = [[[[1], [2], [5], [6]],
|
|
[[3], [4], [7], [8]],
|
|
[[9], [10], [13], [14]],
|
|
[[11], [12], [15], [16]]]]
|
|
```</p><p>the operator will return the following tensor of shape `[1 2 2 4]`:</p><p>```prettyprint
|
|
x = [[[[1, 2, 3, 4],
|
|
[5, 6, 7, 8]],
|
|
[[9, 10, 11, 12],
|
|
[13, 14, 15, 16]]]]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:spaceToDepth-39-" class="def">spaceToDepth'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>block_size</strong>: The size of the spatial block.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseAccumulatorApplyGradient" class="def">sparseAccumulatorApplyGradient</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>has_known_shape</strong>: Boolean indicating whether gradient_shape is unknown, in which
|
|
case the input is ignored during validation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a accumulator.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>local_step</strong>: The local_step value at which the sparse gradient was computed.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>gradient_indices</strong>: Indices of the sparse gradient to be accumulated. Must be a
|
|
vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 dtype</td><td class="doc"><p><strong>gradient_values</strong>: Values are the non-zero slices of the gradient, and must have
|
|
the same first dimension as indices, i.e., the nnz represented by indices and
|
|
values must be consistent.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>gradient_shape</strong>: Shape of the sparse gradient to be accumulated.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Applies a sparse gradient to a given accumulator. Does not add if local_step is</p><p>lesser than the accumulator's global_step.</p></div></div><div class="top"><p class="src"><a name="v:sparseAccumulatorApplyGradient-39-" class="def">sparseAccumulatorApplyGradient'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>has_known_shape</strong>: Boolean indicating whether gradient_shape is unknown, in which
|
|
case the input is ignored during validation.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a accumulator.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>local_step</strong>: The local_step value at which the sparse gradient was computed.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>gradient_indices</strong>: Indices of the sparse gradient to be accumulated. Must be a
|
|
vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 dtype</td><td class="doc"><p><strong>gradient_values</strong>: Values are the non-zero slices of the gradient, and must have
|
|
the same first dimension as indices, i.e., the nnz represented by indices and
|
|
values must be consistent.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>gradient_shape</strong>: Shape of the sparse gradient to be accumulated.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseAccumulatorTakeGradient" class="def">sparseAccumulatorTakeGradient</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a SparseConditionalAccumulator.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>num_required</strong>: Number of gradients required before we return an aggregate.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>indices</strong>, <strong>values</strong>, <strong>shape</strong>)</p><ul><li><strong>indices</strong>: Indices of the average of the accumulated sparse gradients.</li><li><strong>values</strong>: Values of the average of the accumulated sparse gradients.</li><li><strong>shape</strong>: Shape of the average of the accumulated sparse gradients.</li></ul></td></tr></table></div><div class="doc"><p>Extracts the average sparse gradient in the given SparseConditionalAccumulator,</p><p>provided that sufficient (i.e., more than num_required) gradients have been
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accumulated. The op will blocks until sufficient gradients have been
|
|
accumulated. If the accumulator has already aggregated more than num_required
|
|
gradients, it will return its average of the accumulated gradients.
|
|
Also automatically increments the recorded global_step in the accumulator by 1,
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|
and resets the aggregate to 0.</p></div></div><div class="top"><p class="src"><a name="v:sparseAccumulatorTakeGradient-39-" class="def">sparseAccumulatorTakeGradient'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a SparseConditionalAccumulator.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>num_required</strong>: Number of gradients required before we return an aggregate.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>indices</strong>, <strong>values</strong>, <strong>shape</strong>)</p><ul><li><strong>indices</strong>: Indices of the average of the accumulated sparse gradients.</li><li><strong>values</strong>: Values of the average of the accumulated sparse gradients.</li><li><strong>shape</strong>: Shape of the average of the accumulated sparse gradients.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseAdd" class="def">sparseAdd</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` treal)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>a_indices</strong>: 2-D. The <code>indices</code> of the first <code>SparseTensor</code>, size `[nnz, ndims]` Matrix.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>a_values</strong>: 1-D. The <code>values</code> of the first <code>SparseTensor</code>, size `[nnz]` Vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>a_shape</strong>: 1-D. The <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> of the first <code>SparseTensor</code>, size `[ndims]` Vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>b_indices</strong>: 2-D. The <code>indices</code> of the second <code>SparseTensor</code>, size `[nnz, ndims]` Matrix.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>b_values</strong>: 1-D. The <code>values</code> of the second <code>SparseTensor</code>, size `[nnz]` Vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>b_shape</strong>: 1-D. The <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> of the second <code>SparseTensor</code>, size `[ndims]` Vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 treal</td><td class="doc"><p><strong>thresh</strong>: 0-D. The magnitude threshold that determines if an output value/index
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|
pair takes space.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>sum_indices</strong>, <strong>sum_values</strong>, <strong>sum_shape</strong>)</p><ul><li><strong>sum_indices</strong></li><li><strong>sum_values</strong></li><li><strong>sum_shape</strong></li></ul></td></tr></table></div><div class="doc"><p>Adds two <code>SparseTensor</code> objects to produce another <code>SparseTensor</code>.</p><p>The input <code>SparseTensor</code> objects' indices are assumed ordered in standard
|
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lexicographic order. If this is not the case, before this step run
|
|
<code>SparseReorder</code> to restore index ordering.</p><p>By default, if two values sum to zero at some index, the output <code>SparseTensor</code>
|
|
would still include that particular location in its index, storing a zero in the
|
|
corresponding value slot. To override this, callers can specify <code>thresh</code>,
|
|
indicating that if the sum has a magnitude strictly smaller than <code>thresh</code>, its
|
|
corresponding value and index would then not be included. In particular,
|
|
`thresh == 0` (default) means everything is kept and actual thresholding happens
|
|
only for a positive value.</p><p>In the following shapes, <code>nnz</code> is the count after taking <code>thresh</code> into account.</p></div></div><div class="top"><p class="src"><a name="v:sparseAdd-39-" class="def">sparseAdd'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` treal)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>a_indices</strong>: 2-D. The <code>indices</code> of the first <code>SparseTensor</code>, size `[nnz, ndims]` Matrix.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>a_values</strong>: 1-D. The <code>values</code> of the first <code>SparseTensor</code>, size `[nnz]` Vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>a_shape</strong>: 1-D. The <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> of the first <code>SparseTensor</code>, size `[ndims]` Vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>b_indices</strong>: 2-D. The <code>indices</code> of the second <code>SparseTensor</code>, size `[nnz, ndims]` Matrix.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>b_values</strong>: 1-D. The <code>values</code> of the second <code>SparseTensor</code>, size `[nnz]` Vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>b_shape</strong>: 1-D. The <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> of the second <code>SparseTensor</code>, size `[ndims]` Vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 treal</td><td class="doc"><p><strong>thresh</strong>: 0-D. The magnitude threshold that determines if an output value/index
|
|
pair takes space.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>sum_indices</strong>, <strong>sum_values</strong>, <strong>sum_shape</strong>)</p><ul><li><strong>sum_indices</strong></li><li><strong>sum_values</strong></li><li><strong>sum_shape</strong></li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseAddGrad" class="def">sparseAddGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>backprop_val_grad</strong>: 1-D with shape `[nnz(sum)]`. The gradient with respect to
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the non-empty values of the sum.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>a_indices</strong>: 2-D. The <code>indices</code> of the <code>SparseTensor</code> A, size `[nnz(A), ndims]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>b_indices</strong>: 2-D. The <code>indices</code> of the <code>SparseTensor</code> B, size `[nnz(B), ndims]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sum_indices</strong>: 2-D. The <code>indices</code> of the sum <code>SparseTensor</code>, size
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`[nnz(sum), ndims]`.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>a_val_grad</strong>, <strong>b_val_grad</strong>)</p><ul><li><strong>a_val_grad</strong>: 1-D with shape `[nnz(A)]`. The gradient with respect to the
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non-empty values of A.</li><li><strong>b_val_grad</strong>: 1-D with shape `[nnz(B)]`. The gradient with respect to the
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non-empty values of B.</li></ul></td></tr></table></div><div class="doc"><p>The gradient operator for the SparseAdd op.</p><p>The SparseAdd op calculates A + B, where A, B, and the sum are all represented
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as <code>SparseTensor</code> objects. This op takes in the upstream gradient w.r.t.
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non-empty values of the sum, and outputs the gradients w.r.t. the non-empty
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values of A and B.</p></div></div><div class="top"><p class="src"><a name="v:sparseAddGrad-39-" class="def">sparseAddGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>backprop_val_grad</strong>: 1-D with shape `[nnz(sum)]`. The gradient with respect to
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the non-empty values of the sum.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>a_indices</strong>: 2-D. The <code>indices</code> of the <code>SparseTensor</code> A, size `[nnz(A), ndims]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>b_indices</strong>: 2-D. The <code>indices</code> of the <code>SparseTensor</code> B, size `[nnz(B), ndims]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sum_indices</strong>: 2-D. The <code>indices</code> of the sum <code>SparseTensor</code>, size
|
|
`[nnz(sum), ndims]`.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>a_val_grad</strong>, <strong>b_val_grad</strong>)</p><ul><li><strong>a_val_grad</strong>: 1-D with shape `[nnz(A)]`. The gradient with respect to the
|
|
non-empty values of A.</li><li><strong>b_val_grad</strong>: 1-D with shape `[nnz(B)]`. The gradient with respect to the
|
|
non-empty values of B.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseApplyAdadelta" class="def">sparseApplyAdadelta</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum_update</strong>: : Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>rho</strong>: Decay factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>epsilon</strong>: Constant factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>var: Should be from a Variable().</p></div></div><div class="top"><p class="src"><a name="v:sparseApplyAdadelta-39-" class="def">sparseApplyAdadelta'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum_update</strong>: : Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>rho</strong>: Decay factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>epsilon</strong>: Constant factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseApplyAdagrad" class="def">sparseApplyAdagrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Update relevant entries in '*var' and '*accum' according to the adagrad scheme.</p><p>That is for rows we have grad for, we update var and accum as follows:
|
|
accum += grad * grad
|
|
var -= lr * grad * (1 / sqrt(accum))</p></div></div><div class="top"><p class="src"><a name="v:sparseApplyAdagrad-39-" class="def">sparseApplyAdagrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseApplyAdagradDA" class="def">sparseApplyAdagradDA</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>gradient_accumulator</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>gradient_squared_accumulator</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>global_step</strong>: Training step number. Must be a scalar.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Update entries in '*var' and '*accum' according to the proximal adagrad scheme.</p></div></div><div class="top"><p class="src"><a name="v:sparseApplyAdagradDA-39-" class="def">sparseApplyAdagradDA'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>gradient_accumulator</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>gradient_squared_accumulator</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>global_step</strong>: Training step number. Must be a scalar.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseApplyCenteredRMSProp" class="def">sparseApplyCenteredRMSProp</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>mg</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ms</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>mom</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>rho</strong>: Decay rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>momentum</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var, ms and mom.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Update '*var' according to the centered RMSProp algorithm.</p><p>The centered RMSProp algorithm uses an estimate of the centered second moment
|
|
(i.e., the variance) for normalization, as opposed to regular RMSProp, which
|
|
uses the (uncentered) second moment. This often helps with training, but is
|
|
slightly more expensive in terms of computation and memory.</p><p>Note that in dense implementation of this algorithm, mg, ms, and mom will
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|
update even if the grad is zero, but in this sparse implementation, mg, ms,
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|
and mom will not update in iterations during which the grad is zero.</p><p>mean_square = decay * mean_square + (1-decay) * gradient ** 2
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|
mean_grad = decay * mean_grad + (1-decay) * gradient
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|
Delta = learning_rate * gradient / sqrt(mean_square + epsilon - mean_grad ** 2)</p><p>ms <- rho * ms_{t-1} + (1-rho) * grad * grad
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|
mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon)
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|
var <- var - mom</p></div></div><div class="top"><p class="src"><a name="v:sparseApplyCenteredRMSProp-39-" class="def">sparseApplyCenteredRMSProp'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>mg</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ms</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>mom</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>rho</strong>: Decay rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>momentum</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'10 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var, ms and mom.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseApplyFtrl" class="def">sparseApplyFtrl</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>linear</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t</td><td class="doc"><p><strong>lr_power</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Update relevant entries in '*var' according to the Ftrl-proximal scheme.</p><p>That is for rows we have grad for, we update var, accum and linear as follows:
|
|
accum_new = accum + grad * grad
|
|
linear += grad + (accum_new^(-lr_power) - accum^(-lr_power)) / lr * var
|
|
quadratic = 1.0 / (accum_new^(lr_power) * lr) + 2 * l2
|
|
var = (sign(linear) * l1 - linear) / quadratic if |linear| > l1 else 0.0
|
|
accum = accum_new</p></div></div><div class="top"><p class="src"><a name="v:sparseApplyFtrl-39-" class="def">sparseApplyFtrl'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>linear</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 t</td><td class="doc"><p><strong>lr_power</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseApplyMomentum" class="def">sparseApplyMomentum</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>momentum</strong>: Momentum. Must be a scalar.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Update relevant entries in '*var' and '*accum' according to the momentum scheme.</p><p>Set use_nesterov = True if you want to use Nesterov momentum.</p><p>That is for rows we have grad for, we update var and accum as follows:</p><p>accum = accum * momentum + grad
|
|
var -= lr * accum</p></div></div><div class="top"><p class="src"><a name="v:sparseApplyMomentum-39-" class="def">sparseApplyMomentum'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>momentum</strong>: Momentum. Must be a scalar.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseApplyProximalAdagrad" class="def">sparseApplyProximalAdagrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Sparse update entries in '*var' and '*accum' according to FOBOS algorithm.</p><p>That is for rows we have grad for, we update var and accum as follows:
|
|
accum += grad * grad
|
|
prox_v = var
|
|
prox_v -= lr * grad * (1 / sqrt(accum))
|
|
var = sign(prox_v)/(1+lr*l2) * max{|prox_v|-lr*l1,0}</p></div></div><div class="top"><p class="src"><a name="v:sparseApplyProximalAdagrad-39-" class="def">sparseApplyProximalAdagrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>accum</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>lr</strong>: Learning rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseApplyProximalGradientDescent" class="def">sparseApplyProximalGradientDescent</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>alpha</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Sparse update '*var' as FOBOS algorithm with fixed learning rate.</p><p>That is for rows we have grad for, we update var as follows:
|
|
prox_v = var - alpha * grad
|
|
var = sign(prox_v)/(1+alpha*l2) * max{|prox_v|-alpha*l1,0}</p></div></div><div class="top"><p class="src"><a name="v:sparseApplyProximalGradientDescent-39-" class="def">sparseApplyProximalGradientDescent'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>alpha</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>l1</strong>: L1 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>l2</strong>: L2 regularization. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var and accum.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseApplyRMSProp" class="def">sparseApplyRMSProp</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ms</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>mom</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>rho</strong>: Decay rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>momentum</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var, ms and mom.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div><div class="doc"><p>Update '*var' according to the RMSProp algorithm.</p><p>Note that in dense implementation of this algorithm, ms and mom will
|
|
update even if the grad is zero, but in this sparse implementation, ms
|
|
and mom will not update in iterations during which the grad is zero.</p><p>mean_square = decay * mean_square + (1-decay) * gradient ** 2
|
|
Delta = learning_rate * gradient / sqrt(mean_square + epsilon)</p><p>ms <- rho * ms_{t-1} + (1-rho) * grad * grad
|
|
mom <- momentum * mom_{t-1} + lr * grad / sqrt(ms + epsilon)
|
|
var <- var - mom</p></div></div><div class="top"><p class="src"><a name="v:sparseApplyRMSProp-39-" class="def">sparseApplyRMSProp'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>var</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ms</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>mom</strong>: Should be from a Variable().</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>lr</strong>: Scaling factor. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>rho</strong>: Decay rate. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 t</td><td class="doc"><p><strong>momentum</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'7 t</td><td class="doc"><p><strong>epsilon</strong>: Ridge term. Must be a scalar.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'8 t</td><td class="doc"><p><strong>grad</strong>: The gradient.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'9 tindices</td><td class="doc"><p><strong>indices</strong>: A vector of indices into the first dimension of var, ms and mom.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>out</strong>: Same as "var".</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseConcat" class="def">sparseConcat</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>concat_dim</strong>: Dimension to concatenate along. Must be in range [-rank, rank),
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where rank is the number of dimensions in each input <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]</td><td class="doc"><p><strong>indices</strong>: 2-D. Indices of each input <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t]</td><td class="doc"><p><strong>values</strong>: 1-D. Non-empty values of each <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]</td><td class="doc"><p><strong>shapes</strong>: 1-D. Shapes of each <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>output_indices</strong>, <strong>output_values</strong>, <strong>output_shape</strong>)</p><ul><li><strong>output_indices</strong>: 2-D. Indices of the concatenated <code>SparseTensor</code>.</li><li><strong>output_values</strong>: 1-D. Non-empty values of the concatenated <code>SparseTensor</code>.</li><li><strong>output_shape</strong>: 1-D. Shape of the concatenated <code>SparseTensor</code>.</li></ul></td></tr></table></div><div class="doc"><p>Concatenates a list of <code>SparseTensor</code> along the specified dimension.</p><p>Concatenation is with respect to the dense versions of these sparse tensors.
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It is assumed that each input is a <code>SparseTensor</code> whose elements are ordered
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along increasing dimension number.</p><p>All inputs' shapes must match, except for the concat dimension. The
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<code>indices</code>, <code>values</code>, and <code>shapes</code> lists must have the same length.</p><p>The output shape is identical to the inputs', except along the concat
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dimension, where it is the sum of the inputs' sizes along that dimension.</p><p>The output elements will be resorted to preserve the sort order along
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increasing dimension number.</p><p>This op runs in `O(M log M)` time, where <code>M</code> is the total number of non-empty
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values across all inputs. This is due to the need for an internal sort in
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order to concatenate efficiently across an arbitrary dimension.</p><p>For example, if `concat_dim = 1` and the inputs are</p><p>sp_inputs[0]: shape = [2, 3]
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[0, 2]: "a"
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[1, 0]: "b"
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[1, 1]: "c"</p><p>sp_inputs[1]: shape = [2, 4]
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[0, 1]: "d"
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[0, 2]: "e"</p><p>then the output will be</p><p>shape = [2, 7]
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[0, 2]: "a"
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[0, 4]: "d"
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[0, 5]: "e"
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[1, 0]: "b"
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[1, 1]: "c"</p><p>Graphically this is equivalent to doing</p><dl><dt> a</dt><dd>concat [ d e ] = [ a d e ]</dd><dt>b c </dt><dd>[ ] [b c ]</dd></dl></div></div><div class="top"><p class="src"><a name="v:sparseConcat-39-" class="def">sparseConcat'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>concat_dim</strong>: Dimension to concatenate along. Must be in range [-rank, rank),
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where rank is the number of dimensions in each input <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]</td><td class="doc"><p><strong>indices</strong>: 2-D. Indices of each input <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t]</td><td class="doc"><p><strong>values</strong>: 1-D. Non-empty values of each <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]</td><td class="doc"><p><strong>shapes</strong>: 1-D. Shapes of each <code>SparseTensor</code>.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>output_indices</strong>, <strong>output_values</strong>, <strong>output_shape</strong>)</p><ul><li><strong>output_indices</strong>: 2-D. Indices of the concatenated <code>SparseTensor</code>.</li><li><strong>output_values</strong>: 1-D. Non-empty values of the concatenated <code>SparseTensor</code>.</li><li><strong>output_shape</strong>: 1-D. Shape of the concatenated <code>SparseTensor</code>.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseConditionalAccumulator" class="def">sparseConditionalAccumulator</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>dtype</strong>: The type of the value being accumulated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: The shape of the values.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong>: The handle to the accumulator.</p></td></tr></table></div><div class="doc"><p>A conditional accumulator for aggregating sparse gradients. The accumulator</p><p>accepts gradients marked with local_step greater or equal to the most recent
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global_step known to the accumulator. The average can be extracted from the
|
|
accumulator, provided sufficient gradients have been accumulated. Extracting the
|
|
average automatically resets the aggregate to 0, and increments the global_step
|
|
recorded by the accumulator.</p></div></div><div class="top"><p class="src"><a name="v:sparseConditionalAccumulator-39-" class="def">sparseConditionalAccumulator'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>dtype</strong>: The type of the value being accumulated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: The shape of the values.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong>: The handle to the accumulator.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseDenseCwiseAdd" class="def">sparseDenseCwiseAdd</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sp_indices</strong>: 2-D. `N x R` matrix with the indices of non-empty values in a
|
|
SparseTensor, possibly not in canonical ordering.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>sp_values</strong>: 1-D. <code>N</code> non-empty values corresponding to <code>sp_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sp_shape</strong>: 1-D. Shape of the input SparseTensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>dense</strong>: <code>R</code>-D. The dense Tensor operand.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 1-D. The <code>N</code> values that are operated on.</p></td></tr></table></div><div class="doc"><p>Adds up a SparseTensor and a dense Tensor, using these special rules:</p><ol><li>Broadcasts the dense side to have the same shape as the sparse side, if
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eligible;</li><li>Then, only the dense values pointed to by the indices of the SparseTensor
|
|
participate in the cwise addition.</li></ol><p>By these rules, the result is a logical SparseTensor with exactly the same
|
|
indices and shape, but possibly with different non-zero values. The output of
|
|
this Op is the resultant non-zero values.</p></div></div><div class="top"><p class="src"><a name="v:sparseDenseCwiseAdd-39-" class="def">sparseDenseCwiseAdd'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sp_indices</strong>: 2-D. `N x R` matrix with the indices of non-empty values in a
|
|
SparseTensor, possibly not in canonical ordering.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>sp_values</strong>: 1-D. <code>N</code> non-empty values corresponding to <code>sp_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sp_shape</strong>: 1-D. Shape of the input SparseTensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>dense</strong>: <code>R</code>-D. The dense Tensor operand.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 1-D. The <code>N</code> values that are operated on.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseDenseCwiseDiv" class="def">sparseDenseCwiseDiv</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sp_indices</strong>: 2-D. `N x R` matrix with the indices of non-empty values in a
|
|
SparseTensor, possibly not in canonical ordering.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>sp_values</strong>: 1-D. <code>N</code> non-empty values corresponding to <code>sp_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sp_shape</strong>: 1-D. Shape of the input SparseTensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>dense</strong>: <code>R</code>-D. The dense Tensor operand.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 1-D. The <code>N</code> values that are operated on.</p></td></tr></table></div><div class="doc"><p>Component-wise divides a SparseTensor by a dense Tensor.</p><ul><li>Limitation*: this Op only broadcasts the dense side to the sparse side, but not
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|
the other direction.</li></ul></div></div><div class="top"><p class="src"><a name="v:sparseDenseCwiseDiv-39-" class="def">sparseDenseCwiseDiv'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sp_indices</strong>: 2-D. `N x R` matrix with the indices of non-empty values in a
|
|
SparseTensor, possibly not in canonical ordering.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>sp_values</strong>: 1-D. <code>N</code> non-empty values corresponding to <code>sp_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sp_shape</strong>: 1-D. Shape of the input SparseTensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>dense</strong>: <code>R</code>-D. The dense Tensor operand.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 1-D. The <code>N</code> values that are operated on.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseDenseCwiseMul" class="def">sparseDenseCwiseMul</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sp_indices</strong>: 2-D. `N x R` matrix with the indices of non-empty values in a
|
|
SparseTensor, possibly not in canonical ordering.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>sp_values</strong>: 1-D. <code>N</code> non-empty values corresponding to <code>sp_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sp_shape</strong>: 1-D. Shape of the input SparseTensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>dense</strong>: <code>R</code>-D. The dense Tensor operand.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 1-D. The <code>N</code> values that are operated on.</p></td></tr></table></div><div class="doc"><p>Component-wise multiplies a SparseTensor by a dense Tensor.</p><p>The output locations corresponding to the implicitly zero elements in the sparse
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tensor will be zero (i.e., will not take up storage space), regardless of the
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contents of the dense tensor (even if it's +/-INF and that INF*0 == NaN).</p><ul><li>Limitation*: this Op only broadcasts the dense side to the sparse side, but not
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the other direction.</li></ul></div></div><div class="top"><p class="src"><a name="v:sparseDenseCwiseMul-39-" class="def">sparseDenseCwiseMul'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sp_indices</strong>: 2-D. `N x R` matrix with the indices of non-empty values in a
|
|
SparseTensor, possibly not in canonical ordering.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>sp_values</strong>: 1-D. <code>N</code> non-empty values corresponding to <code>sp_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sp_shape</strong>: 1-D. Shape of the input SparseTensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>dense</strong>: <code>R</code>-D. The dense Tensor operand.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 1-D. The <code>N</code> values that are operated on.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseMatMul" class="def">sparseMatMul</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` ta, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tb)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 ta</td><td class="doc"><p><strong>a</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tb</td><td class="doc"><p><strong>b</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>product</strong></p></td></tr></table></div><div class="doc"><p>Multiply matrix "a" by matrix "b".</p><p>The inputs must be two-dimensional matrices and the inner dimension of "a" must
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match the outer dimension of "b". This op is optimized for the case where at
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least one of "a" or "b" is sparse. The breakeven for using this versus a dense
|
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matrix multiply on one platform was 30% zero values in the sparse matrix.</p></div></div><div class="top"><p class="src"><a name="v:sparseMatMul-39-" class="def">sparseMatMul'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` ta, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` tb)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 ta</td><td class="doc"><p><strong>a</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tb</td><td class="doc"><p><strong>b</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>product</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseReduceSum" class="def">sparseReduceSum</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>input_indices</strong>: 2-D. `N x R` matrix with the indices of non-empty values in a
|
|
SparseTensor, possibly not in canonical ordering.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>input_values</strong>: 1-D. <code>N</code> non-empty values corresponding to <code>input_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>input_shape</strong>: 1-D. Shape of the input SparseTensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>reduction_axes</strong>: 1-D. Length-<code>K</code> vector containing the reduction axes.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: `R-K`-D. The reduced Tensor.</p></td></tr></table></div><div class="doc"><p>Computes the sum of elements across dimensions of a SparseTensor.</p><p>This Op takes a SparseTensor and is the sparse counterpart to
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`tf.reduce_sum()`. In particular, this Op also returns a dense <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>
|
|
instead of a sparse one.</p><p>Reduces <code>sp_input</code> along the dimensions given in <code>reduction_axes</code>. Unless
|
|
<code>keep_dims</code> is true, the rank of the tensor is reduced by 1 for each entry in
|
|
<code>reduction_axes</code>. If <code>keep_dims</code> is true, the reduced dimensions are retained
|
|
with length 1.</p><p>If <code>reduction_axes</code> has no entries, all dimensions are reduced, and a tensor
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|
with a single element is returned. Additionally, the axes can be negative,
|
|
which are interpreted according to the indexing rules in Python.</p></div></div><div class="top"><p class="src"><a name="v:sparseReduceSum-39-" class="def">sparseReduceSum'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>input_indices</strong>: 2-D. `N x R` matrix with the indices of non-empty values in a
|
|
SparseTensor, possibly not in canonical ordering.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>input_values</strong>: 1-D. <code>N</code> non-empty values corresponding to <code>input_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>input_shape</strong>: 1-D. Shape of the input SparseTensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>reduction_axes</strong>: 1-D. Length-<code>K</code> vector containing the reduction axes.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: `R-K`-D. The reduced Tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseReduceSumSparse" class="def">sparseReduceSumSparse</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>input_indices</strong>: 2-D. `N x R` matrix with the indices of non-empty values in a
|
|
SparseTensor, possibly not in canonical ordering.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>input_values</strong>: 1-D. <code>N</code> non-empty values corresponding to <code>input_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>input_shape</strong>: 1-D. Shape of the input SparseTensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>reduction_axes</strong>: 1-D. Length-<code>K</code> vector containing the reduction axes.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>output_indices</strong>, <strong>output_values</strong>, <strong>output_shape</strong>)</p><ul><li><strong>output_indices</strong></li><li><strong>output_values</strong></li><li><strong>output_shape</strong></li></ul></td></tr></table></div><div class="doc"><p>Computes the sum of elements across dimensions of a SparseTensor.</p><p>This Op takes a SparseTensor and is the sparse counterpart to
|
|
`tf.reduce_sum()`. In contrast to SparseReduceSum, this Op returns a
|
|
SparseTensor.</p><p>Reduces <code>sp_input</code> along the dimensions given in <code>reduction_axes</code>. Unless
|
|
<code>keep_dims</code> is true, the rank of the tensor is reduced by 1 for each entry in
|
|
<code>reduction_axes</code>. If <code>keep_dims</code> is true, the reduced dimensions are retained
|
|
with length 1.</p><p>If <code>reduction_axes</code> has no entries, all dimensions are reduced, and a tensor
|
|
with a single element is returned. Additionally, the axes can be negative,
|
|
which are interpreted according to the indexing rules in Python.</p></div></div><div class="top"><p class="src"><a name="v:sparseReduceSumSparse-39-" class="def">sparseReduceSumSparse'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>input_indices</strong>: 2-D. `N x R` matrix with the indices of non-empty values in a
|
|
SparseTensor, possibly not in canonical ordering.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>input_values</strong>: 1-D. <code>N</code> non-empty values corresponding to <code>input_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>input_shape</strong>: 1-D. Shape of the input SparseTensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>reduction_axes</strong>: 1-D. Length-<code>K</code> vector containing the reduction axes.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>output_indices</strong>, <strong>output_values</strong>, <strong>output_shape</strong>)</p><ul><li><strong>output_indices</strong></li><li><strong>output_values</strong></li><li><strong>output_shape</strong></li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseReorder" class="def">sparseReorder</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>input_indices</strong>: 2-D. `N x R` matrix with the indices of non-empty values in a
|
|
SparseTensor, possibly not in canonical ordering.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>input_values</strong>: 1-D. <code>N</code> non-empty values corresponding to <code>input_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>input_shape</strong>: 1-D. Shape of the input SparseTensor.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>output_indices</strong>, <strong>output_values</strong>)</p><ul><li><strong>output_indices</strong>: 2-D. `N x R` matrix with the same indices as input_indices, but
|
|
in canonical row-major ordering.</li><li><strong>output_values</strong>: 1-D. <code>N</code> non-empty values corresponding to <code>output_indices</code>.</li></ul></td></tr></table></div><div class="doc"><p>Reorders a SparseTensor into the canonical, row-major ordering.</p><p>Note that by convention, all sparse ops preserve the canonical ordering along
|
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increasing dimension number. The only time ordering can be violated is during
|
|
manual manipulation of the indices and values vectors to add entries.</p><p>Reordering does not affect the shape of the SparseTensor.</p><p>If the tensor has rank <code>R</code> and <code>N</code> non-empty values, <code>input_indices</code> has
|
|
shape `[N, R]`, input_values has length <code>N</code>, and input_shape has length <code>R</code>.</p></div></div><div class="top"><p class="src"><a name="v:sparseReorder-39-" class="def">sparseReorder'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>input_indices</strong>: 2-D. `N x R` matrix with the indices of non-empty values in a
|
|
SparseTensor, possibly not in canonical ordering.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>input_values</strong>: 1-D. <code>N</code> non-empty values corresponding to <code>input_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>input_shape</strong>: 1-D. Shape of the input SparseTensor.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>output_indices</strong>, <strong>output_values</strong>)</p><ul><li><strong>output_indices</strong>: 2-D. `N x R` matrix with the same indices as input_indices, but
|
|
in canonical row-major ordering.</li><li><strong>output_values</strong>: 1-D. <code>N</code> non-empty values corresponding to <code>output_indices</code>.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseReshape" class="def">sparseReshape</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>input_indices</strong>: 2-D. `N x R_in` matrix with the indices of non-empty values in a
|
|
SparseTensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>input_shape</strong>: 1-D. <code>R_in</code> vector with the input SparseTensor's dense shape.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>new_shape</strong>: 1-D. <code>R_out</code> vector with the requested new dense shape.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>output_indices</strong>, <strong>output_shape</strong>)</p><ul><li><strong>output_indices</strong>: 2-D. `N x R_out` matrix with the updated indices of non-empty
|
|
values in the output SparseTensor.</li><li><strong>output_shape</strong>: 1-D. <code>R_out</code> vector with the full dense shape of the output
|
|
SparseTensor. This is the same as <code>new_shape</code> but with any -1 dimensions
|
|
filled in.</li></ul></td></tr></table></div><div class="doc"><p>Reshapes a SparseTensor to represent values in a new dense shape.</p><p>This operation has the same semantics as reshape on the represented dense
|
|
tensor. The <code>input_indices</code> are recomputed based on the requested <code>new_shape</code>.</p><p>If one component of <code>new_shape</code> is the special value -1, the size of that
|
|
dimension is computed so that the total dense size remains constant. At
|
|
most one component of <code>new_shape</code> can be -1. The number of dense elements
|
|
implied by <code>new_shape</code> must be the same as the number of dense elements
|
|
originally implied by <code>input_shape</code>.</p><p>Reshaping does not affect the order of values in the SparseTensor.</p><p>If the input tensor has rank <code>R_in</code> and <code>N</code> non-empty values, and <code>new_shape</code>
|
|
has length <code>R_out</code>, then <code>input_indices</code> has shape `[N, R_in]`,
|
|
<code>input_shape</code> has length <code>R_in</code>, <code>output_indices</code> has shape `[N, R_out]`, and
|
|
<code>output_shape</code> has length <code>R_out</code>.</p></div></div><div class="top"><p class="src"><a name="v:sparseReshape-39-" class="def">sparseReshape'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>input_indices</strong>: 2-D. `N x R_in` matrix with the indices of non-empty values in a
|
|
SparseTensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>input_shape</strong>: 1-D. <code>R_in</code> vector with the input SparseTensor's dense shape.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>new_shape</strong>: 1-D. <code>R_out</code> vector with the requested new dense shape.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>output_indices</strong>, <strong>output_shape</strong>)</p><ul><li><strong>output_indices</strong>: 2-D. `N x R_out` matrix with the updated indices of non-empty
|
|
values in the output SparseTensor.</li><li><strong>output_shape</strong>: 1-D. <code>R_out</code> vector with the full dense shape of the output
|
|
SparseTensor. This is the same as <code>new_shape</code> but with any -1 dimensions
|
|
filled in.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseSegmentMean" class="def">sparseSegmentMean</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>indices</strong>: A 1-D tensor. Has same rank as <code>segment_ids</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>segment_ids</strong>: A 1-D tensor. Values should be sorted and can be repeated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Has same shape as data, except for dimension 0 which
|
|
has size <code>k</code>, the number of segments.</p></td></tr></table></div><div class="doc"><p>Computes the mean along sparse segments of a tensor.</p><p>Read <a href="../../api_docs/python/math_ops.md#segmentation">the section on
|
|
Segmentation</a> for an explanation
|
|
of segments.</p><p>Like <code>SegmentMean</code>, but <code>segment_ids</code> can have rank less than `data`'s first
|
|
dimension, selecting a subset of dimension 0, specified by <code>indices</code>.</p></div></div><div class="top"><p class="src"><a name="v:sparseSegmentMean-39-" class="def">sparseSegmentMean'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>indices</strong>: A 1-D tensor. Has same rank as <code>segment_ids</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>segment_ids</strong>: A 1-D tensor. Values should be sorted and can be repeated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Has same shape as data, except for dimension 0 which
|
|
has size <code>k</code>, the number of segments.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseSegmentMeanGrad" class="def">sparseSegmentMeanGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>grad</strong>: gradient propagated to the SparseSegmentMean op.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>indices</strong>: indices passed to the corresponding SparseSegmentMean op.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>segment_ids</strong>: segment_ids passed to the corresponding SparseSegmentMean op.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>output_dim0</strong>: dimension 0 of "data" passed to SparseSegmentMean op.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Computes gradients for SparseSegmentMean.</p><p>Returns tensor "output" with same shape as grad, except for dimension 0 whose
|
|
value is output_dim0.</p></div></div><div class="top"><p class="src"><a name="v:sparseSegmentMeanGrad-39-" class="def">sparseSegmentMeanGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>grad</strong>: gradient propagated to the SparseSegmentMean op.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>indices</strong>: indices passed to the corresponding SparseSegmentMean op.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>segment_ids</strong>: segment_ids passed to the corresponding SparseSegmentMean op.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>output_dim0</strong>: dimension 0 of "data" passed to SparseSegmentMean op.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseSegmentSqrtN" class="def">sparseSegmentSqrtN</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>indices</strong>: A 1-D tensor. Has same rank as <code>segment_ids</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>segment_ids</strong>: A 1-D tensor. Values should be sorted and can be repeated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Has same shape as data, except for dimension 0 which
|
|
has size <code>k</code>, the number of segments.</p></td></tr></table></div><div class="doc"><p>Computes the sum along sparse segments of a tensor divided by the sqrt of N.</p><p>N is the size of the segment being reduced.</p><p>Read <a href="../../api_docs/python/math_ops.md#segmentation">the section on
|
|
Segmentation</a> for an explanation
|
|
of segments.</p></div></div><div class="top"><p class="src"><a name="v:sparseSegmentSqrtN-39-" class="def">sparseSegmentSqrtN'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>indices</strong>: A 1-D tensor. Has same rank as <code>segment_ids</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>segment_ids</strong>: A 1-D tensor. Values should be sorted and can be repeated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Has same shape as data, except for dimension 0 which
|
|
has size <code>k</code>, the number of segments.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseSegmentSqrtNGrad" class="def">sparseSegmentSqrtNGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>grad</strong>: gradient propagated to the SparseSegmentSqrtN op.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>indices</strong>: indices passed to the corresponding SparseSegmentSqrtN op.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>segment_ids</strong>: segment_ids passed to the corresponding SparseSegmentSqrtN op.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>output_dim0</strong>: dimension 0 of "data" passed to SparseSegmentSqrtN op.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Computes gradients for SparseSegmentSqrtN.</p><p>Returns tensor "output" with same shape as grad, except for dimension 0 whose
|
|
value is output_dim0.</p></div></div><div class="top"><p class="src"><a name="v:sparseSegmentSqrtNGrad-39-" class="def">sparseSegmentSqrtNGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>grad</strong>: gradient propagated to the SparseSegmentSqrtN op.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>indices</strong>: indices passed to the corresponding SparseSegmentSqrtN op.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>segment_ids</strong>: segment_ids passed to the corresponding SparseSegmentSqrtN op.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>output_dim0</strong>: dimension 0 of "data" passed to SparseSegmentSqrtN op.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseSegmentSum" class="def">sparseSegmentSum</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>indices</strong>: A 1-D tensor. Has same rank as <code>segment_ids</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>segment_ids</strong>: A 1-D tensor. Values should be sorted and can be repeated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Has same shape as data, except for dimension 0 which
|
|
has size <code>k</code>, the number of segments.</p></td></tr></table></div><div class="doc"><p>Computes the sum along sparse segments of a tensor.</p><p>Read <a href="../../api_docs/python/math_ops.md#segmentation">the section on
|
|
Segmentation</a> for an explanation
|
|
of segments.</p><p>Like <code>SegmentSum</code>, but <code>segment_ids</code> can have rank less than `data`'s first
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|
dimension, selecting a subset of dimension 0, specified by <code>indices</code>.</p><p>For example:</p><p>```prettyprint
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|
c = tf.constant([[1,2,3,4], [-1,-2,-3,-4], [5,6,7,8]])</p><p># Select two rows, one segment.
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|
tf.sparse_segment_sum(c, tf.constant([0, 1]), tf.constant([0, 0]))
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==> [[0 0 0 0]]</p><p># Select two rows, two segment.
|
|
tf.sparse_segment_sum(c, tf.constant([0, 1]), tf.constant([0, 1]))
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==> [[ 1 2 3 4]
|
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[-1 -2 -3 -4]]</p><p># Select all rows, two segments.
|
|
tf.sparse_segment_sum(c, tf.constant([0, 1, 2]), tf.constant([0, 0, 1]))
|
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==> [[0 0 0 0]
|
|
[5 6 7 8]]</p><p># Which is equivalent to:
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|
tf.segment_sum(c, tf.constant([0, 0, 1]))
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:sparseSegmentSum-39-" class="def">sparseSegmentSum'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>indices</strong>: A 1-D tensor. Has same rank as <code>segment_ids</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>segment_ids</strong>: A 1-D tensor. Values should be sorted and can be repeated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Has same shape as data, except for dimension 0 which
|
|
has size <code>k</code>, the number of segments.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseSoftmax" class="def">sparseSoftmax</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sp_indices</strong>: 2-D. `NNZ x R` matrix with the indices of non-empty values in a
|
|
SparseTensor, in canonical ordering.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>sp_values</strong>: 1-D. <code>NNZ</code> non-empty values corresponding to <code>sp_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sp_shape</strong>: 1-D. Shape of the input SparseTensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 1-D. The <code>NNZ</code> values for the result <code>SparseTensor</code>.</p></td></tr></table></div><div class="doc"><p>Applies softmax to a batched N-D <code>SparseTensor</code>.</p><p>The inputs represent an N-D SparseTensor with logical shape `[..., B, C]`
|
|
(where `N >= 2`), and with indices sorted in the canonical lexicographic order.</p><p>This op is equivalent to applying the normal `tf.nn.softmax()` to each innermost
|
|
logical submatrix with shape `[B, C]`, but with the catch that *the implicitly
|
|
zero elements do not participate*. Specifically, the algorithm is equivalent
|
|
to the following:</p><ol><li>Applies `tf.nn.softmax()` to a densified view of each innermost submatrix
|
|
with shape `[B, C]`, along the size-C dimension;</li><li>Masks out the original implicitly-zero locations;</li><li>Renormalizes the remaining elements.</li></ol><p>Hence, the <code>SparseTensor</code> result has exactly the same non-zero indices and
|
|
shape.</p></div></div><div class="top"><p class="src"><a name="v:sparseSoftmax-39-" class="def">sparseSoftmax'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sp_indices</strong>: 2-D. `NNZ x R` matrix with the indices of non-empty values in a
|
|
SparseTensor, in canonical ordering.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>sp_values</strong>: 1-D. <code>NNZ</code> non-empty values corresponding to <code>sp_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sp_shape</strong>: 1-D. Shape of the input SparseTensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: 1-D. The <code>NNZ</code> values for the result <code>SparseTensor</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseSoftmaxCrossEntropyWithLogits" class="def">sparseSoftmaxCrossEntropyWithLogits</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tlabels)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>features</strong>: batch_size x num_classes matrix</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tlabels</td><td class="doc"><p><strong>labels</strong>: batch_size vector with values in [0, num_classes).
|
|
This is the label for the given minibatch entry.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>loss</strong>, <strong>backprop</strong>)</p><ul><li><strong>loss</strong>: Per example loss (batch_size vector).</li><li><strong>backprop</strong>: backpropagated gradients (batch_size x num_classes matrix).</li></ul></td></tr></table></div><div class="doc"><p>Computes softmax cross entropy cost and gradients to backpropagate.</p><p>Unlike <code>SoftmaxCrossEntropyWithLogits</code>, this operation does not accept
|
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a matrix of label probabilities, but rather a single label per row
|
|
of features. This label is considered to have probability 1.0 for the
|
|
given row.</p><p>Inputs are the logits, not probabilities.</p></div></div><div class="top"><p class="src"><a name="v:sparseSoftmaxCrossEntropyWithLogits-39-" class="def">sparseSoftmaxCrossEntropyWithLogits'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tlabels)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>features</strong>: batch_size x num_classes matrix</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tlabels</td><td class="doc"><p><strong>labels</strong>: batch_size vector with values in [0, num_classes).
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This is the label for the given minibatch entry.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>loss</strong>, <strong>backprop</strong>)</p><ul><li><strong>loss</strong>: Per example loss (batch_size vector).</li><li><strong>backprop</strong>: backpropagated gradients (batch_size x num_classes matrix).</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseSparseMaximum" class="def">sparseSparseMaximum</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>a_indices</strong>: 2-D. `N x R` matrix with the indices of non-empty values in a
|
|
SparseTensor, in the canonical lexicographic ordering.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>a_values</strong>: 1-D. <code>N</code> non-empty values corresponding to <code>a_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>a_shape</strong>: 1-D. Shape of the input SparseTensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>b_indices</strong>: counterpart to <code>a_indices</code> for the other operand.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>b_values</strong>: counterpart to <code>a_values</code> for the other operand; must be of the same dtype.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>b_shape</strong>: counterpart to <code>a_shape</code> for the other operand; the two shapes must be equal.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>output_indices</strong>, <strong>output_values</strong>)</p><ul><li><strong>output_indices</strong>: 2-D. The indices of the output SparseTensor.</li><li><strong>output_values</strong>: 1-D. The values of the output SparseTensor.</li></ul></td></tr></table></div><div class="doc"><p>Returns the element-wise max of two SparseTensors.</p><p>Assumes the two SparseTensors have the same shape, i.e., no broadcasting.</p></div></div><div class="top"><p class="src"><a name="v:sparseSparseMaximum-39-" class="def">sparseSparseMaximum'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>a_indices</strong>: 2-D. `N x R` matrix with the indices of non-empty values in a
|
|
SparseTensor, in the canonical lexicographic ordering.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>a_values</strong>: 1-D. <code>N</code> non-empty values corresponding to <code>a_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>a_shape</strong>: 1-D. Shape of the input SparseTensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>b_indices</strong>: counterpart to <code>a_indices</code> for the other operand.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>b_values</strong>: counterpart to <code>a_values</code> for the other operand; must be of the same dtype.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>b_shape</strong>: counterpart to <code>a_shape</code> for the other operand; the two shapes must be equal.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>output_indices</strong>, <strong>output_values</strong>)</p><ul><li><strong>output_indices</strong>: 2-D. The indices of the output SparseTensor.</li><li><strong>output_values</strong>: 1-D. The values of the output SparseTensor.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseSparseMinimum" class="def">sparseSparseMinimum</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>a_indices</strong>: 2-D. `N x R` matrix with the indices of non-empty values in a
|
|
SparseTensor, in the canonical lexicographic ordering.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>a_values</strong>: 1-D. <code>N</code> non-empty values corresponding to <code>a_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>a_shape</strong>: 1-D. Shape of the input SparseTensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>b_indices</strong>: counterpart to <code>a_indices</code> for the other operand.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>b_values</strong>: counterpart to <code>a_values</code> for the other operand; must be of the same dtype.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>b_shape</strong>: counterpart to <code>a_shape</code> for the other operand; the two shapes must be equal.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>output_indices</strong>, <strong>output_values</strong>)</p><ul><li><strong>output_indices</strong>: 2-D. The indices of the output SparseTensor.</li><li><strong>output_values</strong>: 1-D. The values of the output SparseTensor.</li></ul></td></tr></table></div><div class="doc"><p>Returns the element-wise min of two SparseTensors.</p><p>Assumes the two SparseTensors have the same shape, i.e., no broadcasting.</p></div></div><div class="top"><p class="src"><a name="v:sparseSparseMinimum-39-" class="def">sparseSparseMinimum'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>a_indices</strong>: 2-D. `N x R` matrix with the indices of non-empty values in a
|
|
SparseTensor, in the canonical lexicographic ordering.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>a_values</strong>: 1-D. <code>N</code> non-empty values corresponding to <code>a_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>a_shape</strong>: 1-D. Shape of the input SparseTensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>b_indices</strong>: counterpart to <code>a_indices</code> for the other operand.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>b_values</strong>: counterpart to <code>a_values</code> for the other operand; must be of the same dtype.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>b_shape</strong>: counterpart to <code>a_shape</code> for the other operand; the two shapes must be equal.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>output_indices</strong>, <strong>output_values</strong>)</p><ul><li><strong>output_indices</strong>: 2-D. The indices of the output SparseTensor.</li><li><strong>output_values</strong>: 1-D. The values of the output SparseTensor.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseSplit" class="def">sparseSplit</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_split</strong>: The number of ways to split.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>split_dim</strong>: 0-D. The dimension along which to split. Must be in the range
|
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`[0, rank(shape))`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>indices</strong>: 2-D tensor represents the indices of the sparse tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>values</strong>: 1-D tensor represents the values of the sparse tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>shape</strong>: 1-D. tensor represents the shape of the sparse tensor.
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output indices: A list of 1-D tensors represents the indices of the output
|
|
sparse tensors.</p></td></tr><tr><td class="src">-> ([<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>])</td><td class="doc"><p>(<strong>output_indices</strong>, <strong>output_values</strong>, <strong>output_shape</strong>)</p><ul><li><strong>output_indices</strong></li><li><strong>output_values</strong>: A list of 1-D tensors represents the values of the output sparse
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|
tensors.</li><li><strong>output_shape</strong>: A list of 1-D tensors represents the shape of the output sparse
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|
tensors.</li></ul></td></tr></table></div><div class="doc"><p>Split a <code>SparseTensor</code> into <code>num_split</code> tensors along one dimension.</p><p>If the `shape[split_dim]` is not an integer multiple of <code>num_split</code>. Slices
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`[0 : shape[split_dim] % num_split]` gets one extra dimension.
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|
For example, if `split_dim = 1` and `num_split = 2` and the input is</p><p>input_tensor = shape = [2, 7]
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[ a d e ]
|
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[b c ]</p><p>Graphically the output tensors are:</p><p>output_tensor[0] = shape = [2, 4]
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[ a ]
|
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[b c ]</p><p>output_tensor[1] = shape = [2, 3]
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[ d e ]
|
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[ ]</p></div></div><div class="top"><p class="src"><a name="v:sparseSplit-39-" class="def">sparseSplit'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_split</strong>: The number of ways to split.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>split_dim</strong>: 0-D. The dimension along which to split. Must be in the range
|
|
`[0, rank(shape))`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>indices</strong>: 2-D tensor represents the indices of the sparse tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>values</strong>: 1-D tensor represents the values of the sparse tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>shape</strong>: 1-D. tensor represents the shape of the sparse tensor.
|
|
output indices: A list of 1-D tensors represents the indices of the output
|
|
sparse tensors.</p></td></tr><tr><td class="src">-> ([<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t], [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>])</td><td class="doc"><p>(<strong>output_indices</strong>, <strong>output_values</strong>, <strong>output_shape</strong>)</p><ul><li><strong>output_indices</strong></li><li><strong>output_values</strong>: A list of 1-D tensors represents the values of the output sparse
|
|
tensors.</li><li><strong>output_shape</strong>: A list of 1-D tensors represents the shape of the output sparse
|
|
tensors.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseTensorDenseAdd" class="def">sparseTensorDenseAdd</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tindices</td><td class="doc"><p><strong>a_indices</strong>: 2-D. The <code>indices</code> of the <code>SparseTensor</code>, with shape `[nnz, ndims]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>a_values</strong>: 1-D. The <code>values</code> of the <code>SparseTensor</code>, with shape `[nnz]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tindices</td><td class="doc"><p><strong>a_shape</strong>: 1-D. The <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> of the <code>SparseTensor</code>, with shape `[ndims]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>b</strong>: <code>ndims</code>-D Tensor. With shape <code>a_shape</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Adds up a <code>SparseTensor</code> and a dense <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, producing a dense <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>.</p><p>This Op does not require <code>a_indices</code> be sorted in standard lexicographic order.</p></div></div><div class="top"><p class="src"><a name="v:sparseTensorDenseAdd-39-" class="def">sparseTensorDenseAdd'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tindices</td><td class="doc"><p><strong>a_indices</strong>: 2-D. The <code>indices</code> of the <code>SparseTensor</code>, with shape `[nnz, ndims]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>a_values</strong>: 1-D. The <code>values</code> of the <code>SparseTensor</code>, with shape `[nnz]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 tindices</td><td class="doc"><p><strong>a_shape</strong>: 1-D. The <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> of the <code>SparseTensor</code>, with shape `[ndims]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>b</strong>: <code>ndims</code>-D Tensor. With shape <code>a_shape</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseTensorDenseMatMul" class="def">sparseTensorDenseMatMul</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>a_indices</strong>: 2-D. The <code>indices</code> of the <code>SparseTensor</code>, size `[nnz, 2]` Matrix.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>a_values</strong>: 1-D. The <code>values</code> of the <code>SparseTensor</code>, size `[nnz]` Vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>a_shape</strong>: 1-D. The <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> of the <code>SparseTensor</code>, size `[2]` Vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>b</strong>: 2-D. A dense Matrix.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>product</strong></p></td></tr></table></div><div class="doc"><p>Multiply SparseTensor (of rank 2) <a href="A.html">A</a> by dense matrix <a href="B.html">B</a>.</p><p>No validity checking is performed on the indices of A. However, the following
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input format is recommended for optimal behavior:</p><p>if adjoint_a == false:
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|
A should be sorted in lexicographically increasing order. Use SparseReorder
|
|
if you're not sure.
|
|
if adjoint_a == true:
|
|
A should be sorted in order of increasing dimension 1 (i.e., "column major"
|
|
order instead of "row major" order).</p></div></div><div class="top"><p class="src"><a name="v:sparseTensorDenseMatMul-39-" class="def">sparseTensorDenseMatMul'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>a_indices</strong>: 2-D. The <code>indices</code> of the <code>SparseTensor</code>, size `[nnz, 2]` Matrix.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>a_values</strong>: 1-D. The <code>values</code> of the <code>SparseTensor</code>, size `[nnz]` Vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>a_shape</strong>: 1-D. The <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> of the <code>SparseTensor</code>, size `[2]` Vector.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>b</strong>: 2-D. A dense Matrix.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>product</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseToDense" class="def">sparseToDense</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tindices</td><td class="doc"><p><strong>sparse_indices</strong>: 0-D, 1-D, or 2-D. `sparse_indices[i]` contains the complete
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index where `sparse_values[i]` will be placed.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>output_shape</strong>: 1-D. Shape of the dense output tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>sparse_values</strong>: 1-D. Values corresponding to each row of <code>sparse_indices</code>,
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|
or a scalar value to be used for all sparse indices.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>default_value</strong>: Scalar value to set for indices not specified in
|
|
<code>sparse_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>dense</strong>: Dense output tensor of shape <code>output_shape</code>.</p></td></tr></table></div><div class="doc"><p>Converts a sparse representation into a dense tensor.</p><p>Builds an array <code>dense</code> with shape <code>output_shape</code> such that</p><p>```prettyprint
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|
# If sparse_indices is scalar
|
|
dense[i] = (i == sparse_indices ? sparse_values : default_value)</p><p># If sparse_indices is a vector, then for each i
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|
dense[sparse_indices[i]] = sparse_values[i]</p><p># If sparse_indices is an n by d matrix, then for each i in [0, n)
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|
dense[sparse_indices[i][0], ..., sparse_indices[i][d-1]] = sparse_values[i]
|
|
```</p><p>All other values in <code>dense</code> are set to <code>default_value</code>. If <code>sparse_values</code> is a
|
|
scalar, all sparse indices are set to this single value.</p><p>Indices should be sorted in lexicographic order, and indices must not
|
|
contain any repeats. If <code>validate_indices</code> is true, these properties
|
|
are checked during execution.</p></div></div><div class="top"><p class="src"><a name="v:sparseToDense-39-" class="def">sparseToDense'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 tindices</td><td class="doc"><p><strong>sparse_indices</strong>: 0-D, 1-D, or 2-D. `sparse_indices[i]` contains the complete
|
|
index where `sparse_values[i]` will be placed.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>output_shape</strong>: 1-D. Shape of the dense output tensor.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>sparse_values</strong>: 1-D. Values corresponding to each row of <code>sparse_indices</code>,
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|
or a scalar value to be used for all sparse indices.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 t</td><td class="doc"><p><strong>default_value</strong>: Scalar value to set for indices not specified in
|
|
<code>sparse_indices</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>dense</strong>: Dense output tensor of shape <code>output_shape</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sparseToSparseSetOperation" class="def">sparseToSparseSetOperation</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>set1_indices</strong>: 2D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, indices of a <code>SparseTensor</code>. Must be in row-major
|
|
order.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>set1_values</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, values of a <code>SparseTensor</code>. Must be in row-major
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|
order.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>set1_shape</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, shape of a <code>SparseTensor</code>. `set1_shape[0...n-1]` must
|
|
be the same as `set2_shape[0...n-1]`, `set1_shape[n]` is the
|
|
max set size across `0...n-1` dimensions.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>set2_indices</strong>: 2D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, indices of a <code>SparseTensor</code>. Must be in row-major
|
|
order.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>set2_values</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, values of a <code>SparseTensor</code>. Must be in row-major
|
|
order.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>set2_shape</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, shape of a <code>SparseTensor</code>. `set2_shape[0...n-1]` must
|
|
be the same as `set1_shape[0...n-1]`, `set2_shape[n]` is the
|
|
max set size across `0...n-1` dimensions.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>result_indices</strong>, <strong>result_values</strong>, <strong>result_shape</strong>)</p><ul><li><strong>result_indices</strong>: 2D indices of a <code>SparseTensor</code>.</li><li><strong>result_values</strong>: 1D values of a <code>SparseTensor</code>.</li><li><strong>result_shape</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> shape of a <code>SparseTensor</code>. `result_shape[0...n-1]` is
|
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the same as the 1st `n-1` dimensions of <code>set1</code> and <code>set2</code>, `result_shape[n]`
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is the max result set size across all `0...n-1` dimensions.</li></ul></td></tr></table></div><div class="doc"><p>Applies set operation along last dimension of 2 <code>SparseTensor</code> inputs.</p><p>See SetOperationOp::SetOperationFromContext for values of <code>set_operation</code>.</p><p>If <code>validate_indices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code>, <code>SparseToSparseSetOperation</code> validates the
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order and range of <code>set1</code> and <code>set2</code> indices.</p><p>Input <code>set1</code> is a <code>SparseTensor</code> represented by <code>set1_indices</code>, <code>set1_values</code>,
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and <code>set1_shape</code>. For <code>set1</code> ranked <code>n</code>, 1st `n-1` dimensions must be the same
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|
as <code>set2</code>. Dimension <code>n</code> contains values in a set, duplicates are allowed but
|
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ignored.</p><p>Input <code>set2</code> is a <code>SparseTensor</code> represented by <code>set2_indices</code>, <code>set2_values</code>,
|
|
and <code>set2_shape</code>. For <code>set2</code> ranked <code>n</code>, 1st `n-1` dimensions must be the same
|
|
as <code>set1</code>. Dimension <code>n</code> contains values in a set, duplicates are allowed but
|
|
ignored.</p><p>If <code>validate_indices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code>, this op validates the order and range of <code>set1</code>
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and <code>set2</code> indices.</p><p>Output <code>result</code> is a <code>SparseTensor</code> represented by <code>result_indices</code>,
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<code>result_values</code>, and <code>result_shape</code>. For <code>set1</code> and <code>set2</code> ranked <code>n</code>, this
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|
has rank <code>n</code> and the same 1st `n-1` dimensions as <code>set1</code> and <code>set2</code>. The <code>nth</code>
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|
dimension contains the result of <code>set_operation</code> applied to the corresponding
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`[0...n-1]` dimension of <code>set</code>.</p></div></div><div class="top"><p class="src"><a name="v:sparseToSparseSetOperation-39-" class="def">sparseToSparseSetOperation'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>set1_indices</strong>: 2D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, indices of a <code>SparseTensor</code>. Must be in row-major
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order.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>set1_values</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, values of a <code>SparseTensor</code>. Must be in row-major
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order.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>set1_shape</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, shape of a <code>SparseTensor</code>. `set1_shape[0...n-1]` must
|
|
be the same as `set2_shape[0...n-1]`, `set1_shape[n]` is the
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|
max set size across `0...n-1` dimensions.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>set2_indices</strong>: 2D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, indices of a <code>SparseTensor</code>. Must be in row-major
|
|
order.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>set2_values</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, values of a <code>SparseTensor</code>. Must be in row-major
|
|
order.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'6 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>set2_shape</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, shape of a <code>SparseTensor</code>. `set2_shape[0...n-1]` must
|
|
be the same as `set1_shape[0...n-1]`, `set2_shape[n]` is the
|
|
max set size across `0...n-1` dimensions.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>result_indices</strong>, <strong>result_values</strong>, <strong>result_shape</strong>)</p><ul><li><strong>result_indices</strong>: 2D indices of a <code>SparseTensor</code>.</li><li><strong>result_values</strong>: 1D values of a <code>SparseTensor</code>.</li><li><strong>result_shape</strong>: 1D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> shape of a <code>SparseTensor</code>. `result_shape[0...n-1]` is
|
|
the same as the 1st `n-1` dimensions of <code>set1</code> and <code>set2</code>, `result_shape[n]`
|
|
is the max result set size across all `0...n-1` dimensions.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:split" class="def">split</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_split</strong>: The number of ways to split. Must evenly divide
|
|
`value.shape[split_dim]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>split_dim</strong>: 0-D. The dimension along which to split. Must be in the range
|
|
`[0, rank(value))`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>value</strong>: The tensor to split.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</td><td class="doc"><p><strong>output</strong>: They are identically shaped tensors, whose shape matches that of <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>
|
|
except along <code>split_dim</code>, where their sizes are
|
|
`values.shape[split_dim] / num_split`.</p></td></tr></table></div><div class="doc"><p>Splits a tensor into <code>num_split</code> tensors along one dimension.</p></div></div><div class="top"><p class="src"><a name="v:split-39-" class="def">split'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_split</strong>: The number of ways to split. Must evenly divide
|
|
`value.shape[split_dim]`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>split_dim</strong>: 0-D. The dimension along which to split. Must be in the range
|
|
`[0, rank(value))`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>value</strong>: The tensor to split.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</td><td class="doc"><p><strong>output</strong>: They are identically shaped tensors, whose shape matches that of <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>
|
|
except along <code>split_dim</code>, where their sizes are
|
|
`values.shape[split_dim] / num_split`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:splitV" class="def">splitV</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tlen)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_split</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: The tensor to split.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tlen</td><td class="doc"><p><strong>size_splits</strong>: list containing the sizes of each output tensor along the split
|
|
dimension. Must sum to the dimension of value along split_dim.
|
|
Can contain one -1 indicating that dimension is to be inferred.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>split_dim</strong>: 0-D. The dimension along which to split. Must be in the range
|
|
`[0, rank(value))`.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</td><td class="doc"><p><strong>output</strong>: Tensors whose shape matches that of <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>
|
|
except along <code>split_dim</code>, where their sizes are
|
|
`size_splits[i]`.</p></td></tr></table></div><div class="doc"><p>Splits a tensor into <code>num_split</code> tensors along one dimension.</p></div></div><div class="top"><p class="src"><a name="v:splitV-39-" class="def">splitV'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tlen)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_split</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: The tensor to split.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tlen</td><td class="doc"><p><strong>size_splits</strong>: list containing the sizes of each output tensor along the split
|
|
dimension. Must sum to the dimension of value along split_dim.
|
|
Can contain one -1 indicating that dimension is to be inferred.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>split_dim</strong>: 0-D. The dimension along which to split. Must be in the range
|
|
`[0, rank(value))`.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</td><td class="doc"><p><strong>output</strong>: Tensors whose shape matches that of <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>
|
|
except along <code>split_dim</code>, where their sizes are
|
|
`size_splits[i]`.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sqrt" class="def">sqrt</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes square root of x element-wise.</p><p>I.e., \(y = sqrt{x} = x^{1/2}\).</p></div></div><div class="top"><p class="src"><a name="v:sqrt-39-" class="def">sqrt'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sqrtGrad" class="def">sqrtGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Computes the gradient for the sqrt of <code>x</code> wrt its input.</p><p>Specifically, `grad = dy * 0.5 / y`, where `y = sqrt(x)`, and <code>dy</code>
|
|
is the corresponding input gradient.</p></div></div><div class="top"><p class="src"><a name="v:sqrtGrad-39-" class="def">sqrtGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:square" class="def">square</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes square of x element-wise.</p><p>I.e., \(y = x * x = x^2\).</p></div></div><div class="top"><p class="src"><a name="v:square-39-" class="def">square'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:squaredDifference" class="def">squaredDifference</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns (x - y)(x - y) element-wise.</p><ul><li>NOTE*: <code>SquaredDifference</code> supports broadcasting. More about broadcasting
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<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:squaredDifference-39-" class="def">squaredDifference'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:squeeze" class="def">squeeze</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The <code>input</code> to squeeze.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Contains the same data as <code>input</code>, but has one or more dimensions of
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size 1 removed.</p></td></tr></table></div><div class="doc"><p>Removes dimensions of size 1 from the shape of a tensor.</p><p>Given a tensor <code>input</code>, this operation returns a tensor of the same type with
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all dimensions of size 1 removed. If you don't want to remove all size 1
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dimensions, you can remove specific size 1 dimensions by specifying
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<code>squeeze_dims</code>.</p><p>For example:</p><p>```prettyprint
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|
# <code>t</code> is a tensor of shape [1, 2, 1, 3, 1, 1]
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shape(squeeze(t)) ==> [2, 3]
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```</p><p>Or, to remove specific size 1 dimensions:</p><p>```prettyprint
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# <code>t</code> is a tensor of shape [1, 2, 1, 3, 1, 1]
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|
shape(squeeze(t, [2, 4])) ==> [1, 2, 3, 1]
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|
```</p></div></div><div class="top"><p class="src"><a name="v:squeeze-39-" class="def">squeeze'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The <code>input</code> to squeeze.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Contains the same data as <code>input</code>, but has one or more dimensions of
|
|
size 1 removed.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:stack" class="def">stack</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>elem_type</strong>: The type of the elements on the stack.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong>: The handle to the stack.</p></td></tr></table></div><div class="doc"><p>A stack that produces elements in first-in last-out order.</p></div></div><div class="top"><p class="src"><a name="v:stack-39-" class="def">stack'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>elem_type</strong>: The type of the elements on the stack.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong>: The handle to the stack.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:stackClose" class="def">stackClose</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a stack.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Delete the stack from its resource container.</p></div></div><div class="top"><p class="src"><a name="v:stackClose-39-" class="def">stackClose'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a stack.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:stackPop" class="def">stackPop</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> elem_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a stack.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> elem_type)</td><td class="doc"><p><strong>elem</strong>: The tensor that is popped from the top of the stack.</p></td></tr></table></div><div class="doc"><p>Pop the element at the top of the stack.</p></div></div><div class="top"><p class="src"><a name="v:stackPop-39-" class="def">stackPop'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> elem_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a stack.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> elem_type)</td><td class="doc"><p><strong>elem</strong>: The tensor that is popped from the top of the stack.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:stackPush" class="def">stackPush</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a stack.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>elem</strong>: The tensor to be pushed onto the stack.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</td><td class="doc"><p><strong>output</strong>: The same tensor as the input <code><a href="../base-4.8.2.0/Data-Foldable.html#v:elem">elem</a></code>.</p></td></tr></table></div><div class="doc"><p>Push an element onto the stack.</p></div></div><div class="top"><p class="src"><a name="v:stackPush-39-" class="def">stackPush'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong>: The handle to a stack.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>elem</strong>: The tensor to be pushed onto the stack.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</td><td class="doc"><p><strong>output</strong>: The same tensor as the input <code><a href="../base-4.8.2.0/Data-Foldable.html#v:elem">elem</a></code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:stage" class="def">stage</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> dtypes)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'1 dtypes</td><td class="doc"><p><strong>values</strong>: a list of tensors</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Stage values similar to a lightweight Enqueue. The basic functionality of this</p><p>Op is similar to a queue with many fewer capabilities and options. This Op is
|
|
optimized for performance.</p></div></div><div class="top"><p class="src"><a name="v:stage-39-" class="def">stage'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> dtypes)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'1 dtypes</td><td class="doc"><p><strong>values</strong>: a list of tensors</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:stopGradient" class="def">stopGradient</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Stops gradient computation.</p><p>When executed in a graph, this op outputs its input tensor as-is.</p><p>When building ops to compute gradients, this op prevents the contribution of
|
|
its inputs to be taken into account. Normally, the gradient generator adds ops
|
|
to a graph to compute the derivatives of a specified <code>loss</code> by recursively
|
|
finding out inputs that contributed to its computation. If you insert this op
|
|
in the graph it inputs are masked from the gradient generator. They are not
|
|
taken into account for computing gradients.</p><p>This is useful any time you want to compute a value with TensorFlow but need
|
|
to pretend that the value was a constant. Some examples include:</p><ul><li>The *EM* algorithm where the *M-step* should not involve backpropagation
|
|
through the output of the *E-step*.</li><li>Contrastive divergence training of Boltzmann machines where, when
|
|
differentiating the energy function, the training must not backpropagate
|
|
through the graph that generated the samples from the model.</li><li>Adversarial training, where no backprop should happen through the adversarial
|
|
example generation process.</li></ul></div></div><div class="top"><p class="src"><a name="v:stopGradient-39-" class="def">stopGradient'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:stridedSlice" class="def">stridedSlice</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` index)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 index</td><td class="doc"><p><strong>begin</strong>: `begin[k]` specifies the offset into the <code>k</code>th range specification.
|
|
The exact dimension this corresponds to will be determined by context.
|
|
Out-of-bounds values will be silently clamped. If the <code>k</code>th bit of
|
|
<code>begin_mask</code> then `begin[k]` is ignored and the full range of the
|
|
appropriate dimension is used instead. Negative values causes indexing
|
|
to start from the highest element e.g. If `foo==[1,2,3]` then `foo[-1]==3`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 index</td><td class="doc"><p><strong>end</strong>: `end[i]` is like <code>begin</code> with the exception that <code>end_mask</code> is
|
|
used to determine full ranges.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 index</td><td class="doc"><p><strong>strides</strong>: `strides[i]` specifies the increment in the <code>i</code>th specification
|
|
after extracting a given element. Negative indices will reverse
|
|
the original order. Out or range values are
|
|
clamped to `[0,dim[i]) if slice[i]>0` or `[-1,dim[i]-1] if slice[i] < 0`</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Return a strided slice from <code>input</code>.</p><p>Note, most python users will want to use the Python <code><a href="Tensor.html#v:__getitem__">__getitem__</a></code>
|
|
or <code><a href="Variable.html#v:__getitem__">__getitem__</a></code> rather than this op directly.</p><p>The goal of this op is to produce a new tensor with a subset of
|
|
the elements from the <code>n</code> dimensional <code>input</code> tensor. The subset is chosen using
|
|
a sequence of <code>m</code> sparse range specifications encoded into the arguments
|
|
of this function. Note, in some cases
|
|
<code>m</code> could be equal to <code>n</code>, but this need not be the case. Each
|
|
range specification entry can be one of the following:</p><ul><li>An ellipsis (...). Ellipses are used to imply zero or more
|
|
dimensions of full-dimension selection and are produced using
|
|
<code>ellipsis_mask</code>. For example, `foo[...]` is the identity slice.</li><li>A new axis. This is used to insert a new shape=1 dimension and is
|
|
produced using <code>new_axis_mask</code>. For example, `foo[:, ...]` where
|
|
<code>foo</code> is shape `(3, 4)` produces a `(1, 3, 4)` tensor.</li><li>A range `begin:end:stride`. This is used to specify how much to choose from
|
|
a given dimension. <code>stride</code> can be any integer but 0. <code>begin</code> is an integer
|
|
which represents the index of the first value to select while <code>end</code> represents
|
|
the index of the last value to select. The number of values selected in each
|
|
dimension is `end - begin` if `stride > 0` and `begin - end` if `stride < 0`.
|
|
<code>begin</code> and <code>end</code> can be negative where `-1` is the last element, `-2` is
|
|
the second to last. <code>begin_mask</code> controls whether to replace the explicitly
|
|
given <code>begin</code> with an implicit effective value of `0` if `stride > 0` and
|
|
`-1` if `stride < 0`. <code>end_mask</code> is analogous but produces the number
|
|
required to create the largest open interval. For example, given a shape
|
|
`(3,)` tensor `foo[:]`, the effective <code>begin</code> and <code>end</code> are `0` and `3`. Do
|
|
not assume this is equivalent to `foo[0:-1]` which has an effective <code>begin</code>
|
|
and <code>end</code> of `0` and `2`. Another example is `foo[-2::-1]` which reverses the
|
|
first dimension of a tensor while dropping the last two (in the original
|
|
order elements). For example `foo = [1,2,3,4]; foo[-2::-1]` is `[4,3]`.</li><li>A single index. This is used to keep only elements that have a given
|
|
index. For example (`foo[2, :]` on a shape `(5,6)` tensor produces a
|
|
shape `(6,)` tensor. This is encoded in <code>begin</code> and <code>end</code> and
|
|
<code>shrink_axis_mask</code>.</li></ul><p>Each conceptual range specification is encoded in the op's argument. This
|
|
encoding is best understand by considering a non-trivial example. In
|
|
particular,
|
|
`foo[1, 2:4, None, ..., :-3:-1, :]` will be encoded as</p><p>```prettyprint
|
|
begin = [1, 2, x, x, 0, x] # x denotes don't care (usually 0)
|
|
end = [2, 4, x, x, -3, x]
|
|
strides = [1, 1, x, x, -1, 1]
|
|
begin_mask = 1<<4 | 1 << 5 = 48
|
|
end_mask = 1<<5 = 32
|
|
ellipsis_mask = 1<<3 = 8
|
|
new_axis_mask = 1<<2 4
|
|
shrink_axis_mask = 1<<0
|
|
```</p><p>In this case if `foo.shape` is (5, 5, 5, 5, 5, 5) the final shape of
|
|
the slice becomes (2, 1, 5, 5, 2, 5).
|
|
Let us walk step by step through each argument specification.</p><ol><li>The first argument in the example slice is turned into `begin = 1` and
|
|
`end = begin + 1 = 2`. To disambiguate from the original spec `2:4` we
|
|
also set the appropriate bit in <code>shrink_axis_mask</code>.</li><li>`2:4` is contributes 2, 4, 1 to begin, end, and stride. All masks have
|
|
zero bits contributed.</li><li>None is a synonym for `tf.newaxis`. This means insert a dimension of size 1
|
|
dimension in the final shape. Dummy values are contributed to begin,
|
|
end and stride, while the new_axis_mask bit is set.</li><li><code>...</code> grab the full ranges from as many dimensions as needed to
|
|
fully specify a slice for every dimension of the input shape.</li><li>`:-3:-1` shows the use of negative indices. A negative index <code>i</code> associated
|
|
with a dimension that has shape <code>s</code> is converted to a positive index
|
|
`s + i`. So `-1` becomes `s-1` (i.e. the last element). This conversion
|
|
is done internally so begin, end and strides receive x, -3, and -1.
|
|
The appropriate begin_mask bit is set to indicate the start range is the
|
|
full range (ignoring the x).</li><li><code>:</code> indicates that the entire contents of the corresponding dimension
|
|
is selected. This is equivalent to `::` or `0::1`. begin, end, and strides
|
|
receive 0, 0, and 1, respectively. The appropriate bits in <code>begin_mask</code> and
|
|
<code>end_mask</code> are also set.</li></ol><ul><li>Requirements*:
|
|
`0 != strides[i] for i in [0, m)`
|
|
`ellipsis_mask must be a power of two (only one ellipsis)`</li></ul></div></div><div class="top"><p class="src"><a name="v:stridedSlice-39-" class="def">stridedSlice'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` index)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 index</td><td class="doc"><p><strong>begin</strong>: `begin[k]` specifies the offset into the <code>k</code>th range specification.
|
|
The exact dimension this corresponds to will be determined by context.
|
|
Out-of-bounds values will be silently clamped. If the <code>k</code>th bit of
|
|
<code>begin_mask</code> then `begin[k]` is ignored and the full range of the
|
|
appropriate dimension is used instead. Negative values causes indexing
|
|
to start from the highest element e.g. If `foo==[1,2,3]` then `foo[-1]==3`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 index</td><td class="doc"><p><strong>end</strong>: `end[i]` is like <code>begin</code> with the exception that <code>end_mask</code> is
|
|
used to determine full ranges.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 index</td><td class="doc"><p><strong>strides</strong>: `strides[i]` specifies the increment in the <code>i</code>th specification
|
|
after extracting a given element. Negative indices will reverse
|
|
the original order. Out or range values are
|
|
clamped to `[0,dim[i]) if slice[i]>0` or `[-1,dim[i]-1] if slice[i] < 0`</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:stridedSliceAssign" class="def">stridedSliceAssign</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` index)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 index</td><td class="doc"><p><strong>begin</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 index</td><td class="doc"><p><strong>end</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 index</td><td class="doc"><p><strong>strides</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>value</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong></p></td></tr></table></div><div class="doc"><p>Assign <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> to the sliced l-value reference of <code>ref</code>.</p><p>The values of <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> are assigned to the positions in the variable
|
|
<code>ref</code> that are selected by the slice parameters. The slice parameters
|
|
`begin, <code>end</code>, <code>strides</code>, etc. work exactly as in <code>StridedSlice</code>.</p><p>NOTE this op currently does not support broadcasting and so <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>'s
|
|
shape must be exactly the shape produced by the slice of <code>ref</code>.</p></div></div><div class="top"><p class="src"><a name="v:stridedSliceAssign-39-" class="def">stridedSliceAssign'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` index)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t</td><td class="doc"><p><strong>ref</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 index</td><td class="doc"><p><strong>begin</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 index</td><td class="doc"><p><strong>end</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 index</td><td class="doc"><p><strong>strides</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>value</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> t)</td><td class="doc"><p><strong>output_ref</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:stridedSliceGrad" class="def">stridedSliceGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` index)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 index</td><td class="doc"><p><strong>shape</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 index</td><td class="doc"><p><strong>begin</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 index</td><td class="doc"><p><strong>end</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 index</td><td class="doc"><p><strong>strides</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>dy</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Returns the gradient of <code>StridedSlice</code>.</p><p>Since <code>StridedSlice</code> cuts out pieces of its <code>input</code> which is size
|
|
<code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code>, its gradient will have the same shape (which is passed here
|
|
as <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code>). The gradient will be zero in any element that the slice
|
|
does not select.</p><p>Arguments are the same as StridedSliceGrad with the exception that
|
|
<code>dy</code> is the input gradient to be propagated and <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> is the
|
|
shape of <code>StridedSlice</code>'s <code>input</code>.</p></div></div><div class="top"><p class="src"><a name="v:stridedSliceGrad-39-" class="def">stridedSliceGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` index)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 index</td><td class="doc"><p><strong>shape</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 index</td><td class="doc"><p><strong>begin</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 index</td><td class="doc"><p><strong>end</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 index</td><td class="doc"><p><strong>strides</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'5 t</td><td class="doc"><p><strong>dy</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:stringJoin" class="def">stringJoin</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>]</td><td class="doc"><p><strong>inputs</strong>: A list of string tensors. The tensors must all have the same shape,
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|
or be scalars. Scalars may be mixed in; these will be broadcast to the shape
|
|
of non-scalar inputs.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Joins the strings in the given list of string tensors into one tensor;</p><p>with the given separator (default is an empty separator).</p></div></div><div class="top"><p class="src"><a name="v:stringJoin-39-" class="def">stringJoin'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>]</td><td class="doc"><p><strong>inputs</strong>: A list of string tensors. The tensors must all have the same shape,
|
|
or be scalars. Scalars may be mixed in; these will be broadcast to the shape
|
|
of non-scalar inputs.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:stringSplit" class="def">stringSplit</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>input</strong>: 1-D. Strings to split.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>delimiter</strong>: 0-D. Delimiter characters (bytes), or empty string.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>indices</strong>, <strong>values</strong>, <strong>shape</strong>)</p><ul><li><strong>indices</strong>: A dense matrix of int64 representing the indices of the sparse tensor.</li><li><strong>values</strong>: A vector of strings corresponding to the splited values.</li><li><strong>shape</strong>: a length-2 vector of int64 representing the shape of the sparse
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|
tensor, where the first value is N and the second value is the maximum number
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|
of tokens in a single input entry.</li></ul></td></tr></table></div><div class="doc"><p>Split elements of <code>input</code> based on <code>delimiter</code> into a <code>SparseTensor</code>.</p><p>Let N be the size of source (typically N will be the batch size). Split each
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|
element of <code>input</code> based on <code>delimiter</code> and return a <code>SparseTensor</code>
|
|
containing the splitted tokens. Empty tokens are ignored.</p><p><code>delimiter</code> can be empty, or a string of split characters. If <code>delimiter</code> is an
|
|
empty string, each element of <code>input</code> is split into individual single-byte
|
|
character strings, including splitting of UTF-8 multibyte sequences. Otherwise
|
|
every character of <code>delimiter</code> is a potential split point.</p><p>For example:
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|
N = 2, input[0] is 'hello world' and input[1] is 'a b c', then the output
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|
will be</p><p>indices = [0, 0;
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|
0, 1;
|
|
1, 0;
|
|
1, 1;
|
|
1, 2]
|
|
shape = [2, 3]
|
|
values = [<code>hello</code>, <code>world</code>, <code>a</code>, <code>b</code>, <code>c</code>]</p></div></div><div class="top"><p class="src"><a name="v:stringSplit-39-" class="def">stringSplit'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>input</strong>: 1-D. Strings to split.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>delimiter</strong>: 0-D. Delimiter characters (bytes), or empty string.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>indices</strong>, <strong>values</strong>, <strong>shape</strong>)</p><ul><li><strong>indices</strong>: A dense matrix of int64 representing the indices of the sparse tensor.</li><li><strong>values</strong>: A vector of strings corresponding to the splited values.</li><li><strong>shape</strong>: a length-2 vector of int64 representing the shape of the sparse
|
|
tensor, where the first value is N and the second value is the maximum number
|
|
of tokens in a single input entry.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:stringToHashBucket" class="def">stringToHashBucket</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_buckets</strong>: The number of buckets.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>string_tensor</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>output</strong>: A Tensor of the same shape as the input <code>string_tensor</code>.</p></td></tr></table></div><div class="doc"><p>Converts each string in the input Tensor to its hash mod by a number of buckets.</p><p>The hash function is deterministic on the content of the string within the
|
|
process.</p><p>Note that the hash function may change from time to time.
|
|
This functionality will be deprecated and it's recommended to use
|
|
`tf.string_to_hash_bucket_fast()` or `tf.string_to_hash_bucket_strong()`.</p></div></div><div class="top"><p class="src"><a name="v:stringToHashBucket-39-" class="def">stringToHashBucket'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_buckets</strong>: The number of buckets.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>string_tensor</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>output</strong>: A Tensor of the same shape as the input <code>string_tensor</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:stringToHashBucketFast" class="def">stringToHashBucketFast</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_buckets</strong>: The number of buckets.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>input</strong>: The strings to assign a hash bucket.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>output</strong>: A Tensor of the same shape as the input <code>string_tensor</code>.</p></td></tr></table></div><div class="doc"><p>Converts each string in the input Tensor to its hash mod by a number of buckets.</p><p>The hash function is deterministic on the content of the string within the
|
|
process and will never change. However, it is not suitable for cryptography.
|
|
This function may be used when CPU time is scarce and inputs are trusted or
|
|
unimportant. There is a risk of adversaries constructing inputs that all hash
|
|
to the same bucket. To prevent this problem, use a strong hash function with
|
|
`tf.string_to_hash_bucket_strong`.</p></div></div><div class="top"><p class="src"><a name="v:stringToHashBucketFast-39-" class="def">stringToHashBucketFast'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_buckets</strong>: The number of buckets.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>input</strong>: The strings to assign a hash bucket.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>output</strong>: A Tensor of the same shape as the input <code>string_tensor</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:stringToHashBucketStrong" class="def">stringToHashBucketStrong</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_buckets</strong>: The number of buckets.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>input</strong>: The strings to assign a hash bucket.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>output</strong>: A Tensor of the same shape as the input <code>string_tensor</code>.</p></td></tr></table></div><div class="doc"><p>Converts each string in the input Tensor to its hash mod by a number of buckets.</p><p>The hash function is deterministic on the content of the string within the
|
|
process. The hash function is a keyed hash function, where attribute <code>key</code>
|
|
defines the key of the hash function. <code>key</code> is an array of 2 elements.</p><p>A strong hash is important when inputs may be malicious, e.g. URLs with
|
|
additional components. Adversaries could try to make their inputs hash to the
|
|
same bucket for a denial-of-service attack or to skew the results. A strong
|
|
hash prevents this by making it dificult, if not infeasible, to compute inputs
|
|
that hash to the same bucket. This comes at a cost of roughly 4x higher compute
|
|
time than `tf.string_to_hash_bucket_fast`.</p></div></div><div class="top"><p class="src"><a name="v:stringToHashBucketStrong-39-" class="def">stringToHashBucketStrong'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_buckets</strong>: The number of buckets.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>input</strong>: The strings to assign a hash bucket.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>output</strong>: A Tensor of the same shape as the input <code>string_tensor</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:stringToNumber" class="def">stringToNumber</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` out_type</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>string_tensor</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</td><td class="doc"><p><strong>output</strong>: A Tensor of the same shape as the input <code>string_tensor</code>.</p></td></tr></table></div><div class="doc"><p>Converts each string in the input Tensor to the specified numeric type.</p><p>(Note that int32 overflow results in an error while float overflow
|
|
results in a rounded value.)</p></div></div><div class="top"><p class="src"><a name="v:stringToNumber-39-" class="def">stringToNumber'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` out_type</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>string_tensor</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_type</td><td class="doc"><p><strong>output</strong>: A Tensor of the same shape as the input <code>string_tensor</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sub" class="def">sub</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns x - y element-wise.</p><ul><li>NOTE*: <code>Sub</code> supports broadcasting. More about broadcasting
|
|
<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:sub-39-" class="def">sub'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:substr" class="def">substr</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>input</strong>: Tensor of strings</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>pos</strong>: Scalar defining the position of first character in each substring</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>len</strong>: Scalar defining the number of characters to include in each substring</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>output</strong>: Tensor of substrings</p></td></tr></table></div><div class="doc"><p>Return substrings from <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> of strings.</p><p>For each string in the input <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code>, creates a substring starting at index
|
|
<code>pos</code> with a total length of <code>len</code>.</p><p>If <code>len</code> defines a substring that would extend beyond the length of the input
|
|
string, then as many characters as possible are used.</p><p>If <code>pos</code> is negative or specifies a character index larger than any of the input
|
|
strings, then an <code>InvalidArgumentError</code> is thrown.</p><p><code>pos</code> and <code>len</code> must have the same shape, otherwise a <code>ValueError</code> is thrown on
|
|
Op creation.</p><ul><li>NOTE*: <code>Substr</code> supports broadcasting up to two dimensions. More about
|
|
broadcasting
|
|
<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li><li>--</li></ul><p>Examples</p><p>Using scalar <code>pos</code> and <code>len</code>:</p><p>```
|
|
input = [b<code>Hello</code>, b<code>World</code>]
|
|
position = 1
|
|
length = 3</p><p>output = [b<code>ell</code>, b<code>orl</code>]
|
|
```</p><p>Using <code>pos</code> and <code>len</code> with same shape as <code>input</code>:</p><p>```
|
|
input = [[b<code>ten</code>, b<code>eleven</code>, b<code>twelve</code>],
|
|
[b<code>thirteen</code>, b<code>fourteen</code>, b<code>fifteen</code>],
|
|
[b<code>sixteen</code>, b<code>seventeen</code>, b<code>eighteen</code>]]
|
|
position = [[1, 2, 3],
|
|
[1, 2, 3],
|
|
[1, 2, 3]]
|
|
length = [[2, 3, 4],
|
|
[4, 3, 2],
|
|
[5, 5, 5]]</p><p>output = [[b<code>en</code>, b<code>eve</code>, b<code>lve</code>],
|
|
[b<code>hirt</code>, b<code>urt</code>, b<code>te</code>],
|
|
[b<code>ixtee</code>, b<code>vente</code>, b<code>hteen</code>]]
|
|
```</p><p>Broadcasting <code>pos</code> and <code>len</code> onto <code>input</code>:</p><p>```
|
|
input = [[b<code>ten</code>, b<code>eleven</code>, b<code>twelve</code>],
|
|
[b<code>thirteen</code>, b<code>fourteen</code>, b<code>fifteen</code>],
|
|
[b<code>sixteen</code>, b<code>seventeen</code>, b<code>eighteen</code>],
|
|
[b<code>nineteen</code>, b<code>twenty</code>, b<code>twentyone</code>]]
|
|
position = [1, 2, 3]
|
|
length = [1, 2, 3]</p><p>output = [[b<code>e</code>, b<code>ev</code>, b<code>lve</code>],
|
|
[b<code>h</code>, b<code>ur</code>, b<code>tee</code>],
|
|
[b<code>i</code>, b<code>ve</code>, b<code>hte</code>],
|
|
[b<code>i</code>, b<code>en</code>, b<code>nty</code>]]
|
|
```</p><p>Broadcasting <code>input</code> onto <code>pos</code> and <code>len</code>:</p><p>```
|
|
input = b<code>thirteen</code>
|
|
position = [1, 5, 7]
|
|
length = [3, 2, 1]</p><p>output = [b<code>hir</code>, b<code>ee</code>, b'n"]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:substr-39-" class="def">substr'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>input</strong>: Tensor of strings</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>pos</strong>: Scalar defining the position of first character in each substring</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>len</strong>: Scalar defining the number of characters to include in each substring</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>output</strong>: Tensor of substrings</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:sum" class="def">sum</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The tensor to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>reduction_indices</strong>: The dimensions to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The reduced tensor.</p></td></tr></table></div><div class="doc"><p>Computes the sum of elements across dimensions of a tensor.</p><p>Reduces <code>input</code> along the dimensions given in <code>reduction_indices</code>. Unless
|
|
<code>keep_dims</code> is true, the rank of the tensor is reduced by 1 for each entry in
|
|
<code>reduction_indices</code>. If <code>keep_dims</code> is true, the reduced dimensions are
|
|
retained with length 1.</p></div></div><div class="top"><p class="src"><a name="v:sum-39-" class="def">sum'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tidx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The tensor to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tidx</td><td class="doc"><p><strong>reduction_indices</strong>: The dimensions to reduce.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: The reduced tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:svd" class="def">svd</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: A tensor of shape `[..., M, N]` whose inner-most 2 dimensions
|
|
form matrices of size `[M, N]`. Let <code>P</code> be the minimum of <code>M</code> and <code>N</code>.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>s</strong>, <strong>u</strong>, <strong>v</strong>)</p><ul><li><strong>s</strong>: Singular values. Shape is `[..., P]`.</li><li><strong>u</strong>: Left singular vectors. If <code>full_matrices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:False">False</a></code> then shape is
|
|
`[..., M, P]`; if <code>full_matrices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code> then shape is
|
|
`[..., M, M]`. Undefined if <code>compute_uv</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:False">False</a></code>.</li><li><strong>v</strong>: Left singular vectors. If <code>full_matrices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:False">False</a></code> then shape is
|
|
`[..., N, P]`. If <code>full_matrices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code> then shape is `[..., N, N]`.
|
|
Undefined if <code>compute_uv</code> is false.</li></ul></td></tr></table></div><div class="doc"><p>Computes the singular value decompositions of one or more matrices.</p><p>Computes the SVD of each inner matrix in <code>input</code> such that
|
|
`input[..., :, :] = u[..., :, :] * diag(s[..., :, :]) * transpose(v[..., :, :])`</p><p>```prettyprint
|
|
# a is a tensor containing a batch of matrices.
|
|
# s is a tensor of singular values for each matrix.
|
|
# u is the tensor containing of left singular vectors for each matrix.
|
|
# v is the tensor containing of right singular vectors for each matrix.
|
|
s, u, v = svd(a)
|
|
s, _, _ = svd(a, compute_uv=False)
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:svd-39-" class="def">svd'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: A tensor of shape `[..., M, N]` whose inner-most 2 dimensions
|
|
form matrices of size `[M, N]`. Let <code>P</code> be the minimum of <code>M</code> and <code>N</code>.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>s</strong>, <strong>u</strong>, <strong>v</strong>)</p><ul><li><strong>s</strong>: Singular values. Shape is `[..., P]`.</li><li><strong>u</strong>: Left singular vectors. If <code>full_matrices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:False">False</a></code> then shape is
|
|
`[..., M, P]`; if <code>full_matrices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code> then shape is
|
|
`[..., M, M]`. Undefined if <code>compute_uv</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:False">False</a></code>.</li><li><strong>v</strong>: Left singular vectors. If <code>full_matrices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:False">False</a></code> then shape is
|
|
`[..., N, P]`. If <code>full_matrices</code> is <code><a href="../base-4.8.2.0/Data-Bool.html#v:True">True</a></code> then shape is `[..., N, N]`.
|
|
Undefined if <code>compute_uv</code> is false.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:switch" class="def">switch</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong>: The tensor to be forwarded to the appropriate output.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>pred</strong>: A scalar that specifies which output port will receive data.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>output_false</strong>, <strong>output_true</strong>)</p><ul><li><strong>output_false</strong>: If <code><a href="../base-4.8.2.0/Prelude.html#v:pred">pred</a></code> is false, data will be forwarded to this output.</li><li><strong>output_true</strong>: If <code><a href="../base-4.8.2.0/Prelude.html#v:pred">pred</a></code> is true, data will be forwarded to this output.</li></ul></td></tr></table></div><div class="doc"><p>Forwards `data` to the output port determined by <code><a href="../base-4.8.2.0/Prelude.html#v:pred">pred</a></code>.</p><p>If <code><a href="../base-4.8.2.0/Prelude.html#v:pred">pred</a></code> is true, the `data` input is forwarded to <code>output_true</code>. Otherwise,
|
|
the data goes to <code>output_false</code>.</p><p>See also <code>RefSwitch</code> and <code>Merge</code>.</p></div></div><div class="top"><p class="src"><a name="v:switch-39-" class="def">switch'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong>: The tensor to be forwarded to the appropriate output.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>pred</strong>: A scalar that specifies which output port will receive data.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t)</td><td class="doc"><p>(<strong>output_false</strong>, <strong>output_true</strong>)</p><ul><li><strong>output_false</strong>: If <code><a href="../base-4.8.2.0/Prelude.html#v:pred">pred</a></code> is false, data will be forwarded to this output.</li><li><strong>output_true</strong>: If <code><a href="../base-4.8.2.0/Prelude.html#v:pred">pred</a></code> is true, data will be forwarded to this output.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tFRecordReader" class="def">tFRecordReader</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div><div class="doc"><p>A Reader that outputs the records from a TensorFlow Records file.</p></div></div><div class="top"><p class="src"><a name="v:tFRecordReader-39-" class="def">tFRecordReader'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tFRecordReaderV2" class="def">tFRecordReaderV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div><div class="doc"><p>A Reader that outputs the records from a TensorFlow Records file.</p></div></div><div class="top"><p class="src"><a name="v:tFRecordReaderV2-39-" class="def">tFRecordReaderV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:takeManySparseFromTensorsMap" class="def">takeManySparseFromTensorsMap</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sparse_handles</strong>: 1-D, The <code>N</code> serialized <code>SparseTensor</code> objects.
|
|
Shape: `[N]`.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>sparse_indices</strong>, <strong>sparse_values</strong>, <strong>sparse_shape</strong>)</p><ul><li><strong>sparse_indices</strong>: 2-D. The <code>indices</code> of the minibatch <code>SparseTensor</code>.</li><li><strong>sparse_values</strong>: 1-D. The <code>values</code> of the minibatch <code>SparseTensor</code>.</li><li><strong>sparse_shape</strong>: 1-D. The <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> of the minibatch <code>SparseTensor</code>.</li></ul></td></tr></table></div><div class="doc"><p>Read <code>SparseTensors</code> from a <code>SparseTensorsMap</code> and concatenate them.</p><p>The input <code>sparse_handles</code> must be an <code>int64</code> matrix of shape `[N, 1]` where
|
|
<code>N</code> is the minibatch size and the rows correspond to the output handles of
|
|
<code>AddSparseToTensorsMap</code> or <code>AddManySparseToTensorsMap</code>. The ranks of the
|
|
original <code>SparseTensor</code> objects that went into the given input ops must all
|
|
match. When the final <code>SparseTensor</code> is created, it has rank one
|
|
higher than the ranks of the incoming <code>SparseTensor</code> objects
|
|
(they have been concatenated along a new row dimension on the left).</p><p>The output <code>SparseTensor</code> object's shape values for all dimensions but the
|
|
first are the max across the input <code>SparseTensor</code> objects' shape values
|
|
for the corresponding dimensions. Its first shape value is <code>N</code>, the minibatch
|
|
size.</p><p>The input <code>SparseTensor</code> objects' indices are assumed ordered in
|
|
standard lexicographic order. If this is not the case, after this
|
|
step run <code>SparseReorder</code> to restore index ordering.</p><p>For example, if the handles represent an input, which is a `[2, 3]` matrix
|
|
representing two original <code>SparseTensor</code> objects:</p><p>```
|
|
index = [ 0]
|
|
[10]
|
|
[20]
|
|
values = [1, 2, 3]
|
|
shape = [50]
|
|
```</p><p>and</p><p>```
|
|
index = [ 2]
|
|
[10]
|
|
values = [4, 5]
|
|
shape = [30]
|
|
```</p><p>then the final <code>SparseTensor</code> will be:</p><p>```
|
|
index = [0 0]
|
|
[0 10]
|
|
[0 20]
|
|
[1 2]
|
|
[1 10]
|
|
values = [1, 2, 3, 4, 5]
|
|
shape = [2 50]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:takeManySparseFromTensorsMap-39-" class="def">takeManySparseFromTensorsMap'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>sparse_handles</strong>: 1-D, The <code>N</code> serialized <code>SparseTensor</code> objects.
|
|
Shape: `[N]`.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>sparse_indices</strong>, <strong>sparse_values</strong>, <strong>sparse_shape</strong>)</p><ul><li><strong>sparse_indices</strong>: 2-D. The <code>indices</code> of the minibatch <code>SparseTensor</code>.</li><li><strong>sparse_values</strong>: 1-D. The <code>values</code> of the minibatch <code>SparseTensor</code>.</li><li><strong>sparse_shape</strong>: 1-D. The <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> of the minibatch <code>SparseTensor</code>.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tan" class="def">tan</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes tan of x element-wise.</p></div></div><div class="top"><p class="src"><a name="v:tan-39-" class="def">tan'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tanh" class="def">tanh</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Computes hyperbolic tangent of <code>x</code> element-wise.</p></div></div><div class="top"><p class="src"><a name="v:tanh-39-" class="def">tanh'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tanhGrad" class="def">tanhGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Computes the gradient for the tanh of <code>x</code> wrt its input.</p><p>Specifically, `grad = dy * (1 - y*y)`, where `y = tanh(x)`, and <code>dy</code>
|
|
is the corresponding input gradient.</p></div></div><div class="top"><p class="src"><a name="v:tanhGrad-39-" class="def">tanhGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:temporaryVariable" class="def">temporaryVariable</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: The shape of the variable tensor.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> dtype)</td><td class="doc"><p><strong>ref</strong>: A reference to the variable tensor.</p></td></tr></table></div><div class="doc"><p>Returns a tensor that may be mutated, but only persists within a single step.</p><p>This is an experimental op for internal use only and it is possible to use this
|
|
op in unsafe ways. DO NOT USE unless you fully understand the risks.</p><p>It is the caller's responsibility to ensure that <code>ref</code> is eventually passed to a
|
|
matching <code>DestroyTemporaryVariable</code> op after all other uses have completed.</p><p>Outputs a ref to the tensor state so it may be read or modified.</p><p>E.g.
|
|
var = state_ops._temporary_variable([1, 2], types.float_)
|
|
var_name = var.op.name
|
|
var = state_ops.assign(var, [[4.0, 5.0]])
|
|
var = state_ops.assign_add(var, [[6.0, 7.0]])
|
|
final = state_ops._destroy_temporary_variable(var, var_name=var_name)</p></div></div><div class="top"><p class="src"><a name="v:temporaryVariable-39-" class="def">temporaryVariable'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: The shape of the variable tensor.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> dtype)</td><td class="doc"><p><strong>ref</strong>: A reference to the variable tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArray" class="def">tensorArray</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>dtype</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArray-39-" class="def">tensorArray'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>dtype</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayClose" class="def">tensorArrayClose</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayClose-39-" class="def">tensorArrayClose'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayCloseV2" class="def">tensorArrayCloseV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Deprecated. Use TensorArrayCloseV3</p></div></div><div class="top"><p class="src"><a name="v:tensorArrayCloseV2-39-" class="def">tensorArrayCloseV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayCloseV3" class="def">tensorArrayCloseV3</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a TensorArray (output of TensorArray or TensorArrayGrad).</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Delete the TensorArray from its resource container. This enables</p><p>the user to close and release the resource in the middle of a step/run.</p></div></div><div class="top"><p class="src"><a name="v:tensorArrayCloseV3-39-" class="def">tensorArrayCloseV3'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a TensorArray (output of TensorArray or TensorArrayGrad).</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayConcat" class="def">tensorArrayConcat</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>value</strong>, <strong>lengths</strong>)</p><ul><li><strong>value</strong></li><li><strong>lengths</strong></li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayConcat-39-" class="def">tensorArrayConcat'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>value</strong>, <strong>lengths</strong>)</p><ul><li><strong>value</strong></li><li><strong>lengths</strong></li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayConcatV2" class="def">tensorArrayConcatV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>value</strong>, <strong>lengths</strong>)</p><ul><li><strong>value</strong></li><li><strong>lengths</strong></li></ul></td></tr></table></div><div class="doc"><p>Deprecated. Use TensorArrayConcatV3</p></div></div><div class="top"><p class="src"><a name="v:tensorArrayConcatV2-39-" class="def">tensorArrayConcatV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>value</strong>, <strong>lengths</strong>)</p><ul><li><strong>value</strong></li><li><strong>lengths</strong></li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayConcatV3" class="def">tensorArrayConcatV3</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>value</strong>, <strong>lengths</strong>)</p><ul><li><strong>value</strong>: All of the elements in the TensorArray, concatenated along the first
|
|
axis.</li><li><strong>lengths</strong>: A vector of the row sizes of the original T elements in the
|
|
value output. In the example above, this would be the values:
|
|
`(n1, n2, ..., n(T-1))`.</li></ul></td></tr></table></div><div class="doc"><p>Concat the elements from the TensorArray into value <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>.</p><p>Takes <code>T</code> elements of shapes</p><p>```
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|
(n0 x d0 x d1 x ...), (n1 x d0 x d1 x ...), ..., (n(T-1) x d0 x d1 x ...)
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|
```</p><p>and concatenates them into a Tensor of shape:</p><p>```(n0 + n1 + ... + n(T-1) x d0 x d1 x ...)```</p><p>All elements must have the same shape (excepting the first dimension).</p></div></div><div class="top"><p class="src"><a name="v:tensorArrayConcatV3-39-" class="def">tensorArrayConcatV3'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>)</td><td class="doc"><p>(<strong>value</strong>, <strong>lengths</strong>)</p><ul><li><strong>value</strong>: All of the elements in the TensorArray, concatenated along the first
|
|
axis.</li><li><strong>lengths</strong>: A vector of the row sizes of the original T elements in the
|
|
value output. In the example above, this would be the values:
|
|
`(n1, n2, ..., n(T-1))`.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayGather" class="def">tensorArrayGather</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>indices</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>value</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayGather-39-" class="def">tensorArrayGather'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>indices</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>value</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayGatherV2" class="def">tensorArrayGatherV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>indices</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</td><td class="doc"><p><strong>value</strong></p></td></tr></table></div><div class="doc"><p>Deprecated. Use TensorArrayGatherV3</p></div></div><div class="top"><p class="src"><a name="v:tensorArrayGatherV2-39-" class="def">tensorArrayGatherV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>indices</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</td><td class="doc"><p><strong>value</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayGatherV3" class="def">tensorArrayGatherV3</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>indices</strong>: The locations in the TensorArray from which to read tensor elements.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>value</strong>: All of the elements in the TensorArray, concatenated along a new
|
|
axis (the new dimension 0).</p></td></tr></table></div><div class="doc"><p>Gather specific elements from the TensorArray into output <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>.</p><p>All elements selected by <code>indices</code> must have the same shape.</p></div></div><div class="top"><p class="src"><a name="v:tensorArrayGatherV3-39-" class="def">tensorArrayGatherV3'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>indices</strong>: The locations in the TensorArray from which to read tensor elements.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>value</strong>: All of the elements in the TensorArray, concatenated along a new
|
|
axis (the new dimension 0).</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayGrad" class="def">tensorArrayGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>grad_handle</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayGrad-39-" class="def">tensorArrayGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>grad_handle</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayGradV2" class="def">tensorArrayGradV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>grad_handle</strong></p></td></tr></table></div><div class="doc"><p>Deprecated. Use TensorArrayGradV3</p></div></div><div class="top"><p class="src"><a name="v:tensorArrayGradV2-39-" class="def">tensorArrayGradV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>grad_handle</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayGradV3" class="def">tensorArrayGradV3</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to the forward TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>grad_handle</strong>, <strong>flow_out</strong>)</p><ul><li><strong>grad_handle</strong></li><li><strong>flow_out</strong></li></ul></td></tr></table></div><div class="doc"><p>Creates a TensorArray for storing the gradients of values in the given handle.</p><p>If the given TensorArray gradient already exists, returns a reference to it.</p><p>Locks the size of the original TensorArray by disabling its dynamic size flag.</p><ul><li>*A note about the input flow_in:**</li></ul><p>The handle flow_in forces the execution of the gradient lookup to occur
|
|
only after certain other operations have occurred. For example, when
|
|
the forward TensorArray is dynamically sized, writes to this TensorArray
|
|
may resize the object. The gradient TensorArray is statically sized based
|
|
on the size of the forward TensorArray when this operation executes.
|
|
Furthermore, the size of the forward TensorArray is frozen by this call.
|
|
As a result, the flow is used to ensure that the call to generate the gradient
|
|
TensorArray only happens after all writes are executed.</p><p>In the case of dynamically sized TensorArrays, gradient computation should
|
|
only be performed on read operations that have themselves been chained via
|
|
flow to occur only after all writes have executed. That way the final size
|
|
of the forward TensorArray is known when this operation is called.</p><ul><li>*A note about the source attribute:**</li></ul><p>TensorArray gradient calls use an accumulator TensorArray object. If
|
|
multiple gradients are calculated and run in the same session, the multiple
|
|
gradient nodes may accidentally flow throuth the same accumulator TensorArray.
|
|
This double counts and generally breaks the TensorArray gradient flow.</p><p>The solution is to identify which gradient call this particular
|
|
TensorArray gradient is being called in. This is performed by identifying
|
|
a unique string (e.g. "gradients", "gradients_1", ...) from the input
|
|
gradient Tensor's name. This string is used as a suffix when creating
|
|
the TensorArray gradient object here (the attribute <code>source</code>).</p><p>The attribute <code>source</code> is added as a suffix to the forward TensorArray's
|
|
name when performing the creation / lookup, so that each separate gradient
|
|
calculation gets its own TensorArray accumulator.</p></div></div><div class="top"><p class="src"><a name="v:tensorArrayGradV3-39-" class="def">tensorArrayGradV3'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to the forward TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>grad_handle</strong>, <strong>flow_out</strong>)</p><ul><li><strong>grad_handle</strong></li><li><strong>flow_out</strong></li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayPack" class="def">tensorArrayPack</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>value</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayPack-39-" class="def">tensorArrayPack'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>value</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayRead" class="def">tensorArrayRead</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>index</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>value</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayRead-39-" class="def">tensorArrayRead'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>index</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>value</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayReadV2" class="def">tensorArrayReadV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>index</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</td><td class="doc"><p><strong>value</strong></p></td></tr></table></div><div class="doc"><p>Deprecated. Use TensorArrayReadV3</p></div></div><div class="top"><p class="src"><a name="v:tensorArrayReadV2-39-" class="def">tensorArrayReadV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>index</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dtype</td><td class="doc"><p><strong>value</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayReadV3" class="def">tensorArrayReadV3</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>index</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>value</strong>: The tensor that is read from the TensorArray.</p></td></tr></table></div><div class="doc"><p>Read an element from the TensorArray into output <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>.</p></div></div><div class="top"><p class="src"><a name="v:tensorArrayReadV3-39-" class="def">tensorArrayReadV3'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>index</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>value</strong>: The tensor that is read from the TensorArray.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayScatter" class="def">tensorArrayScatter</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>indices</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>flow_out</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayScatter-39-" class="def">tensorArrayScatter'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>indices</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>flow_out</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayScatterV2" class="def">tensorArrayScatterV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>indices</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_out</strong></p></td></tr></table></div><div class="doc"><p>Deprecated. Use TensorArrayScatterV3</p></div></div><div class="top"><p class="src"><a name="v:tensorArrayScatterV2-39-" class="def">tensorArrayScatterV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>indices</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_out</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayScatterV3" class="def">tensorArrayScatterV3</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>indices</strong>: The locations at which to write the tensor elements.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>value</strong>: The concatenated tensor to write to the TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>flow_out</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr></table></div><div class="doc"><p>Scatter the data from the input value into specific TensorArray elements.</p><p><code>indices</code> must be a vector, its length must match the first dim of <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>.</p></div></div><div class="top"><p class="src"><a name="v:tensorArrayScatterV3-39-" class="def">tensorArrayScatterV3'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>indices</strong>: The locations at which to write the tensor elements.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>value</strong>: The concatenated tensor to write to the TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>flow_out</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArraySize" class="def">tensorArraySize</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p><strong>size</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArraySize-39-" class="def">tensorArraySize'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p><strong>size</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArraySizeV2" class="def">tensorArraySizeV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong></p></td></tr></table></div><div class="doc"><p>Deprecated. Use TensorArraySizeV3</p></div></div><div class="top"><p class="src"><a name="v:tensorArraySizeV2-39-" class="def">tensorArraySizeV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArraySizeV3" class="def">tensorArraySizeV3</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a TensorArray (output of TensorArray or TensorArrayGrad).</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p><strong>size</strong>: The current size of the TensorArray.</p></td></tr></table></div><div class="doc"><p>Get the current size of the TensorArray.</p></div></div><div class="top"><p class="src"><a name="v:tensorArraySizeV3-39-" class="def">tensorArraySizeV3'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a TensorArray (output of TensorArray or TensorArrayGrad).</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p><strong>size</strong>: The current size of the TensorArray.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArraySplit" class="def">tensorArraySplit</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>lengths</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>flow_out</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArraySplit-39-" class="def">tensorArraySplit'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>lengths</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>flow_out</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArraySplitV2" class="def">tensorArraySplitV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>lengths</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_out</strong></p></td></tr></table></div><div class="doc"><p>Deprecated. Use TensorArraySplitV3</p></div></div><div class="top"><p class="src"><a name="v:tensorArraySplitV2-39-" class="def">tensorArraySplitV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>lengths</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_out</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArraySplitV3" class="def">tensorArraySplitV3</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>value</strong>: The concatenated tensor to write to the TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>lengths</strong>: The vector of lengths, how to split the rows of value into the
|
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TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>flow_out</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr></table></div><div class="doc"><p>Split the data from the input value into TensorArray elements.</p><p>Assuming that <code>lengths</code> takes on values</p><p>```(n0, n1, ..., n(T-1))```</p><p>and that <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> has shape</p><p>```(n0 + n1 + ... + n(T-1) x d0 x d1 x ...)```,</p><p>this splits values into a TensorArray with T tensors.</p><p>TensorArray index t will be the subtensor of values with starting position</p><p>```(n0 + n1 + ... + n(t-1), 0, 0, ...)```</p><p>and having size</p><p>```nt x d0 x d1 x ...```</p></div></div><div class="top"><p class="src"><a name="v:tensorArraySplitV3-39-" class="def">tensorArraySplitV3'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>value</strong>: The concatenated tensor to write to the TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>lengths</strong>: The vector of lengths, how to split the rows of value into the
|
|
TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>flow_out</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayUnpack" class="def">tensorArrayUnpack</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>flow_out</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayUnpack-39-" class="def">tensorArrayUnpack'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>flow_out</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayV2" class="def">tensorArrayV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>dtype</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong></p></td></tr></table></div><div class="doc"><p>Deprecated. Use TensorArrayV3</p></div></div><div class="top"><p class="src"><a name="v:tensorArrayV2-39-" class="def">tensorArrayV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>dtype</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>handle</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayV3" class="def">tensorArrayV3</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>dtype</strong>: The type of the elements on the tensor_array.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong>: The size of the array.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>handle</strong>, <strong>flow</strong>)</p><ul><li><strong>handle</strong>: The handle to the TensorArray.</li><li><strong>flow</strong>: A scalar used to control gradient flow.</li></ul></td></tr></table></div><div class="doc"><p>An array of Tensors of given size, with data written via Write and read</p><p>via Read or Pack.</p></div></div><div class="top"><p class="src"><a name="v:tensorArrayV3-39-" class="def">tensorArrayV3'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>dtype</strong>: The type of the elements on the tensor_array.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>size</strong>: The size of the array.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>handle</strong>, <strong>flow</strong>)</p><ul><li><strong>handle</strong>: The handle to the TensorArray.</li><li><strong>flow</strong>: A scalar used to control gradient flow.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayWrite" class="def">tensorArrayWrite</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>index</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>flow_out</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayWrite-39-" class="def">tensorArrayWrite'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>index</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>flow_out</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayWriteV2" class="def">tensorArrayWriteV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>index</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_out</strong></p></td></tr></table></div><div class="doc"><p>Deprecated. Use TensorArrayGradV3</p></div></div><div class="top"><p class="src"><a name="v:tensorArrayWriteV2-39-" class="def">tensorArrayWriteV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>handle</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>index</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>value</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_out</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorArrayWriteV3" class="def">tensorArrayWriteV3</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>index</strong>: The position to write to inside the TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>value</strong>: The tensor to write to the TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>flow_out</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr></table></div><div class="doc"><p>Push an element onto the tensor_array.</p></div></div><div class="top"><p class="src"><a name="v:tensorArrayWriteV3-39-" class="def">tensorArrayWriteV3'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>handle</strong>: The handle to a TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>index</strong>: The position to write to inside the TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 t</td><td class="doc"><p><strong>value</strong>: The tensor to write to the TensorArray.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'4 <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a></td><td class="doc"><p><strong>flow_in</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p><strong>flow_out</strong>: A float scalar that enforces proper chaining of operations.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tensorSummary" class="def">tensorSummary</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>tensor</strong>: A tensor to serialize.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>summary</strong></p></td></tr></table></div><div class="doc"><p>Outputs a <code>Summary</code> protocol buffer with a tensor.</p></div></div><div class="top"><p class="src"><a name="v:tensorSummary-39-" class="def">tensorSummary'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>tensor</strong>: A tensor to serialize.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>summary</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:textLineReader" class="def">textLineReader</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div><div class="doc"><p>A Reader that outputs the lines of a file delimited by '\n'.</p></div></div><div class="top"><p class="src"><a name="v:textLineReader-39-" class="def">textLineReader'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:textLineReaderV2" class="def">textLineReaderV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div><div class="doc"><p>A Reader that outputs the lines of a file delimited by '\n'.</p></div></div><div class="top"><p class="src"><a name="v:textLineReaderV2-39-" class="def">textLineReaderV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:threadUnsafeUnigramCandidateSampler" class="def">threadUnsafeUnigramCandidateSampler</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_sampled</strong>: Number of candidates to randomly sample per batch.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_true</strong>: Number of true labels per context.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>range_max</strong>: The sampler will sample integers from the interval [0, range_max).</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>unique</strong>: If unique is true, we sample with rejection, so that all sampled
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candidates in a batch are unique. This requires some approximation to
|
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estimate the post-rejection sampling probabilities.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>true_classes</strong>: A batch_size * num_true matrix, in which each row contains the
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IDs of the num_true target_classes in the corresponding original label.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>sampled_candidates</strong>, <strong>true_expected_count</strong>, <strong>sampled_expected_count</strong>)</p><ul><li><strong>sampled_candidates</strong>: A vector of length num_sampled, in which each element is
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the ID of a sampled candidate.</li><li><strong>true_expected_count</strong>: A batch_size * num_true matrix, representing
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|
the number of times each candidate is expected to occur in a batch
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of sampled candidates. If unique=true, then this is a probability.</li><li><strong>sampled_expected_count</strong>: A vector of length num_sampled, for each sampled
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candidate representing the number of times the candidate is expected
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|
to occur in a batch of sampled candidates. If unique=true, then this is a
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probability.</li></ul></td></tr></table></div><div class="doc"><p>Generates labels for candidate sampling with a learned unigram distribution.</p><p>See explanations of candidate sampling and the data formats at
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go/candidate-sampling.</p><p>For each batch, this op picks a single set of sampled candidate labels.</p><p>The advantages of sampling candidates per-batch are simplicity and the
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possibility of efficient dense matrix multiplication. The disadvantage is that
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the sampled candidates must be chosen independently of the context and of the
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true labels.</p></div></div><div class="top"><p class="src"><a name="v:threadUnsafeUnigramCandidateSampler-39-" class="def">threadUnsafeUnigramCandidateSampler'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_sampled</strong>: Number of candidates to randomly sample per batch.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_true</strong>: Number of true labels per context.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>range_max</strong>: The sampler will sample integers from the interval [0, range_max).</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>unique</strong>: If unique is true, we sample with rejection, so that all sampled
|
|
candidates in a batch are unique. This requires some approximation to
|
|
estimate the post-rejection sampling probabilities.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>true_classes</strong>: A batch_size * num_true matrix, in which each row contains the
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IDs of the num_true target_classes in the corresponding original label.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>sampled_candidates</strong>, <strong>true_expected_count</strong>, <strong>sampled_expected_count</strong>)</p><ul><li><strong>sampled_candidates</strong>: A vector of length num_sampled, in which each element is
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|
the ID of a sampled candidate.</li><li><strong>true_expected_count</strong>: A batch_size * num_true matrix, representing
|
|
the number of times each candidate is expected to occur in a batch
|
|
of sampled candidates. If unique=true, then this is a probability.</li><li><strong>sampled_expected_count</strong>: A vector of length num_sampled, for each sampled
|
|
candidate representing the number of times the candidate is expected
|
|
to occur in a batch of sampled candidates. If unique=true, then this is a
|
|
probability.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tile" class="def">tile</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tmultiples)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 1-D or higher.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tmultiples</td><td class="doc"><p><strong>multiples</strong>: 1-D. Length must be the same as the number of dimensions in <code>input</code></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Constructs a tensor by tiling a given tensor.</p><p>This operation creates a new tensor by replicating <code>input</code> <code>multiples</code> times.
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The output tensor's i'th dimension has `input.dims(i) * multiples[i]` elements,
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and the values of <code>input</code> are replicated `multiples[i]` times along the <code>i</code>th
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dimension. For example, tiling `[a b c d]` by `[2]` produces
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`[a b c d a b c d]`.</p></div></div><div class="top"><p class="src"><a name="v:tile-39-" class="def">tile'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tmultiples)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 1-D or higher.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tmultiples</td><td class="doc"><p><strong>multiples</strong>: 1-D. Length must be the same as the number of dimensions in <code>input</code></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:tileGrad" class="def">tileGrad</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>multiples</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Returns the gradient of <code>Tile</code>.</p><p>Since <code>Tile</code> takes an input and repeats the input <code>multiples</code> times
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along each dimension, <code>TileGrad</code> takes in <code>multiples</code> and aggregates
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each repeated tile of <code>input</code> into <code>output</code>.</p></div></div><div class="top"><p class="src"><a name="v:tileGrad-39-" class="def">tileGrad'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>multiples</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:topK" class="def">topK</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>k</strong>: Number of top elements to look for along the last dimension (along each
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row for matrices).</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 1-D or higher with last dimension at least <code>k</code>.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p>(<strong>values</strong>, <strong>indices</strong>)</p><ul><li><strong>values</strong>: The <code>k</code> largest elements along each last dimensional slice.</li><li><strong>indices</strong>: The indices of <code>values</code> within the last dimension of <code>input</code>.</li></ul></td></tr></table></div><div class="doc"><p>Finds values and indices of the <code>k</code> largest elements for the last dimension.</p><p>If the input is a vector (rank-1), finds the <code>k</code> largest entries in the vector
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and outputs their values and indices as vectors. Thus `values[j]` is the
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<code>j</code>-th largest entry in <code>input</code>, and its index is `indices[j]`.</p><p>For matrices (resp. higher rank input), computes the top <code>k</code> entries in each
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row (resp. vector along the last dimension). Thus,</p><p>values.shape = indices.shape = input.shape[:-1] + [k]</p><p>If two elements are equal, the lower-index element appears first.</p><p>If <code>k</code> varies dynamically, use <code>TopKV2</code> below.</p></div></div><div class="top"><p class="src"><a name="v:topK-39-" class="def">topK'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>k</strong>: Number of top elements to look for along the last dimension (along each
|
|
row for matrices).</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 1-D or higher with last dimension at least <code>k</code>.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p>(<strong>values</strong>, <strong>indices</strong>)</p><ul><li><strong>values</strong>: The <code>k</code> largest elements along each last dimensional slice.</li><li><strong>indices</strong>: The indices of <code>values</code> within the last dimension of <code>input</code>.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:topKV2" class="def">topKV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 1-D or higher with last dimension at least <code>k</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>k</strong>: 0-D. Number of top elements to look for along the last dimension (along each
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|
row for matrices).</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p>(<strong>values</strong>, <strong>indices</strong>)</p><ul><li><strong>values</strong>: The <code>k</code> largest elements along each last dimensional slice.</li><li><strong>indices</strong>: The indices of <code>values</code> within the last dimension of <code>input</code>.</li></ul></td></tr></table></div><div class="doc"><p>Finds values and indices of the <code>k</code> largest elements for the last dimension.</p><p>If the input is a vector (rank-1), finds the <code>k</code> largest entries in the vector
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and outputs their values and indices as vectors. Thus `values[j]` is the
|
|
<code>j</code>-th largest entry in <code>input</code>, and its index is `indices[j]`.</p><p>For matrices (resp. higher rank input), computes the top <code>k</code> entries in each
|
|
row (resp. vector along the last dimension). Thus,</p><p>values.shape = indices.shape = input.shape[:-1] + [k]</p><p>If two elements are equal, the lower-index element appears first.</p></div></div><div class="top"><p class="src"><a name="v:topKV2-39-" class="def">topKV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: 1-D or higher with last dimension at least <code>k</code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>k</strong>: 0-D. Number of top elements to look for along the last dimension (along each
|
|
row for matrices).</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>)</td><td class="doc"><p>(<strong>values</strong>, <strong>indices</strong>)</p><ul><li><strong>values</strong>: The <code>k</code> largest elements along each last dimensional slice.</li><li><strong>indices</strong>: The indices of <code>values</code> within the last dimension of <code>input</code>.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:transpose" class="def">transpose</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tperm)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tperm</td><td class="doc"><p><strong>perm</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Shuffle dimensions of x according to a permutation.</p><p>The output <code>y</code> has the same rank as <code>x</code>. The shapes of <code>x</code> and <code>y</code> satisfy:
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`y.shape[i] == x.shape[perm[i]] for i in [0, 1, ..., rank(x) - 1]`</p></div></div><div class="top"><p class="src"><a name="v:transpose-39-" class="def">transpose'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tperm)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tperm</td><td class="doc"><p><strong>perm</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:truncateDiv" class="def">truncateDiv</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns x / y element-wise for integer types.</p><p>Truncation designates that negative numbers will round fractional quantities
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toward zero. I.e. -7 / 5 = 1. This matches C semantics but it is different
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|
than Python semantics. See <code>FloorDiv</code> for a division function that matches
|
|
Python Semantics.</p><ul><li>NOTE*: <code>TruncateDiv</code> supports broadcasting. More about broadcasting
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|
<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:truncateDiv-39-" class="def">truncateDiv'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:truncateMod" class="def">truncateMod</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Returns element-wise remainder of division. This emulates C semantics where</p><p>true, this follows C semantics in that the result here is consistent
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|
with a flooring divide. E.g. `floor(x / y) * y + mod(x, y) = x`.</p><ul><li>NOTE*: <code>Mod</code> supports broadcasting. More about broadcasting
|
|
<a href="http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html">here</a></li></ul></div></div><div class="top"><p class="src"><a name="v:truncateMod-39-" class="def">truncateMod'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>y</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:truncatedNormal" class="def">truncatedNormal</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>shape</strong>: The shape of the output tensor.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>output</strong>: A tensor of the specified shape filled with random truncated normal
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|
values.</p></td></tr></table></div><div class="doc"><p>Outputs random values from a truncated normal distribution.</p><p>The generated values follow a normal distribution with mean 0 and standard
|
|
deviation 1, except that values whose magnitude is more than 2 standard
|
|
deviations from the mean are dropped and re-picked.</p></div></div><div class="top"><p class="src"><a name="v:truncatedNormal-39-" class="def">truncatedNormal'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` dtype, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>shape</strong>: The shape of the output tensor.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>output</strong>: A tensor of the specified shape filled with random truncated normal
|
|
values.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:uniformCandidateSampler" class="def">uniformCandidateSampler</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_sampled</strong>: Number of candidates to randomly sample per batch.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_true</strong>: Number of true labels per context.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>range_max</strong>: The sampler will sample integers from the interval [0, range_max).</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>unique</strong>: If unique is true, we sample with rejection, so that all sampled
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|
candidates in a batch are unique. This requires some approximation to
|
|
estimate the post-rejection sampling probabilities.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>true_classes</strong>: A batch_size * num_true matrix, in which each row contains the
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|
IDs of the num_true target_classes in the corresponding original label.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>sampled_candidates</strong>, <strong>true_expected_count</strong>, <strong>sampled_expected_count</strong>)</p><ul><li><strong>sampled_candidates</strong>: A vector of length num_sampled, in which each element is
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|
the ID of a sampled candidate.</li><li><strong>true_expected_count</strong>: A batch_size * num_true matrix, representing
|
|
the number of times each candidate is expected to occur in a batch
|
|
of sampled candidates. If unique=true, then this is a probability.</li><li><strong>sampled_expected_count</strong>: A vector of length num_sampled, for each sampled
|
|
candidate representing the number of times the candidate is expected
|
|
to occur in a batch of sampled candidates. If unique=true, then this is a
|
|
probability.</li></ul></td></tr></table></div><div class="doc"><p>Generates labels for candidate sampling with a uniform distribution.</p><p>See explanations of candidate sampling and the data formats at
|
|
go/candidate-sampling.</p><p>For each batch, this op picks a single set of sampled candidate labels.</p><p>The advantages of sampling candidates per-batch are simplicity and the
|
|
possibility of efficient dense matrix multiplication. The disadvantage is that
|
|
the sampled candidates must be chosen independently of the context and of the
|
|
true labels.</p></div></div><div class="top"><p class="src"><a name="v:uniformCandidateSampler-39-" class="def">uniformCandidateSampler'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_sampled</strong>: Number of candidates to randomly sample per batch.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num_true</strong>: Number of true labels per context.</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>range_max</strong>: The sampler will sample integers from the interval [0, range_max).</p></td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>unique</strong>: If unique is true, we sample with rejection, so that all sampled
|
|
candidates in a batch are unique. This requires some approximation to
|
|
estimate the post-rejection sampling probabilities.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>true_classes</strong>: A batch_size * num_true matrix, in which each row contains the
|
|
IDs of the num_true target_classes in the corresponding original label.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>)</td><td class="doc"><p>(<strong>sampled_candidates</strong>, <strong>true_expected_count</strong>, <strong>sampled_expected_count</strong>)</p><ul><li><strong>sampled_candidates</strong>: A vector of length num_sampled, in which each element is
|
|
the ID of a sampled candidate.</li><li><strong>true_expected_count</strong>: A batch_size * num_true matrix, representing
|
|
the number of times each candidate is expected to occur in a batch
|
|
of sampled candidates. If unique=true, then this is a probability.</li><li><strong>sampled_expected_count</strong>: A vector of length num_sampled, for each sampled
|
|
candidate representing the number of times the candidate is expected
|
|
to occur in a batch of sampled candidates. If unique=true, then this is a
|
|
probability.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:unique" class="def">unique</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_idx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong>: 1-D.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_idx)</td><td class="doc"><p>(<strong>y</strong>, <strong>idx</strong>)</p><ul><li><strong>y</strong>: 1-D.</li><li><strong>idx</strong>: 1-D.</li></ul></td></tr></table></div><div class="doc"><p>Finds unique elements in a 1-D tensor.</p><p>This operation returns a tensor <code>y</code> containing all of the unique elements of <code>x</code>
|
|
sorted in the same order that they occur in <code>x</code>. This operation also returns a
|
|
tensor <code>idx</code> the same size as <code>x</code> that contains the index of each value of <code>x</code>
|
|
in the unique output <code>y</code>. In other words:</p><p>`y[idx[i]] = x[i] for i in [0, 1,...,rank(x) - 1]`</p><p>For example:</p><p>```prettyprint
|
|
# tensor <code>x</code> is [1, 1, 2, 4, 4, 4, 7, 8, 8]
|
|
y, idx = unique(x)
|
|
y ==> [1, 2, 4, 7, 8]
|
|
idx ==> [0, 0, 1, 2, 2, 2, 3, 4, 4]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:unique-39-" class="def">unique'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_idx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong>: 1-D.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_idx)</td><td class="doc"><p>(<strong>y</strong>, <strong>idx</strong>)</p><ul><li><strong>y</strong>: 1-D.</li><li><strong>idx</strong>: 1-D.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:uniqueWithCounts" class="def">uniqueWithCounts</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_idx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong>: 1-D.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_idx, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_idx)</td><td class="doc"><p>(<strong>y</strong>, <strong>idx</strong>, <strong>count</strong>)</p><ul><li><strong>y</strong>: 1-D.</li><li><strong>idx</strong>: 1-D.</li><li><strong>count</strong>: 1-D.</li></ul></td></tr></table></div><div class="doc"><p>Finds unique elements in a 1-D tensor.</p><p>This operation returns a tensor <code>y</code> containing all of the unique elements of <code>x</code>
|
|
sorted in the same order that they occur in <code>x</code>. This operation also returns a
|
|
tensor <code>idx</code> the same size as <code>x</code> that contains the index of each value of <code>x</code>
|
|
in the unique output <code>y</code>. Finally, it returns a third tensor <code>count</code> that
|
|
contains the count of each element of <code>y</code> in <code>x</code>. In other words:</p><p>`y[idx[i]] = x[i] for i in [0, 1,...,rank(x) - 1]`</p><p>For example:</p><p>```prettyprint
|
|
# tensor <code>x</code> is [1, 1, 2, 4, 4, 4, 7, 8, 8]
|
|
y, idx, count = unique_with_counts(x)
|
|
y ==> [1, 2, 4, 7, 8]
|
|
idx ==> [0, 0, 1, 2, 2, 2, 3, 4, 4]
|
|
count ==> [2, 1, 3, 1, 2]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:uniqueWithCounts-39-" class="def">uniqueWithCounts'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` out_idx)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong>: 1-D.</p></td></tr><tr><td class="src">-> (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_idx, <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_idx)</td><td class="doc"><p>(<strong>y</strong>, <strong>idx</strong>, <strong>count</strong>)</p><ul><li><strong>y</strong>: 1-D.</li><li><strong>idx</strong>: 1-D.</li><li><strong>count</strong>: 1-D.</li></ul></td></tr></table></div></div><div class="top"><p class="src"><a name="v:unpack" class="def">unpack</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: 1-D or higher, with <code>axis</code> dimension size equal to <code>num</code>.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</td><td class="doc"><p><strong>output</strong>: The list of tensors unpacked from <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>.</p></td></tr></table></div><div class="doc"><p>Unpacks a given dimension of a rank-<code>R</code> tensor into <code>num</code> rank-`(R-1)` tensors.</p><p>Unpacks <code>num</code> tensors from <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> by chipping it along the <code>axis</code> dimension.
|
|
For example, given a tensor of shape `(A, B, C, D)`;</p><p>If `axis == 0` then the i'th tensor in <code>output</code> is the slice `value[i, :, :, :]`
|
|
and each tensor in <code>output</code> will have shape `(B, C, D)`. (Note that the
|
|
dimension unpacked along is gone, unlike <code><a href="TensorFlow-GenOps-Core.html#v:split">split</a></code>).</p><p>If `axis == 1` then the i'th tensor in <code>output</code> is the slice `value[:, i, :, :]`
|
|
and each tensor in <code>output</code> will have shape `(A, C, D)`.
|
|
Etc.</p><p>This is the opposite of <code><a href="TensorFlow-GenOps-Core.html#v:pack">pack</a></code>.</p></div></div><div class="top"><p class="src"><a name="v:unpack-39-" class="def">unpack'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>num</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: 1-D or higher, with <code>axis</code> dimension size equal to <code>num</code>.</p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</td><td class="doc"><p><strong>output</strong>: The list of tensors unpacked from <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:unsortedSegmentSum" class="def">unsortedSegmentSum</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>segment_ids</strong>: A tensor whose shape is a prefix of `data.shape`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>num_segments</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Has same shape as data, except for the first `segment_ids.rank`
|
|
dimensions, which are replaced with a single dimension which has size
|
|
<code>num_segments</code>.</p></td></tr></table></div><div class="doc"><p>Computes the sum along segments of a tensor.</p><p>Read <a href="../../api_docs/python/math_ops.md#segmentation">the section on
|
|
Segmentation</a> for an explanation
|
|
of segments.</p><p>Computes a tensor such that
|
|
`(output[i] = sum_{j...} data[j...]` where the sum is over tuples `j...` such
|
|
that `segment_ids[j...] == i`. Unlike <code>SegmentSum</code>, <code>segment_ids</code>
|
|
need not be sorted and need not cover all values in the full
|
|
range of valid values.</p><p>If the sum is empty for a given segment ID <code>i</code>, `output[i] = 0`.</p><p><code>num_segments</code> should equal the number of distinct segment IDs.</p><p><a href="div">style="width:70%; margin:auto; margin-bottom:10px; margin-top:20px;"</a>
|
|
<a href="img">style="width:100%" src="../../images/UnsortedSegmentSum.png" alt</a>
|
|
<a href="/div">/div</a></p></div></div><div class="top"><p class="src"><a name="v:unsortedSegmentSum-39-" class="def">unsortedSegmentSum'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Data-Complex.html#t:Complex">Complex</a> <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int16">Int16</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int8">Int8</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word16">Word16</a>, <a href="../base-4.8.2.0/Data-Word.html#t:Word8">Word8</a>, <a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a>, <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a>]` tindices)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>data</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 tindices</td><td class="doc"><p><strong>segment_ids</strong>: A tensor whose shape is a prefix of `data.shape`.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'3 <a href="../base-4.8.2.0/Data-Int.html#t:Int32">Int32</a></td><td class="doc"><p><strong>num_segments</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: Has same shape as data, except for the first `segment_ids.rank`
|
|
dimensions, which are replaced with a single dimension which has size
|
|
<code>num_segments</code>.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:unstage" class="def">unstage</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> dtypes)</td><td class="doc empty"> </td></tr><tr><td class="src">=> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtypes)</td><td class="doc"><p><strong>values</strong></p></td></tr></table></div><div class="doc"><p>Op is similar to a lightweight Dequeue. The basic funtionality is similar to</p><p>dequeue with many fewer capabilities and options. This Op is optimized for
|
|
performance.</p></div></div><div class="top"><p class="src"><a name="v:unstage-39-" class="def">unstage'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> dtypes)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtypes)</td><td class="doc"><p><strong>values</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:varHandleOp" class="def">varHandleOp</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>dtype</strong>: the type of this variable. Must agree with the dtypes
|
|
of all ops using this variable.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: The (possibly partially specified) shape of this variable.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>resource</strong></p></td></tr></table></div><div class="doc"><p>Creates a handle to a Variable resource.</p></div></div><div class="top"><p class="src"><a name="v:varHandleOp-39-" class="def">varHandleOp'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:DataType">DataType</a></td><td class="doc"><p><strong>dtype</strong>: the type of this variable. Must agree with the dtypes
|
|
of all ops using this variable.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: The (possibly partially specified) shape of this variable.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>resource</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:varIsInitializedOp" class="def">varIsInitializedOp</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>resource</strong>: the input resource handle.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>)</td><td class="doc"><p><strong>is_initialized</strong>: a scalar boolean which is true if the variable has been
|
|
initialized.</p></td></tr></table></div><div class="doc"><p>Checks whether a resource handle-based variable has been initialized.</p></div></div><div class="top"><p class="src"><a name="v:varIsInitializedOp-39-" class="def">varIsInitializedOp'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>resource</strong>: the input resource handle.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a>)</td><td class="doc"><p><strong>is_initialized</strong>: a scalar boolean which is true if the variable has been
|
|
initialized.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:variable" class="def">variable</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> dtype)</td><td class="doc"><p><strong>ref</strong></p></td></tr></table></div><div class="doc"><p>Use VariableV2 instead.</p></div></div><div class="top"><p class="src"><a name="v:variable-39-" class="def">variable'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong></p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> dtype)</td><td class="doc"><p><strong>ref</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:variableV2" class="def">variableV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: The shape of the variable tensor.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> dtype)</td><td class="doc"><p><strong>ref</strong>: A reference to the variable tensor.</p></td></tr></table></div><div class="doc"><p>Holds state in the form of a tensor that persists across steps.</p><p>Outputs a ref to the tensor state so it may be read or modified.
|
|
TODO(zhifengc/mrry): Adds a pointer to a more detail document
|
|
about sharing states in tensorflow.</p></div></div><div class="top"><p class="src"><a name="v:variableV2-39-" class="def">variableV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: The shape of the variable tensor.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> dtype)</td><td class="doc"><p><strong>ref</strong>: A reference to the variable tensor.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:where-39-" class="def">where'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>index</strong></p></td></tr></table></div><div class="doc"><p>Returns locations of true values in a boolean tensor.</p><p>This operation returns the coordinates of true elements in <code>input</code>. The
|
|
coordinates are returned in a 2-D tensor where the first dimension (rows)
|
|
represents the number of true elements, and the second dimension (columns)
|
|
represents the coordinates of the true elements. Keep in mind, the shape of
|
|
the output tensor can vary depending on how many true values there are in
|
|
<code>input</code>. Indices are output in row-major order.</p><p>For example:</p><p>```prettyprint
|
|
# <code>input</code> tensor is [[True, False]
|
|
# [True, False]]
|
|
# <code>input</code> has two true values, so output has two coordinates.
|
|
# <code>input</code> has rank of 2, so coordinates have two indices.
|
|
where(input) ==> [[0, 0],
|
|
[1, 0]]</p><p># <code>input</code> tensor is [[[True, False]
|
|
# [True, False]]
|
|
# [[False, True]
|
|
# [False, True]]
|
|
# [[False, False]
|
|
# [False, True]]]
|
|
# <code>input</code> has 5 true values, so output has 5 coordinates.
|
|
# <code>input</code> has rank of 3, so coordinates have three indices.
|
|
where(input) ==> [[0, 0, 0],
|
|
[0, 1, 0],
|
|
[1, 0, 1],
|
|
[1, 1, 1],
|
|
[2, 1, 1]]
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:where-39--39-" class="def">where''</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../base-4.8.2.0/Data-Bool.html#t:Bool">Bool</a></td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>index</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:wholeFileReader" class="def">wholeFileReader</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div><div class="doc"><p>A Reader that outputs the entire contents of a file as a value.</p><p>To use, enqueue filenames in a Queue. The output of ReaderRead will
|
|
be a filename (key) and the contents of that file (value).</p></div></div><div class="top"><p class="src"><a name="v:wholeFileReader-39-" class="def">wholeFileReader'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Ref">Ref</a> <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a>)</td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:wholeFileReaderV2" class="def">wholeFileReaderV2</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div><div class="doc"><p>A Reader that outputs the entire contents of a file as a value.</p><p>To use, enqueue filenames in a Queue. The output of ReaderRead will
|
|
be a filename (key) and the contents of that file (value).</p></div></div><div class="top"><p class="src"><a name="v:wholeFileReaderV2-39-" class="def">wholeFileReaderV2'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ResourceHandle">ResourceHandle</a></td><td class="doc"><p><strong>reader_handle</strong>: The handle to reference the Reader.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:writeFile" class="def">writeFile</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>filename</strong>: scalar. The name of the file to which we write the contents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>contents</strong>: scalar. The content to be written to the output file.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Writes contents to the file at input filename. Creates file if not existing.</p></div></div><div class="top"><p class="src"><a name="v:writeFile-39-" class="def">writeFile'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m'</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>filename</strong>: scalar. The name of the file to which we write the contents.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 <a href="../bytestring-0.10.6.0/Data-ByteString.html#t:ByteString">ByteString</a></td><td class="doc"><p><strong>contents</strong>: scalar. The content to be written to the output file.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:zerosLike" class="def">zerosLike</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong>: a tensor of type T.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong>: a tensor of the same shape and type as x but filled with zeros.</p></td></tr></table></div><div class="doc"><p>Returns a tensor of zeros with the same shape and type as x.</p></div></div><div class="top"><p class="src"><a name="v:zerosLike-39-" class="def">zerosLike'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong>: a tensor of type T.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>y</strong>: a tensor of the same shape and type as x but filled with zeros.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:zeta" class="def">zeta</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>q</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div><div class="doc"><p>Compute the Hurwitz zeta function \(zeta(x, q)\).</p><p>The Hurwitz zeta function is defined as:</p><p>```
|
|
zeta(x, q) = sum_{n=0}^{infty} (q + n)^{-x}
|
|
```</p></div></div><div class="top"><p class="src"><a name="v:zeta-39-" class="def">zeta'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:OneOf">OneOf</a> `[<a href="../base-4.8.2.0/Prelude.html#t:Double">Double</a>, <a href="../base-4.8.2.0/Prelude.html#t:Float">Float</a>]` t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>q</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>z</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:_Arg" class="def">_Arg</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>index</strong>: This argument is the index-th argument of the function.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</td><td class="doc"><p><strong>output</strong>: The argument.</p></td></tr></table></div><div class="doc"><p>A graph node which represents an argument to a function.</p></div></div><div class="top"><p class="src"><a name="v:_Arg-39-" class="def">_Arg'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>index</strong>: This argument is the index-th argument of the function.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> t)</td><td class="doc"><p><strong>output</strong>: The argument.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:_ArrayToList" class="def">_ArrayToList</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> out_types)</td><td class="doc empty"> </td></tr><tr><td class="src">=> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t]</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_types</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Converts an array of tensors to a list of tensors.</p></div></div><div class="top"><p class="src"><a name="v:_ArrayToList-39-" class="def">_ArrayToList'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> out_types)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t]</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> out_types</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:_HostCast" class="def">_HostCast</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> srcT, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dstT)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 srcT</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dstT</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div><div class="doc"><p>Cast x of type SrcT to y of DstT.</p><p>_HostCast requires its input and produces its output in host memory.</p></div></div><div class="top"><p class="src"><a name="v:_HostCast-39-" class="def">_HostCast'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> srcT, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dstT)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 srcT</td><td class="doc"><p><strong>x</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> dstT</td><td class="doc"><p><strong>y</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:_HostRecv" class="def">_HostRecv</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tensor_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>send_device_incarnation</strong>: The current incarnation of send_device.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tensor_type)</td><td class="doc"><p><strong>tensor</strong>: The tensor to receive.</p></td></tr></table></div><div class="doc"><p>Receives the named tensor from send_device on recv_device.</p><p>_HostRecv requires its input on host memory whereas _Recv requires its
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input on device memory.</p></div></div><div class="top"><p class="src"><a name="v:_HostRecv-39-" class="def">_HostRecv'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tensor_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>send_device_incarnation</strong>: The current incarnation of send_device.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tensor_type)</td><td class="doc"><p><strong>tensor</strong>: The tensor to receive.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:_HostSend" class="def">_HostSend</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>send_device_incarnation</strong>: The current incarnation of send_device.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>tensor</strong>: The tensor to send.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Sends the named tensor from send_device to recv_device.</p><p>_HostSend requires its input on host memory whereas _Send requires its
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input on device memory.</p></div></div><div class="top"><p class="src"><a name="v:_HostSend-39-" class="def">_HostSend'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>send_device_incarnation</strong>: The current incarnation of send_device.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>tensor</strong>: The tensor to send.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:_ListToArray" class="def">_ListToArray</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tin, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>N</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'1 tin</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div><div class="doc"><p>Converts a list of tensors to an array of tensors.</p></div></div><div class="top"><p class="src"><a name="v:_ListToArray-39-" class="def">_ListToArray'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorTypes">TensorTypes</a> tin, <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>N</strong></p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:TensorList">TensorList</a> v'1 tin</td><td class="doc"><p><strong>input</strong></p></td></tr><tr><td class="src">-> [<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t]</td><td class="doc"><p><strong>output</strong></p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:_ParallelConcatStart" class="def">_ParallelConcatStart</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: 1-D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> indicating the shape of the output.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>output</strong>: An empty Tensor of the specified type.</p></td></tr></table></div><div class="doc"><p>Creates an empty Tensor with shape <code><a href="TensorFlow-GenOps-Core.html#v:shape">shape</a></code> and type <code>dtype</code>.</p><p>The memory can optionally be initialized. This is usually useful in
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conjunction with inplace operations.</p></div></div><div class="top"><p class="src"><a name="v:_ParallelConcatStart-39-" class="def">_ParallelConcatStart'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> dtype)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:Shape">Shape</a></td><td class="doc"><p><strong>shape</strong>: 1-D <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> indicating the shape of the output.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> dtype)</td><td class="doc"><p><strong>output</strong>: An empty Tensor of the specified type.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:_ParallelConcatUpdate" class="def">_ParallelConcatUpdate</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>loc</strong>: A scalar indicating the index of the first dimension such that
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value[loc, :] is updated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: A <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> object that will be updated in-place.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>update</strong>: A <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> of rank one less than <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> if <code>loc</code> is a scalar,
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otherwise of rank equal to <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> that contains the new values
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for <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> that has been updated accordingly.</p></td></tr></table></div><div class="doc"><p>Updates input <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> at <code>loc</code> with <code>update</code>.</p><p>If you use this function you will almost certainly want to add
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a control dependency as done in the implementation of parallel_stack to
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avoid race conditions.</p></div></div><div class="top"><p class="src"><a name="v:_ParallelConcatUpdate-39-" class="def">_ParallelConcatUpdate'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>loc</strong>: A scalar indicating the index of the first dimension such that
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value[loc, :] is updated.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>value</strong>: A <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> object that will be updated in-place.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'2 t</td><td class="doc"><p><strong>update</strong>: A <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a></code> of rank one less than <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> if <code>loc</code> is a scalar,
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otherwise of rank equal to <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> that contains the new values
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for <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code>.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:Build">Build</a> t</td><td class="doc"><p><strong>output</strong>: <code><a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#v:value">value</a></code> that has been updated accordingly.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:_Recv" class="def">_Recv</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tensor_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>send_device_incarnation</strong>: The current incarnation of send_device.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tensor_type)</td><td class="doc"><p><strong>tensor</strong>: The tensor to receive.</p></td></tr></table></div><div class="doc"><p>Receives the named tensor from send_device on recv_device.</p></div></div><div class="top"><p class="src"><a name="v:_Recv-39-" class="def">_Recv'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> tensor_type)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>send_device_incarnation</strong>: The current incarnation of send_device.</p></td></tr><tr><td class="src">-> m' (<a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Value">Value</a> tensor_type)</td><td class="doc"><p><strong>tensor</strong>: The tensor to receive.</p></td></tr></table></div></div><div class="top"><p class="src"><a name="v:_Retval" class="def">_Retval</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>index</strong>: This return value is the index-th return value of the function.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The return value.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>A graph node which represents a return value of a function.</p></div></div><div class="top"><p class="src"><a name="v:_Retval-39-" class="def">_Retval'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>index</strong>: This return value is the index-th return value of the function.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>input</strong>: The return value.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div><div class="top"><p class="src"><a name="v:_Send" class="def">_Send</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>send_device_incarnation</strong>: The current incarnation of send_device.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>tensor</strong>: The tensor to send.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div><div class="doc"><p>Sends the named tensor from send_device to recv_device.</p></div></div><div class="top"><p class="src"><a name="v:_Send-39-" class="def">_Send'</a></p><div class="subs arguments"><p class="caption">Arguments</p><table><tr><td class="src">:: (<a href="../tensorflow-0.1.0.0/TensorFlow-Build.html#t:MonadBuild">MonadBuild</a> m', <a href="../tensorflow-0.1.0.0/TensorFlow-Types.html#t:TensorType">TensorType</a> t)</td><td class="doc empty"> </td></tr><tr><td class="src">=> <a href="../tensorflow-0.1.0.0/TensorFlow-BuildOp.html#t:OpParams">OpParams</a></td><td class="doc empty"> </td></tr><tr><td class="src">-> <a href="../base-4.8.2.0/Data-Int.html#t:Int64">Int64</a></td><td class="doc"><p><strong>send_device_incarnation</strong>: The current incarnation of send_device.</p></td></tr><tr><td class="src">-> <a href="../tensorflow-0.1.0.0/TensorFlow-Tensor.html#t:Tensor">Tensor</a> v'1 t</td><td class="doc"><p><strong>tensor</strong>: The tensor to send.</p></td></tr><tr><td class="src">-> m' <a href="../tensorflow-0.1.0.0/TensorFlow-Output.html#t:ControlNode">ControlNode</a></td><td class="doc empty"> </td></tr></table></div></div></div></div><div id="footer"><p>Produced by <a href="http://www.haskell.org/haddock/">Haddock</a> 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