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<title>src/TensorFlow/Tensor.hs</title>
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<pre><a name="line-1"></a><span class='hs-comment'>-- Copyright 2016 TensorFlow authors.</span>
<a name="line-2"></a><span class='hs-comment'>--</span>
<a name="line-3"></a><span class='hs-comment'>-- Licensed under the Apache License, Version 2.0 (the "License");</span>
<a name="line-4"></a><span class='hs-comment'>-- you may not use this file except in compliance with the License.</span>
<a name="line-5"></a><span class='hs-comment'>-- You may obtain a copy of the License at</span>
<a name="line-6"></a><span class='hs-comment'>--</span>
<a name="line-7"></a><span class='hs-comment'>-- <a href="http://www.apache.org/licenses/LICENSE-2.0">http://www.apache.org/licenses/LICENSE-2.0</a></span>
<a name="line-8"></a><span class='hs-comment'>--</span>
<a name="line-9"></a><span class='hs-comment'>-- Unless required by applicable law or agreed to in writing, software</span>
<a name="line-10"></a><span class='hs-comment'>-- distributed under the License is distributed on an "AS IS" BASIS,</span>
<a name="line-11"></a><span class='hs-comment'>-- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.</span>
<a name="line-12"></a><span class='hs-comment'>-- See the License for the specific language governing permissions and</span>
<a name="line-13"></a><span class='hs-comment'>-- limitations under the License.</span>
<a name="line-14"></a>
<a name="line-15"></a><span class='hs-comment'>{-# LANGUAGE FlexibleInstances #-}</span>
<a name="line-16"></a><span class='hs-comment'>{-# LANGUAGE GADTs #-}</span>
<a name="line-17"></a><span class='hs-comment'>{-# LANGUAGE OverloadedStrings #-}</span>
<a name="line-18"></a><span class='hs-comment'>{-# LANGUAGE Rank2Types #-}</span>
<a name="line-19"></a>
<a name="line-20"></a><span class='hs-keyword'>module</span> <span class='hs-conid'>TensorFlow</span><span class='hs-varop'>.</span><span class='hs-conid'>Tensor</span> <span class='hs-keyword'>where</span>
<a name="line-21"></a>
<a name="line-22"></a><span class='hs-keyword'>import</span> <span class='hs-conid'>Data</span><span class='hs-varop'>.</span><span class='hs-conid'>String</span> <span class='hs-layout'>(</span><span class='hs-conid'>IsString</span><span class='hs-layout'>(</span><span class='hs-keyglyph'>..</span><span class='hs-layout'>)</span><span class='hs-layout'>)</span>
<a name="line-23"></a><span class='hs-keyword'>import</span> <span class='hs-keyword'>qualified</span> <span class='hs-conid'>Data</span><span class='hs-varop'>.</span><span class='hs-conid'>Text</span> <span class='hs-keyword'>as</span> <span class='hs-conid'>Text</span>
<a name="line-24"></a><span class='hs-keyword'>import</span> <span class='hs-conid'>Lens</span><span class='hs-varop'>.</span><span class='hs-conid'>Family2</span> <span class='hs-layout'>(</span><span class='hs-conid'>Lens'</span><span class='hs-layout'>,</span> <span class='hs-conid'>Traversal'</span><span class='hs-layout'>)</span>
<a name="line-25"></a><span class='hs-keyword'>import</span> <span class='hs-conid'>Lens</span><span class='hs-varop'>.</span><span class='hs-conid'>Family2</span><span class='hs-varop'>.</span><span class='hs-conid'>Unchecked</span> <span class='hs-layout'>(</span><span class='hs-varid'>lens</span><span class='hs-layout'>)</span>
<a name="line-26"></a>
<a name="line-27"></a><span class='hs-keyword'>import</span> <span class='hs-conid'>TensorFlow</span><span class='hs-varop'>.</span><span class='hs-conid'>Output</span> <span class='hs-layout'>(</span><span class='hs-conid'>Output</span><span class='hs-layout'>,</span> <span class='hs-varid'>outputOp</span><span class='hs-layout'>,</span> <span class='hs-varid'>opUnrendered</span><span class='hs-layout'>,</span> <span class='hs-varid'>opAttr</span><span class='hs-layout'>)</span>
<a name="line-28"></a><span class='hs-keyword'>import</span> <span class='hs-conid'>TensorFlow</span><span class='hs-varop'>.</span><span class='hs-conid'>Types</span> <span class='hs-layout'>(</span><span class='hs-conid'>TensorData</span><span class='hs-layout'>(</span><span class='hs-keyglyph'>..</span><span class='hs-layout'>)</span><span class='hs-layout'>,</span> <span class='hs-conid'>Attribute</span><span class='hs-layout'>)</span>
<a name="line-29"></a><span class='hs-keyword'>import</span> <span class='hs-keyword'>qualified</span> <span class='hs-conid'>TensorFlow</span><span class='hs-varop'>.</span><span class='hs-conid'>Internal</span><span class='hs-varop'>.</span><span class='hs-conid'>FFI</span> <span class='hs-keyword'>as</span> <span class='hs-conid'>FFI</span>
<a name="line-30"></a>
<a name="line-31"></a><a name="Tensor"></a><span class='hs-comment'>-- | A named output of a TensorFlow operation.</span>
<a name="line-32"></a><a name="Tensor"></a><span class='hs-comment'>--</span>
<a name="line-33"></a><a name="Tensor"></a><span class='hs-comment'>-- The type parameter @a@ is the type of the elements in the 'Tensor'. The</span>
<a name="line-34"></a><a name="Tensor"></a><span class='hs-comment'>-- parameter @v@ is either 'Value' or 'Ref', depending on whether the graph is</span>
<a name="line-35"></a><a name="Tensor"></a><span class='hs-comment'>-- treating this op output as an immutable 'Value' or a stateful 'Ref' (e.g., a</span>
<a name="line-36"></a><a name="Tensor"></a><span class='hs-comment'>-- variable). Note that a @Tensor Ref@ can be casted into a @Tensor Value@ via</span>
<a name="line-37"></a><a name="Tensor"></a><span class='hs-comment'>-- 'value'.</span>
<a name="line-38"></a><a name="Tensor"></a><span class='hs-keyword'>data</span> <span class='hs-conid'>Tensor</span> <span class='hs-varid'>v</span> <span class='hs-varid'>a</span> <span class='hs-keyglyph'>=</span> <span class='hs-conid'>Tensor</span> <span class='hs-layout'>(</span><span class='hs-conid'>TensorKind</span> <span class='hs-varid'>v</span><span class='hs-layout'>)</span> <span class='hs-conid'>Output</span>
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<a name="line-40"></a><a name="Value"></a><span class='hs-keyword'>data</span> <span class='hs-conid'>Value</span>
<a name="line-41"></a><a name="Ref"></a><span class='hs-keyword'>data</span> <span class='hs-conid'>Ref</span>
<a name="line-42"></a>
<a name="line-43"></a><a name="TensorKind"></a><span class='hs-comment'>-- | This class provides a runtime switch on whether a 'Tensor' should be</span>
<a name="line-44"></a><a name="TensorKind"></a><span class='hs-comment'>-- treated as a 'Value' or as a 'Ref'.</span>
<a name="line-45"></a><a name="TensorKind"></a><span class='hs-keyword'>data</span> <span class='hs-conid'>TensorKind</span> <span class='hs-varid'>v</span> <span class='hs-keyword'>where</span>
<a name="line-46"></a> <span class='hs-conid'>ValueKind</span> <span class='hs-keyglyph'>::</span> <span class='hs-conid'>TensorKind</span> <span class='hs-conid'>Value</span>
<a name="line-47"></a> <span class='hs-conid'>RefKind</span> <span class='hs-keyglyph'>::</span> <span class='hs-conid'>TensorKind</span> <span class='hs-conid'>Ref</span>
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<a name="line-49"></a><a name="tensorKind"></a><span class='hs-definition'>tensorKind</span> <span class='hs-keyglyph'>::</span> <span class='hs-conid'>Lens'</span> <span class='hs-layout'>(</span><span class='hs-conid'>Tensor</span> <span class='hs-varid'>v</span> <span class='hs-varid'>a</span><span class='hs-layout'>)</span> <span class='hs-layout'>(</span><span class='hs-conid'>TensorKind</span> <span class='hs-varid'>v</span><span class='hs-layout'>)</span>
<a name="line-50"></a><span class='hs-definition'>tensorKind</span> <span class='hs-keyglyph'>=</span> <span class='hs-varid'>lens</span> <span class='hs-layout'>(</span><span class='hs-keyglyph'>\</span><span class='hs-layout'>(</span><span class='hs-conid'>Tensor</span> <span class='hs-varid'>v</span> <span class='hs-keyword'>_</span><span class='hs-layout'>)</span> <span class='hs-keyglyph'>-></span> <span class='hs-varid'>v</span><span class='hs-layout'>)</span> <span class='hs-layout'>(</span><span class='hs-keyglyph'>\</span><span class='hs-layout'>(</span><span class='hs-conid'>Tensor</span> <span class='hs-keyword'>_</span> <span class='hs-varid'>o</span><span class='hs-layout'>)</span> <span class='hs-varid'>v</span> <span class='hs-keyglyph'>-></span> <span class='hs-conid'>Tensor</span> <span class='hs-varid'>v</span> <span class='hs-varid'>o</span><span class='hs-layout'>)</span>
<a name="line-51"></a>
<a name="line-52"></a><a name="tensorOutput"></a><span class='hs-definition'>tensorOutput</span> <span class='hs-keyglyph'>::</span> <span class='hs-conid'>Lens'</span> <span class='hs-layout'>(</span><span class='hs-conid'>Tensor</span> <span class='hs-varid'>v</span> <span class='hs-varid'>a</span><span class='hs-layout'>)</span> <span class='hs-conid'>Output</span>
<a name="line-53"></a><span class='hs-definition'>tensorOutput</span> <span class='hs-keyglyph'>=</span> <span class='hs-varid'>lens</span> <span class='hs-layout'>(</span><span class='hs-keyglyph'>\</span><span class='hs-layout'>(</span><span class='hs-conid'>Tensor</span> <span class='hs-keyword'>_</span> <span class='hs-varid'>o</span><span class='hs-layout'>)</span> <span class='hs-keyglyph'>-></span> <span class='hs-varid'>o</span><span class='hs-layout'>)</span> <span class='hs-layout'>(</span><span class='hs-keyglyph'>\</span><span class='hs-layout'>(</span><span class='hs-conid'>Tensor</span> <span class='hs-varid'>v</span> <span class='hs-keyword'>_</span><span class='hs-layout'>)</span> <span class='hs-varid'>o</span> <span class='hs-keyglyph'>-></span> <span class='hs-conid'>Tensor</span> <span class='hs-varid'>v</span> <span class='hs-varid'>o</span><span class='hs-layout'>)</span>
<a name="line-54"></a>
<a name="line-55"></a><a name="tensorAttr"></a><span class='hs-comment'>-- TODO: Come up with a better API for handling attributes.</span>
<a name="line-56"></a><span class='hs-comment'>-- | Lens for the attributes of a tensor.</span>
<a name="line-57"></a><span class='hs-comment'>--</span>
<a name="line-58"></a><span class='hs-comment'>-- Only valid if the tensor has not yet been rendered. If the tensor has been</span>
<a name="line-59"></a><span class='hs-comment'>-- rendered, the traversal will be over nothing (nothing can be read or</span>
<a name="line-60"></a><span class='hs-comment'>-- written).</span>
<a name="line-61"></a><span class='hs-definition'>tensorAttr</span> <span class='hs-keyglyph'>::</span> <span class='hs-conid'>Attribute</span> <span class='hs-varid'>attr</span> <span class='hs-keyglyph'>=></span> <span class='hs-conid'>Text</span><span class='hs-varop'>.</span><span class='hs-conid'>Text</span> <span class='hs-keyglyph'>-></span> <span class='hs-conid'>Traversal'</span> <span class='hs-layout'>(</span><span class='hs-conid'>Tensor</span> <span class='hs-varid'>v</span> <span class='hs-varid'>a</span><span class='hs-layout'>)</span> <span class='hs-varid'>attr</span>
<a name="line-62"></a><span class='hs-definition'>tensorAttr</span> <span class='hs-varid'>x</span> <span class='hs-keyglyph'>=</span> <span class='hs-varid'>tensorOutput</span> <span class='hs-varop'>.</span> <span class='hs-varid'>outputOp</span> <span class='hs-varop'>.</span> <span class='hs-varid'>opUnrendered</span> <span class='hs-varop'>.</span> <span class='hs-varid'>opAttr</span> <span class='hs-varid'>x</span>
<a name="line-63"></a>
<a name="line-64"></a><a name="value"></a><span class='hs-comment'>-- | Cast a 'Tensor *' into a 'Tensor Value'. Common usage is to cast a</span>
<a name="line-65"></a><span class='hs-comment'>-- Ref into Value. This behaves like a no-op.</span>
<a name="line-66"></a><span class='hs-definition'>value</span> <span class='hs-keyglyph'>::</span> <span class='hs-conid'>Tensor</span> <span class='hs-varid'>v</span> <span class='hs-varid'>a</span> <span class='hs-keyglyph'>-></span> <span class='hs-conid'>Tensor</span> <span class='hs-conid'>Value</span> <span class='hs-varid'>a</span>
<a name="line-67"></a><span class='hs-definition'>value</span> <span class='hs-layout'>(</span><span class='hs-conid'>Tensor</span> <span class='hs-keyword'>_</span> <span class='hs-varid'>o</span><span class='hs-layout'>)</span> <span class='hs-keyglyph'>=</span> <span class='hs-conid'>Tensor</span> <span class='hs-conid'>ValueKind</span> <span class='hs-varid'>o</span>
<a name="line-68"></a>
<a name="line-69"></a><a name="Feed"></a><span class='hs-comment'>-- | A pair of a 'Tensor' and some data that should be fed into that 'Tensor'</span>
<a name="line-70"></a><a name="Feed"></a><span class='hs-comment'>-- when running the graph.</span>
<a name="line-71"></a><a name="Feed"></a><span class='hs-keyword'>data</span> <span class='hs-conid'>Feed</span> <span class='hs-keyglyph'>=</span> <span class='hs-conid'>Feed</span> <span class='hs-conid'>Output</span> <span class='hs-conid'>FFI</span><span class='hs-varop'>.</span><span class='hs-conid'>TensorData</span>
<a name="line-72"></a>
<a name="line-73"></a><a name="feed"></a><span class='hs-comment'>-- | Create a 'Feed' for feeding the given data into a 'Tensor' when running</span>
<a name="line-74"></a><span class='hs-comment'>-- the graph.</span>
<a name="line-75"></a><span class='hs-comment'>--</span>
<a name="line-76"></a><span class='hs-comment'>-- Note that if a 'Tensor' is rendered, its identity may change; so feeding the</span>
<a name="line-77"></a><span class='hs-comment'>-- rendered 'Tensor' may be different than feeding the original 'Tensor'.</span>
<a name="line-78"></a><span class='hs-definition'>feed</span> <span class='hs-keyglyph'>::</span> <span class='hs-conid'>Tensor</span> <span class='hs-varid'>v</span> <span class='hs-varid'>a</span> <span class='hs-keyglyph'>-></span> <span class='hs-conid'>TensorData</span> <span class='hs-varid'>a</span> <span class='hs-keyglyph'>-></span> <span class='hs-conid'>Feed</span>
<a name="line-79"></a><span class='hs-definition'>feed</span> <span class='hs-layout'>(</span><span class='hs-conid'>Tensor</span> <span class='hs-keyword'>_</span> <span class='hs-varid'>o</span><span class='hs-layout'>)</span> <span class='hs-layout'>(</span><span class='hs-conid'>TensorData</span> <span class='hs-varid'>td</span><span class='hs-layout'>)</span> <span class='hs-keyglyph'>=</span> <span class='hs-conid'>Feed</span> <span class='hs-varid'>o</span> <span class='hs-varid'>td</span>
<a name="line-80"></a>
<a name="line-81"></a><a name="tensorFromName"></a><span class='hs-comment'>-- | Create a 'Tensor' for a given name. This can be used to reference nodes</span>
<a name="line-82"></a><span class='hs-comment'>-- in a 'GraphDef' that was loaded via 'addGraphDef'.</span>
<a name="line-83"></a><span class='hs-comment'>-- TODO(judahjacobson): add more safety checks here.</span>
<a name="line-84"></a><span class='hs-definition'>tensorFromName</span> <span class='hs-keyglyph'>::</span> <span class='hs-conid'>TensorKind</span> <span class='hs-varid'>v</span> <span class='hs-keyglyph'>-></span> <span class='hs-conid'>Text</span><span class='hs-varop'>.</span><span class='hs-conid'>Text</span> <span class='hs-keyglyph'>-></span> <span class='hs-conid'>Tensor</span> <span class='hs-varid'>v</span> <span class='hs-varid'>a</span>
<a name="line-85"></a><span class='hs-definition'>tensorFromName</span> <span class='hs-varid'>v</span> <span class='hs-keyglyph'>=</span> <span class='hs-conid'>Tensor</span> <span class='hs-varid'>v</span> <span class='hs-varop'>.</span> <span class='hs-varid'>fromString</span> <span class='hs-varop'>.</span> <span class='hs-conid'>Text</span><span class='hs-varop'>.</span><span class='hs-varid'>unpack</span>
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