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Add versions of each op that take optional params as an extra arg. (#84)
Each op `foo :: ...` now has a corresponding `foo' :: OpParams -> ...` which lets you set optional attributes. `OpParams` is currently a type alias for `OpDef -> OpDef`. In the future we should consider more type safety, e.g., using type-level strings and OverloadedLabels for optional attributes. I used it to replace a few manual `buildOp`s in our code with the codegenerated ops, now that it's easier to set attributes. I also removed `tensorAttr` and `named` since it's now possible to set those op attributes directly. Although this clutters up the API a bit, I think it's simpler than using type classes to implement optional arguments (as in, for example, `Text.Printf`) -- especially in terms of type inference with the rest of the library.
This commit is contained in:
Judah Jacobson
GitHub
parent
2c5c879037
commit
c99a23b6a7
11 changed files with 190 additions and 152 deletions
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@ -12,6 +12,7 @@
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-- See the License for the specific language governing permissions and
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-- limitations under the License.
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{-# LANGUAGE CPP #-}
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{-# LANGUAGE FlexibleContexts #-}
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{-# LANGUAGE LambdaCase #-}
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{-# LANGUAGE OverloadedStrings #-}
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@ -172,18 +173,28 @@ renderQuotedTFName = dquotes . renderTFName
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renderOp :: ParsedOp -> Doc
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renderOp pOp = stack $
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[ haddocks
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, n <+> "::" <+> hang 0 (typeSig pOp)
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, n <+> hang 0 args <+> "|" <+> funcGuard listSizeAttrs
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-- Prevent unreasonably long compilation times on ghc-7.10, due
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-- to stack calling "-dump-hi" which (unnecessarily) includes the
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-- inlining information, and is large for ops with many arguments.
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#if __GLASGOW_HASKELL__ < 800
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, "{-# NOINLINE " <> n <> "#-}"
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#endif
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, n <+> "::" <+> hang 0 (typeSig empty pOp)
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, n <+> "=" <+> n <> "' id"
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, n' <+> "::" <+> hang 0 (typeSig "OpParams ->" pOp)
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, n' <+> hang 0 args <+> "|" <+> funcGuard listSizeAttrs
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<+> "=" </> -- args are indented
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-- the body needs to be indented wrt the name
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indent indentation (functionBody pOp)
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] ++ whereClause listSizeAttrs
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where
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n = renderHaskellName $ parsedOpName pOp
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n' = n <> "'"
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listSizeAttrs = inferredListSizeAttrs pOp
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args = sep $ map renderHaskellName
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args = sep $ "op'options"
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: (map renderHaskellName
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$ map attrName (explicitInputAttrs pOp)
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++ map parsedArgName (parsedInputs pOp)
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++ map parsedArgName (parsedInputs pOp))
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haddocks = "-- |" <+> multilineComment (parsedOpSummary pOp) (parsedOpDescription pOp)
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-- | A check that all lists of the given size have the given length.
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@ -247,7 +258,9 @@ functionBody pOp = maybeLift <+> buildFunction <+> parens (hang 0 (stack buildOp
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-- Renders sizes of tensor list types having number_attr.
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[ "& opAttr" <+> renderQuotedTFName n <+> ".~" <+> renderHaskellName n
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| a <- inferredListSizeAttrs pOp, let n = attrName a
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]
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] ++
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["& op'options"]
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tensorArgs = renderHaskellName . parsedArgName <$> parsedInputs pOp
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inferredTypeExpr a
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@ -270,12 +283,12 @@ extras d = enclose "{-\n" "\n-}" $
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-- | The type signature for an op.
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-- Of the form:
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-- forall t1 t2 v1 v2 . (TensorType t1, TensorType t2)
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-- => Float -> Tensor t1 v1 -> Tensor t2 v2
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-- => {pre} Float -> Tensor t1 v1 -> Tensor t2 v2
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-- where "Float" is an explicit input attribute, "Tensor t1 v1" is an input, and
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-- "Tensor t2 v2" is an output.
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typeSig :: ParsedOp -> Doc
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typeSig pOp = constraints
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<+/> signatureFold (map attrInput (explicitInputAttrs pOp)
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typeSig :: Doc -> ParsedOp -> Doc
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typeSig pre pOp = constraints
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<+/> pre </> signatureFold (map attrInput (explicitInputAttrs pOp)
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++ map tensorArgAndComment (parsedInputs pOp)
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++ [outputs])
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where
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@ -72,6 +72,7 @@ import TensorFlow.Ops
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, expandDims
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, fill
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, matMul
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, matMul'
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, reducedShape
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, reluGrad
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, reshape
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@ -95,7 +96,6 @@ import TensorFlow.Tensor
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, TensorKind (ValueKind)
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, Value
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, tensorOutput
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, tensorAttr
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)
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import TensorFlow.Types (Attribute, OneOf, TensorType, attrLens)
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import Proto.Tensorflow.Core.Framework.NodeDef
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@ -532,20 +532,20 @@ opGrad "MatMul" nodeDef [toT -> x, toT -> y] [dz] =
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let transposeA = lookupAttr nodeDef "transpose_a"
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transposeB = lookupAttr nodeDef "transpose_b"
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transAttrs a b =
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(tensorAttr "transpose_a" .~ a) . (tensorAttr "transpose_b" .~ b)
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(opAttr "transpose_a" .~ a) . (opAttr "transpose_b" .~ b)
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in case (transposeA, transposeB) of
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(False, False) ->
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[ Just $ (dz `matMul` y) & transAttrs False True
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, Just $ (x `matMul` dz) & transAttrs True False ]
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[ Just $ matMul' (transAttrs False True) dz y
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, Just $ matMul' (transAttrs True False) x dz]
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(False, True) ->
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[ Just $ dz `matMul` y
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, Just $ (x `matMul` dz) & transAttrs True False ]
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[ Just $ matMul dz y
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, Just $ matMul' (transAttrs True False) x dz]
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(True, False) ->
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[ Just $ (dz `matMul` y) & transAttrs False True
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, Just $ x `matMul` dz ]
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[ Just $ matMul' (transAttrs False True) dz y
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, Just $ matMul x dz]
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(True, True) ->
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[ Just $ (dz `matMul` y) & transAttrs True True
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, Just $ (x `matMul` dz) & transAttrs True True ]
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[ Just $ matMul' (transAttrs True True) dz y
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, Just $ matMul' (transAttrs True True) x dz]
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opGrad "Transpose" _ [_, toT -> p] [dz] =
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[ Just $ CoreOps.transpose dz
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@ -554,16 +554,18 @@ opGrad "Transpose" _ [_, toT -> p] [dz] =
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]
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opGrad "Conv2D" nodeDef [toT -> x, toT -> y] [dz] =
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[ Just $ CoreOps.conv2DBackpropInput (shape x) y dz
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& tensorAttr "strides" .~ strides
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& tensorAttr "padding" .~ padding
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& tensorAttr "use_cudnn_on_gpu" .~ useCudnnOnGpu
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& tensorAttr "data_format" .~ dataFormat
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, Just $ CoreOps.conv2DBackpropFilter x (shape y) dz
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& tensorAttr "strides" .~ strides
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& tensorAttr "padding" .~ padding
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& tensorAttr "use_cudnn_on_gpu" .~ useCudnnOnGpu
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& tensorAttr "data_format" .~ dataFormat
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[ Just $ CoreOps.conv2DBackpropInput'
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((opAttr "strides" .~ strides)
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. (opAttr "padding" .~ padding)
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. (opAttr "use_cudnn_on_gpu" .~ useCudnnOnGpu)
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. (opAttr "data_format" .~ dataFormat))
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(shape x) y dz
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, Just $ CoreOps.conv2DBackpropFilter'
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((opAttr "strides" .~ strides)
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. (opAttr "padding" .~ padding)
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. (opAttr "use_cudnn_on_gpu" .~ useCudnnOnGpu)
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. (opAttr "data_format" .~ dataFormat))
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x (shape y) dz
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]
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where
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strides = lookupAttr nodeDef "strides" :: [Int64]
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@ -572,11 +574,12 @@ opGrad "Conv2D" nodeDef [toT -> x, toT -> y] [dz] =
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dataFormat = lookupAttr nodeDef "data_format" :: ByteString
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opGrad "MaxPool" nodeDef [toT -> x] [dz] =
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[ Just $ CoreOps.maxPoolGrad x output dz
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& tensorAttr "ksize" .~ ksize
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& tensorAttr "strides" .~ strides
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& tensorAttr "padding" .~ padding
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& tensorAttr "data_format" .~ dataFormat
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[ Just $ CoreOps.maxPoolGrad'
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((opAttr "ksize" .~ ksize)
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. (opAttr "strides" .~ strides)
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. (opAttr "padding" .~ padding)
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. (opAttr "data_format" .~ dataFormat))
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x output dz
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]
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where
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output :: Tensor Value a
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@ -58,56 +58,99 @@
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module TensorFlow.Ops
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( CoreOps.add
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, CoreOps.add'
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, CoreOps.abs
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, CoreOps.abs'
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, CoreOps.addN
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, CoreOps.addN'
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, CoreOps.argMax
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, CoreOps.argMax'
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, CoreOps.assign
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, CoreOps.assign'
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, CoreOps.broadcastGradientArgs
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, CoreOps.broadcastGradientArgs'
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, CoreOps.cast
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, CoreOps.cast'
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, CoreOps.concat
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, CoreOps.concat'
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, constant
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, constant'
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, CoreOps.equal
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, CoreOps.equal'
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, expandDims
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, expandDims'
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, initializedVariable
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, initializedVariable'
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, zeroInitializedVariable
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, zeroInitializedVariable'
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, CoreOps.fill
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, CoreOps.oneHot
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, CoreOps.fill'
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, CoreOps.identity
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, CoreOps.identity'
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, CoreOps.matMul
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, CoreOps.matMul'
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, matTranspose
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, matTranspose'
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, CoreOps.mean
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, CoreOps.mean'
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, CoreOps.mul
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, CoreOps.mul'
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, CoreOps.neg
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, CoreOps.neg'
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, CoreOps.oneHot
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, CoreOps.oneHot'
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, CoreOps.pack
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, CoreOps.pack'
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, placeholder
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, placeholder'
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, CoreOps.range
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, CoreOps.range'
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, reducedShape
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, CoreOps.relu
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, CoreOps.relu'
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, CoreOps.reluGrad
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, CoreOps.reluGrad'
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, CoreOps.reshape
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, CoreOps.reshape'
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, restore
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, restoreFromName
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, save
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, scalar
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, scalar'
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, shape
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, shape'
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, CoreOps.sign
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, CoreOps.sign'
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, CoreOps.size
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, CoreOps.size'
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, CoreOps.softmax
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, CoreOps.softmax'
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, CoreOps.softmaxCrossEntropyWithLogits
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, CoreOps.softmaxCrossEntropyWithLogits'
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, CoreOps.sparseToDense
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, CoreOps.sparseToDense'
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, CoreOps.sub
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, CoreOps.sub'
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, CoreOps.sum
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, CoreOps.sum'
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, CoreOps.transpose
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, CoreOps.transpose'
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, truncatedNormal
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, truncatedNormal'
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, CoreOps.variable
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, CoreOps.variable'
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, vector
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, vector'
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, zeros
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, CoreOps.zerosLike
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, CoreOps.zerosLike'
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, scalarize
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) where
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import Data.ByteString (ByteString)
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import Data.Complex (Complex)
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import Data.Int (Int32, Int64)
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import Data.Word (Word16)
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import Prelude hiding (abs, sum, concat)
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import Data.ProtoLens (def)
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import Data.Text.Encoding (encodeUtf8)
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@ -151,29 +194,31 @@ instance ( TensorType a
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signum = CoreOps.sign
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negate = CoreOps.neg
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matTranspose :: forall a v . TensorType a
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=> Tensor v a -> Tensor Value a
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matTranspose = flip CoreOps.transpose (vector [1, 0 :: Int32])
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matTranspose :: TensorType a => Tensor v a -> Tensor Value a
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matTranspose = matTranspose' id
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placeholder :: forall a m . (MonadBuild m, TensorType a) => Shape -> m (Tensor Value a)
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placeholder shape' =
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build $ buildOp $ opDef "Placeholder"
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& opAttr "dtype" .~ tensorType (undefined :: a)
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& opAttr "shape" .~ shape'
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matTranspose' :: TensorType a => OpParams -> Tensor v a -> Tensor Value a
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matTranspose' params = flip (CoreOps.transpose' params) (vector [1, 0 :: Int32])
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placeholder :: (MonadBuild m, TensorType a) => Shape -> m (Tensor Value a)
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placeholder = placeholder' id
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placeholder' :: (MonadBuild m, TensorType a) => OpParams -> Shape -> m (Tensor Value a)
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placeholder' params pShape
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= render $ CoreOps.placeholder' (params . (opAttr "shape" .~ pShape))
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-- | Creates a variable initialized to the given value.
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-- Initialization happens next time session runs.
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initializedVariable :: forall a m . (MonadBuild m, TensorType a)
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initializedVariable :: (MonadBuild m, TensorType a)
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=> Tensor Value a -> m (Tensor Ref a)
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initializedVariable initializer = do
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v <- CoreOps.variable [] -- The shape is not known initially.
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(i :: Tensor Ref a) <-
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build $ buildOp (opDef "Assign"
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& opAttr "T" .~ tensorType (undefined :: a)
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& opAttr "use_locking" .~ True
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& opAttr "validate_shape" .~ False
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)
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v initializer
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initializedVariable = initializedVariable' id
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initializedVariable' :: (MonadBuild m, TensorType a)
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=> OpParams -> Tensor Value a -> m (Tensor Ref a)
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initializedVariable' params initializer = do
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v <- CoreOps.variable' params [] -- The shape is not known initially.
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i <- CoreOps.assign' (opAttr "validate_shape" .~ False) v
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initializer
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addInitializer =<< group i
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return v
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@ -181,7 +226,12 @@ initializedVariable initializer = do
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zeroInitializedVariable
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:: (MonadBuild m, TensorType a, Num a) =>
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TensorFlow.Types.Shape -> m (Tensor TensorFlow.Tensor.Ref a)
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zeroInitializedVariable = initializedVariable . zeros
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zeroInitializedVariable = zeroInitializedVariable' id
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zeroInitializedVariable'
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:: (MonadBuild m, TensorType a, Num a) =>
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OpParams -> TensorFlow.Types.Shape -> m (Tensor TensorFlow.Tensor.Ref a)
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zeroInitializedVariable' params = initializedVariable' params . zeros
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-- TODO: Support heterogeneous list of tensors.
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save :: forall a m v . (MonadBuild m, TensorType a)
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@ -227,23 +277,23 @@ restore path x = do
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-- element 0: index (0, ..., 0)
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-- element 1: index (0, ..., 1)
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-- ...
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constant :: forall a . TensorType a => Shape -> [a] -> Tensor Value a
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constant (Shape shape') values
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constant :: TensorType a => Shape -> [a] -> Tensor Value a
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constant = constant' id
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constant' :: forall a . TensorType a => OpParams -> Shape -> [a] -> Tensor Value a
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constant' params (Shape cShape) values
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| invalidLength = error invalidLengthMsg
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| otherwise = buildOp $ opDef "Const"
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& opAttr "value" .~ typedNode
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& opAttr "dtype" .~ nodeType
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| otherwise = CoreOps.const' (params . (opAttr "value" .~ typedNode))
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where
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invalidLength = product shape' /= fromIntegral (length values)
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invalidLength = product cShape /= fromIntegral (length values)
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invalidLengthMsg = printf "invalid tensor length: expected %d got %d"
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(product shape')
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(product cShape)
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(length values)
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nodeType = tensorType (undefined :: a)
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typedNode :: TensorProto
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typedNode = def
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& dtype .~ nodeType
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& dtype .~ tensorType (undefined :: a)
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& tensorShape.TensorShape.dim .~
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[def & TensorShape.size .~ x | x <- shape']
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[def & TensorShape.size .~ x | x <- cShape]
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& tensorVal .~ values
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-- | Reshape a N-D tensor down to a scalar.
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@ -257,30 +307,46 @@ scalarize t = CoreOps.reshape t (vector scalarShape)
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-- | Create a constant vector.
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vector :: TensorType a => [a] -> Tensor Value a
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vector xs = constant [fromIntegral $ length xs] xs
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vector = vector' id
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vector' :: TensorType a => OpParams -> [a] -> Tensor Value a
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vector' params xs = constant' params [fromIntegral $ length xs] xs
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-- | Create a constant scalar.
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scalar :: forall a . TensorType a => a -> Tensor Value a
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scalar x = constant [] [x]
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scalar :: TensorType a => a -> Tensor Value a
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scalar = scalar' id
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-- Random tensor from the unit normal distribution with bounded values.
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truncatedNormal :: forall a m v . (MonadBuild m, TensorType a)
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scalar' :: TensorType a => OpParams -> a -> Tensor Value a
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scalar' params x = constant' params [] [x]
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-- | Random tensor from the unit normal distribution with bounded values.
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--
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-- This is a type-restricted version of 'TensorFlow.GenOps.Core.truncatedNormal'.
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truncatedNormal :: (MonadBuild m, OneOf '[Word16, Double, Float] a)
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=> Tensor v Int64 -- ^ Shape.
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-> m (Tensor Value a)
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truncatedNormal
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= build . buildOp (opDef "TruncatedNormal"
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& opAttr "dtype" .~ tensorType (undefined :: a)
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& opAttr "T" .~ tensorType (undefined :: Int64))
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truncatedNormal = CoreOps.truncatedNormal
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truncatedNormal' :: (MonadBuild m, OneOf '[Word16, Double, Float] a)
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=> OpParams -> Tensor v Int64 -- ^ Shape.
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-> m (Tensor Value a)
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truncatedNormal' = CoreOps.truncatedNormal'
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zeros :: forall a . (Num a, TensorType a) => Shape -> Tensor Value a
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zeros (Shape shape') = CoreOps.fill (vector $ map fromIntegral shape') (scalar 0)
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zeros (Shape s) = CoreOps.fill (vector $ map fromIntegral s) (scalar 0)
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shape :: (TensorType t) => Tensor v1 t -> Tensor Value Int32
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shape :: TensorType t => Tensor v1 t -> Tensor Value Int32
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shape = CoreOps.shape
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expandDims :: (TensorType t) => Tensor v1 t -> Tensor v2 Int32 -> Tensor Value t
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shape' :: TensorType t => OpParams -> Tensor v1 t -> Tensor Value Int32
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shape' = CoreOps.shape'
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expandDims :: TensorType t => Tensor v1 t -> Tensor v2 Int32 -> Tensor Value t
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expandDims = CoreOps.expandDims
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|
||||
expandDims' :: TensorType t => OpParams -> Tensor v1 t -> Tensor v2 Int32 -> Tensor Value t
|
||||
expandDims' = CoreOps.expandDims'
|
||||
|
||||
-- | Helper function for reduction ops (translation of math_ops.reduced_shape).
|
||||
reducedShape :: (OneOf '[ Int32, Int64 ] t1, OneOf '[ Int32, Int64 ] t2) =>
|
||||
Tensor v1 t1 -> Tensor v2 t2 -> Tensor Value Int32
|
||||
|
|
|
|||
|
|
@ -19,7 +19,7 @@
|
|||
module Main where
|
||||
|
||||
import Control.Monad.IO.Class (liftIO)
|
||||
import Lens.Family2 ((^.))
|
||||
import Lens.Family2 ((^.), (.~))
|
||||
import Data.List (sort)
|
||||
import Proto.Tensorflow.Core.Framework.Graph
|
||||
( node )
|
||||
|
|
@ -38,8 +38,8 @@ import TensorFlow.Build
|
|||
, withDevice
|
||||
, colocateWith
|
||||
, withNameScope
|
||||
, opName
|
||||
)
|
||||
import TensorFlow.ControlFlow (named)
|
||||
import TensorFlow.Types (unScalar)
|
||||
import TensorFlow.Ops
|
||||
( add
|
||||
|
|
@ -47,6 +47,7 @@ import TensorFlow.Ops
|
|||
, constant
|
||||
, initializedVariable
|
||||
, variable
|
||||
, variable'
|
||||
)
|
||||
import TensorFlow.Output (Device(..))
|
||||
import TensorFlow.Tensor (Tensor, Value, Ref)
|
||||
|
|
@ -61,26 +62,16 @@ import Test.HUnit ((@=?))
|
|||
import Google.Test (googleTest)
|
||||
import qualified Data.Vector as V
|
||||
|
||||
-- | Test named behavior.
|
||||
testNamed :: Test
|
||||
testNamed = testCase "testNamed" $ do
|
||||
let graph = named "foo" <$> variable [] >>= render :: Build (Tensor Ref Float)
|
||||
-- | Test 'opName' behavior.
|
||||
testOpName :: Test
|
||||
testOpName = testCase "testOpName" $ do
|
||||
let graph = variable' (opName .~ "foo") []
|
||||
>>= render :: Build (Tensor Ref Float)
|
||||
nodeDef :: NodeDef
|
||||
nodeDef = head $ asGraphDef graph ^. node
|
||||
"RefIdentity" @=? (nodeDef ^. op)
|
||||
"Variable" @=? (nodeDef ^. op)
|
||||
"foo" @=? (nodeDef ^. name)
|
||||
|
||||
-- | Test named deRef behavior.
|
||||
testNamedDeRef :: Test
|
||||
testNamedDeRef = testCase "testNamedDeRef" $ do
|
||||
let graph = named "foo" <$> do
|
||||
v :: Tensor Ref Float <- variable []
|
||||
assign v 5
|
||||
-- TODO: Implement TensorFlow get_variable and test it.
|
||||
runSession $ do
|
||||
out <- graph >>= run
|
||||
liftIO $ 5 @=? (unScalar out :: Float)
|
||||
|
||||
-- | Test that "run" will render and extend any pure ops that haven't already
|
||||
-- been rendered.
|
||||
testPureRender :: Test
|
||||
|
|
@ -118,14 +109,15 @@ testNameScoped = testCase "testNameScoped" $ do
|
|||
"foo/Variable_0" @=? (nodeDef ^. name) -- TODO: Check prefix.
|
||||
"Variable" @=? (nodeDef ^. op)
|
||||
|
||||
-- | Test combined named and nameScoped behavior.
|
||||
-- | Test combined opName and nameScoped behavior.
|
||||
testNamedAndScoped :: Test
|
||||
testNamedAndScoped = testCase "testNamedAndScoped" $ do
|
||||
let graph :: Build (Tensor Ref Float)
|
||||
graph = withNameScope "foo1" ((named "bar1" <$> variable []) >>= render)
|
||||
graph = withNameScope "foo1" (variable' (opName .~ "bar1") [])
|
||||
>>= render
|
||||
nodeDef :: NodeDef
|
||||
nodeDef = head $ asGraphDef graph ^. node
|
||||
"RefIdentity" @=? (nodeDef ^. op)
|
||||
"Variable" @=? (nodeDef ^. op)
|
||||
"foo1/bar1" @=? (nodeDef ^. name)
|
||||
|
||||
-- | Flush the node buffer and sort the nodes by name (for more stable tests).
|
||||
|
|
@ -174,8 +166,7 @@ main :: IO ()
|
|||
main = googleTest [ testInitializedVariable
|
||||
, testInitializedVariableShape
|
||||
, testDeviceColocation
|
||||
, testNamed
|
||||
, testNamedDeRef
|
||||
, testOpName
|
||||
, testNameScoped
|
||||
, testNamedAndScoped
|
||||
, testPureRender
|
||||
|
|
|
|||
|
|
@ -19,6 +19,7 @@ module Main where
|
|||
import Control.Monad.IO.Class (liftIO)
|
||||
import Data.Int (Int32, Int64)
|
||||
import Google.Test (googleTest)
|
||||
import Lens.Family2 ((.~))
|
||||
import System.IO.Temp (withSystemTempDirectory)
|
||||
import Test.Framework (Test)
|
||||
import Test.Framework.Providers.HUnit (testCase)
|
||||
|
|
@ -27,7 +28,6 @@ import qualified Data.ByteString.Char8 as B8
|
|||
|
||||
import qualified Data.Vector as V
|
||||
import qualified TensorFlow.Build as TF
|
||||
import qualified TensorFlow.ControlFlow as TF
|
||||
import qualified TensorFlow.Nodes as TF
|
||||
import qualified TensorFlow.Ops as TF
|
||||
import qualified TensorFlow.Session as TF
|
||||
|
|
@ -56,7 +56,8 @@ testSaveRestore = testCase "testSaveRestore" $
|
|||
let path = B8.pack $ dirPath ++ "/checkpoint"
|
||||
var :: TF.MonadBuild m => m (TF.Tensor TF.Ref Float)
|
||||
var = TF.render =<<
|
||||
TF.named "a" <$> TF.zeroInitializedVariable (TF.Shape [])
|
||||
TF.zeroInitializedVariable' (TF.opName .~ "a")
|
||||
(TF.Shape [])
|
||||
TF.runSession $ do
|
||||
v <- var
|
||||
TF.assign v 134 >>= TF.run_
|
||||
|
|
|
|||
|
|
@ -36,7 +36,6 @@ import qualified Data.ByteString as B
|
|||
import qualified Data.ByteString.Char8 as B8
|
||||
import qualified Data.Vector as V
|
||||
|
||||
import qualified TensorFlow.ControlFlow as TF
|
||||
import qualified TensorFlow.GenOps.Core as TF (select)
|
||||
import qualified TensorFlow.Ops as TF
|
||||
import qualified TensorFlow.Session as TF
|
||||
|
|
|
|||
|
|
@ -23,6 +23,7 @@ module TensorFlow.BuildOp
|
|||
, buildOp
|
||||
, buildListOp
|
||||
, eqLengthGuard
|
||||
, OpParams
|
||||
)
|
||||
where
|
||||
|
||||
|
|
@ -238,3 +239,7 @@ eqLengthGuard = all eachOk
|
|||
eachOk (numberAttrName, pairs@((_, x) : zs)) = all (\z -> snd z == x) zs ||
|
||||
error ("number_attr " ++ numberAttrName ++
|
||||
" contains tensors with different length " ++ show pairs)
|
||||
|
||||
-- | Parameters to build an op (for example, the node name or optional attributes).
|
||||
-- TODO: be more type safe.
|
||||
type OpParams = OpDef -> OpDef
|
||||
|
|
|
|||
|
|
@ -22,21 +22,15 @@ module TensorFlow.ControlFlow
|
|||
withControlDependencies
|
||||
, group
|
||||
-- * Operations
|
||||
, identity
|
||||
, noOp
|
||||
, named
|
||||
) where
|
||||
|
||||
import qualified Data.Set as Set
|
||||
import Data.Text (Text)
|
||||
import Lens.Family2 ((&), (^.), (.~))
|
||||
import Lens.Family2 ((&), (.~))
|
||||
|
||||
import TensorFlow.BuildOp
|
||||
import TensorFlow.Build
|
||||
import TensorFlow.Nodes
|
||||
import TensorFlow.Output
|
||||
import TensorFlow.Tensor
|
||||
import TensorFlow.Types
|
||||
|
||||
-- | Modify a 'Build' action, such that all new ops rendered in it will depend
|
||||
-- on the nodes in the first argument.
|
||||
|
|
@ -57,31 +51,6 @@ group deps = do
|
|||
-- TODO: slicker way
|
||||
return $ buildOp $ opDef "NoOp" & opControlInputs .~ nodes
|
||||
|
||||
|
||||
-- | Returns a 'Tensor' with the same shape and contents as the input.
|
||||
identity :: TensorType a => Tensor v a -> Tensor v a
|
||||
identity = namedIdentity implicitName
|
||||
|
||||
-- | Returns a 'Tensor' with a given name and the same shape and contents as
|
||||
-- the input.
|
||||
--
|
||||
-- TODO(judahjacobson): This breaks when used with uninitialize @Tensor Ref@s,
|
||||
-- since @RefIdentity@ doesn't have SetAllowsUninitializedInput(). Look into
|
||||
-- whether we can change that op.
|
||||
named :: TensorType a => Text -> Tensor v a -> Tensor v a
|
||||
named = namedIdentity . explicitName
|
||||
|
||||
-- | An internal version of "identity" that allows setting the name
|
||||
-- of the output Tensor.
|
||||
namedIdentity :: forall a v . TensorType a
|
||||
=> PendingNodeName -> Tensor v a -> Tensor v a
|
||||
namedIdentity n t = case t ^. tensorKind of
|
||||
ValueKind -> buildOp (opDefWithName n "Identity" & setTypeAttr) t
|
||||
RefKind -> buildOp (opDefWithName n "RefIdentity" & setTypeAttr) t
|
||||
where
|
||||
setTypeAttr = opAttr "T" .~ tensorType (undefined :: a)
|
||||
|
||||
|
||||
-- | Does nothing. Only useful as a placeholder for control edges.
|
||||
noOp :: ControlNode
|
||||
noOp = buildOp $ opDef "NoOp"
|
||||
|
|
|
|||
|
|
@ -50,14 +50,14 @@ module TensorFlow.Core
|
|||
, render
|
||||
, asGraphDef
|
||||
, addGraphDef
|
||||
|
||||
, opName
|
||||
, opAttr
|
||||
-- * Tensor
|
||||
, ControlNode
|
||||
, Tensor
|
||||
, Value
|
||||
, Ref
|
||||
, TensorKind(..)
|
||||
, tensorAttr
|
||||
, value
|
||||
, tensorFromName
|
||||
-- ** Element types
|
||||
|
|
@ -74,12 +74,10 @@ module TensorFlow.Core
|
|||
, Device(..)
|
||||
, withDevice
|
||||
, withNameScope
|
||||
, named
|
||||
-- ** Dependencies
|
||||
, withControlDependencies
|
||||
, group
|
||||
-- ** Misc
|
||||
, identity
|
||||
, noOp
|
||||
) where
|
||||
|
||||
|
|
|
|||
|
|
@ -124,6 +124,9 @@ data OpDef = OpDef
|
|||
data PendingNodeName = ExplicitName !Text | ImplicitName
|
||||
deriving (Eq, Ord, Show)
|
||||
|
||||
instance IsString PendingNodeName where
|
||||
fromString = ExplicitName . fromString
|
||||
|
||||
-- | The name of a node in the graph. This corresponds to the proto field
|
||||
-- NodeDef.name. Includes the scope prefix (if any) and a unique identifier
|
||||
-- (if the node was implicitly named).
|
||||
|
|
|
|||
|
|
@ -27,13 +27,12 @@ module TensorFlow.Tensor where
|
|||
|
||||
import Data.String (IsString(..))
|
||||
import qualified Data.Text as Text
|
||||
import Lens.Family2 (Lens', Traversal', (^.))
|
||||
import Lens.Family2 (Lens', (^.))
|
||||
import Lens.Family2.Unchecked (lens)
|
||||
|
||||
import TensorFlow.Output (Output, outputOp, opUnrendered, opAttr)
|
||||
import TensorFlow.Output (Output)
|
||||
import TensorFlow.Types
|
||||
( TensorData(..)
|
||||
, Attribute
|
||||
, ListOf(..)
|
||||
)
|
||||
import qualified TensorFlow.Internal.FFI as FFI
|
||||
|
|
@ -62,15 +61,6 @@ tensorKind = lens (\(Tensor v _) -> v) (\(Tensor _ o) v -> Tensor v o)
|
|||
tensorOutput :: Lens' (Tensor v a) Output
|
||||
tensorOutput = lens (\(Tensor _ o) -> o) (\(Tensor v _) o -> Tensor v o)
|
||||
|
||||
-- TODO: Come up with a better API for handling attributes.
|
||||
-- | Lens for the attributes of a tensor.
|
||||
--
|
||||
-- Only valid if the tensor has not yet been rendered. If the tensor has been
|
||||
-- rendered, the traversal will be over nothing (nothing can be read or
|
||||
-- written).
|
||||
tensorAttr :: Attribute attr => Text.Text -> Traversal' (Tensor v a) attr
|
||||
tensorAttr x = tensorOutput . outputOp . opUnrendered . opAttr x
|
||||
|
||||
-- | Cast a 'Tensor *' into a 'Tensor Value'. Common usage is to cast a
|
||||
-- Ref into Value. This behaves like a no-op.
|
||||
value :: Tensor v a -> Tensor Value a
|
||||
|
|
|
|||
Loading…
Reference in a new issue