Tensorflow 2.3.0 Support (#267)

* Tensorflow 2.3.0 building and passing tests.
* Added einsum and test.
* Added ByteString as a possible argument to a function.
* Support more data types for Adam.
* Move to later version of LTS on stackage.
* Added a wrapper module for convolution functions.
* Update ci build to use a later version of stack.
* Removed a deprecated import in GradientTest.
This commit is contained in:
jcmartin 2020-11-06 11:32:21 -08:00 committed by GitHub
parent 568c9b6f03
commit c66c912c32
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
21 changed files with 409 additions and 75 deletions

1
.gitignore vendored
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@ -2,3 +2,4 @@
.stack/
tensorflow-mnist-input-data/data/*.gz
.DS_Store
stack.yaml.lock

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@ -3,7 +3,7 @@
# stack to be installed on the host. This comes at the expense of
# flexibility.
FROM tensorflow/tensorflow:1.14.0
FROM tensorflow/tensorflow:2.3.0
LABEL maintainer="TensorFlow authors <tensorflow-haskell@googlegroups.com>"
# The build context directory is the top of the tensorflow-haskell
@ -30,14 +30,14 @@ RUN \
netbase \
&& \
# Installs stack.
curl -O -L https://github.com/commercialhaskell/stack/releases/download/v2.1.3/stack-2.1.3-linux-x86_64.tar.gz && \
tar zxf stack-2.1.3-linux-x86_64.tar.gz -C /usr/local/bin stack-2.1.3-linux-x86_64/stack --strip 1 && \
curl -O -L https://github.com/commercialhaskell/stack/releases/download/v2.5.1/stack-2.5.1-linux-x86_64.tar.gz && \
tar zxf stack-2.5.1-linux-x86_64.tar.gz -C /usr/local/bin stack-2.5.1-linux-x86_64/stack --strip 1 && \
# Installs protoc and the libraries.
curl -O -L https://github.com/google/protobuf/releases/download/v3.9.1/protoc-3.9.1-linux-x86_64.zip && \
unzip -d /usr/local protoc-3.9.1-linux-x86_64.zip bin/protoc && \
curl -O -L https://github.com/google/protobuf/releases/download/v3.13.0/protoc-3.13.0-linux-x86_64.zip && \
unzip -d /usr/local protoc-3.13.0-linux-x86_64.zip bin/protoc && \
chmod 755 /usr/local/bin/protoc && \
curl -O https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-1.14.0.tar.gz && \
tar zxf libtensorflow-cpu-linux-x86_64-1.14.0.tar.gz -C /usr/local && \
curl -O https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-2.3.0.tar.gz && \
tar zxf libtensorflow-cpu-linux-x86_64-2.3.0.tar.gz -C /usr/local && \
ldconfig && \
stack setup && \
stack test --only-dependencies

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@ -1,6 +1,6 @@
# Prepare the image with:
# docker build -t tensorflow/haskell:v0 docker
FROM tensorflow/tensorflow:1.14.0
FROM tensorflow/tensorflow:2.3.0
LABEL maintainer="TensorFlow authors <tensorflow-haskell@googlegroups.com>"
RUN apt-get update
@ -28,11 +28,11 @@ RUN dpkg-reconfigure locales && \
# Installs protoc and the libraries.
RUN \
curl -O -L https://github.com/google/protobuf/releases/download/v3.9.1/protoc-3.9.1-linux-x86_64.zip && \
unzip -d /usr/local protoc-3.9.1-linux-x86_64.zip bin/protoc && \
curl -O -L https://github.com/google/protobuf/releases/download/v3.13.0/protoc-3.13.0-linux-x86_64.zip && \
unzip -d /usr/local protoc-3.13.0-linux-x86_64.zip bin/protoc && \
chmod 755 /usr/local/bin/protoc && \
curl -O https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-1.14.0.tar.gz && \
tar zxf libtensorflow-cpu-linux-x86_64-1.14.0.tar.gz -C /usr/local && \
curl -O https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-2.3.0.tar.gz && \
tar zxf libtensorflow-cpu-linux-x86_64-2.3.0.tar.gz -C /usr/local && \
ldconfig
ENV LANG en_US.UTF-8

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@ -1,6 +1,6 @@
# Prepare the image with:
# docker build -t tensorflow/haskell:1.14.0-gpu docker/gpu
FROM tensorflow/tensorflow:1.14.0-gpu
FROM tensorflow/tensorflow:2.3.0-gpu
LABEL maintainer="TensorFlow authors <tensorflow-haskell@googlegroups.com>"
RUN apt-get update
@ -28,11 +28,11 @@ RUN dpkg-reconfigure locales && \
# Installs protoc and the libraries.
RUN \
curl -O -L https://github.com/google/protobuf/releases/download/v3.9.1/protoc-3.9.1-linux-x86_64.zip && \
unzip -d /usr/local protoc-3.9.1-linux-x86_64.zip bin/protoc && \
curl -O -L https://github.com/google/protobuf/releases/download/v3.13.0/protoc-3.13.0-linux-x86_64.zip && \
unzip -d /usr/local protoc-3.13.0-linux-x86_64.zip bin/protoc && \
chmod 755 /usr/local/bin/protoc && \
curl -O https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-linux-x86_64-1.14.0.tar.gz && \
tar zxf libtensorflow-gpu-linux-x86_64-1.14.0.tar.gz -C /usr/local && \
curl -O https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-gpu-linux-x86_64-2.3.0.tar.gz && \
tar zxf libtensorflow-gpu-linux-x86_64-2.3.0.tar.gz -C /usr/local && \
ldconfig
ENV LANG en_US.UTF-8

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@ -1,4 +1,4 @@
resolver: lts-15.11
resolver: lts-16.18
packages:
- tensorflow

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@ -105,6 +105,8 @@ blackList =
, "GroupByWindowDataset"
, "If"
, "InterleaveDataset"
, "LegacyParallelInterleaveDatasetV2"
, "LoadDataset"
, "MapAndBatchDataset"
, "MapAndBatchDatasetV2"
, "MapDataset"
@ -112,16 +114,24 @@ blackList =
, "OneShotIterator"
, "ParallelInterleaveDataset"
, "ParallelInterleaveDatasetV2"
, "ParallelInterleaveDatasetV3"
, "ParallelInterleaveDatasetV4"
, "ParallelMapDataset"
, "ParallelMapDatasetV2"
, "ParseSequenceExample"
, "ParseSequenceExampleV2"
, "ParseSingleSequenceExample"
, "PartitionedCall"
, "ReduceDataset"
, "RemoteCall"
, "SaveDataset"
, "ScanDataset"
, "SnapshotDatasetV2"
, "StatefulPartitionedCall"
, "StatelessIf"
, "StatelessWhile"
, "SymbolicGradient"
, "TakeWhileDataset"
, "TPUPartitionedCall"
, "TPUReplicate"
, "While"
@ -130,6 +140,7 @@ blackList =
, "XlaReduce"
, "XlaReduceWindow"
, "XlaSelectAndScatter"
, "XlaScatter"
, "XlaWhile"
, "_If"
, "_TPUReplicate"

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@ -16,7 +16,7 @@ library
exposed-modules: TensorFlow.GenOps.Core
autogen-modules: TensorFlow.GenOps.Core
build-depends: bytestring
, proto-lens == 0.6.*
, proto-lens == 0.7.*
, tensorflow == 0.2.*
, base >= 4.7 && < 5
, lens-family == 2.*
@ -27,7 +27,7 @@ custom-setup
setup-depends: Cabal
, bytestring
, directory
, proto-lens == 0.6.*
, proto-lens == 0.7.*
, tensorflow-opgen == 0.2.*
, tensorflow == 0.2.*
, base >= 4.7 && < 5

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@ -24,7 +24,7 @@ library
, filepath
, hostname
, lens-family == 2.*
, proto-lens == 0.6.*
, proto-lens == 0.7.*
, resourcet
, stm
, stm-chans

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@ -20,7 +20,7 @@ library
exposed-modules: TensorFlow.Examples.MNIST.Parse
, TensorFlow.Examples.MNIST.TrainedGraph
other-modules: Paths_tensorflow_mnist
build-depends: proto-lens == 0.6.*
build-depends: proto-lens == 0.7.*
, base >= 4.7 && < 5
, binary
, bytestring

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@ -266,7 +266,7 @@ getExplicitInputAttr o implicitAttrs a
, a ^. maybe'defaultValue == Nothing
, t <- parseAttrType o (a ^. type')
, t `elem` map AttrSingle
[AttrBool, AttrInt64, AttrFloat, AttrType, AttrShape]
[AttrBool, AttrInt64, AttrFloat, AttrType, AttrShape, AttrBytes]
++ [AttrList AttrType] = Just t
| otherwise = Nothing

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@ -16,7 +16,7 @@ library
hs-source-dirs: src
exposed-modules: TensorFlow.OpGen.ParsedOp
, TensorFlow.OpGen
build-depends: proto-lens == 0.6.*
build-depends: proto-lens == 0.7.*
, tensorflow-proto == 0.2.*
, base >= 4.7 && < 5
, bytestring

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@ -0,0 +1,300 @@
-- Copyright 2020 TensorFlow authors.
--
-- Licensed under the Apache License, Version 2.0 (the "License");
-- you may not use this file except in compliance with the License.
-- You may obtain a copy of the License at
--
-- http://www.apache.org/licenses/LICENSE-2.0
--
-- Unless required by applicable law or agreed to in writing, software
-- distributed under the License is distributed on an "AS IS" BASIS,
-- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-- See the License for the specific language governing permissions and
-- limitations under the License.
{-# LANGUAGE ConstraintKinds #-}
{-# LANGUAGE DataKinds #-}
{-# LANGUAGE OverloadedStrings #-}
module TensorFlow.Convolution
( Padding(..)
, DataFormat(..)
, conv2D
, conv2D'
, conv2DBackpropFilter
, conv2DBackpropFilter'
, conv2DBackpropInput
, conv2DBackpropInput'
, conv3D
, conv3D'
, conv3DBackpropFilter
, conv3DBackpropFilter'
, conv3DBackpropFilterV2
, conv3DBackpropFilterV2'
, conv3DBackpropInput
, conv3DBackpropInput'
, conv3DBackpropInputV2
, conv3DBackpropInputV2'
, depthwiseConv2dNative
, depthwiseConv2dNative'
, depthwiseConv2dNativeBackpropFilter
, depthwiseConv2dNativeBackpropFilter'
, depthwiseConv2dNativeBackpropInput
, depthwiseConv2dNativeBackpropInput'
) where
import Data.Word (Word16)
import Data.Int (Int32,Int64)
import Data.ByteString (ByteString)
import Lens.Family2 ((.~))
import qualified TensorFlow.BuildOp as TF
import qualified TensorFlow.Core as TF
import qualified TensorFlow.GenOps.Core as TF
-- TODO: Support other convolution parameters such as stride.
-- | Convolution padding.
data Padding =
-- | output_spatial_shape[i] = ceil(input_spatial_shape[i] / strides[i])
PaddingValid
-- | output_spatial_shape[i] = ceil(
-- (input_spatial_shape[i] -
-- (spatial_filter_shape[i]-1) * dilation_rate[i]) / strides[i])
| PaddingSame
paddingToByteString :: Padding -> ByteString
paddingToByteString x = case x of
PaddingValid -> "VALID"
PaddingSame -> "SAME"
-- | Matrix format.
data DataFormat = ChannelLast -- ^ Channel is the last dimension (e.g. NWC, NHWC, NDHWC)
| ChannelFirst -- ^ Channel is the first dimension after N (e.g. NCW, NCHW, NCDHW)
-- TODO: Address 1D convolution.
dataFormat2D :: DataFormat -> ByteString
dataFormat2D x = case x of
ChannelLast -> "NHWC"
ChannelFirst -> "NCHW"
dataFormat3D :: DataFormat -> ByteString
dataFormat3D x = case x of
ChannelLast -> "NDHWC"
ChannelFirst -> "NCDHW"
-- | 2D Convolution with default parameters.
conv2D :: TF.OneOf '[Word16, Double, Float] t
=> TF.Tensor v1 t -- ^ input
-> TF.Tensor v2 t -- ^ filter
-> TF.Tensor TF.Build t -- ^ output
conv2D = conv2D' id PaddingValid ChannelLast
conv2D' :: TF.OneOf '[Word16, Double, Float] t
=> TF.OpParams
-> Padding
-> DataFormat
-> TF.Tensor v1 t -- ^ input
-> TF.Tensor v2 t -- ^ filter
-> TF.Tensor TF.Build t -- ^ output
conv2D' params padding dataformat = TF.conv2D'
(params . (TF.opAttr "data_format" .~ dataFormat2D dataformat))
(paddingToByteString padding)
-- | 2D convolution backpropagation filter with default parameters.
conv2DBackpropFilter :: TF.OneOf '[Word16, Double, Float] t
=> TF.Tensor v1 t -- ^ input
-> TF.Tensor v2 Int32 -- ^ filter_sizes
-> TF.Tensor v3 t -- ^ out_backprop
-> TF.Tensor TF.Build t -- ^ output
conv2DBackpropFilter = conv2DBackpropFilter' id PaddingValid ChannelLast
conv2DBackpropFilter' :: TF.OneOf '[Word16, Double, Float] t
=> TF.OpParams
-> Padding
-> DataFormat
-> TF.Tensor v1 t -- ^ input
-> TF.Tensor v2 Int32 -- ^ filter_sizes
-> TF.Tensor v3 t -- ^ out_backprop
-> TF.Tensor TF.Build t -- ^ output
conv2DBackpropFilter' params padding dataformat = TF.conv2DBackpropFilter'
(params . (TF.opAttr "data_format" .~ dataFormat2D dataformat))
(paddingToByteString padding)
-- | 2D convolution backpropagation input with default parameters.
conv2DBackpropInput :: TF.OneOf '[Word16, Double, Float] t
=> TF.Tensor v1 Int32 -- ^ input_sizes
-> TF.Tensor v2 t -- ^ filter
-> TF.Tensor v3 t -- ^ out_backprop
-> TF.Tensor TF.Build t -- ^ output
conv2DBackpropInput = conv2DBackpropInput' id PaddingValid ChannelLast
conv2DBackpropInput' :: TF.OneOf '[Word16, Double, Float] t
=> TF.OpParams
-> Padding
-> DataFormat
-> TF.Tensor v1 Int32 -- ^ input_sizes
-> TF.Tensor v2 t -- ^ filter
-> TF.Tensor v3 t -- ^ out_backprop
-> TF.Tensor TF.Build t -- ^ output
conv2DBackpropInput' params padding dataformat = TF.conv2DBackpropInput'
(params . (TF.opAttr "data_format" .~ dataFormat2D dataformat))
(paddingToByteString padding)
-- | 3D Convolution with default parameters.
conv3D :: TF.OneOf '[Word16, Double, Float] t
=> TF.Tensor v1 t -- ^ input
-> TF.Tensor v2 t -- ^ filter
-> TF.Tensor TF.Build t -- ^ output
conv3D = conv3D' id PaddingValid ChannelLast
conv3D' :: TF.OneOf '[Word16, Double, Float] t
=> TF.OpParams
-> Padding
-> DataFormat
-> TF.Tensor v1 t -- ^ input
-> TF.Tensor v2 t -- ^ filter
-> TF.Tensor TF.Build t -- ^ output
conv3D' params padding dataformat = TF.conv3D'
(params . (TF.opAttr "data_format" .~ dataFormat3D dataformat))
(paddingToByteString padding)
-- | 3D convolution backpropagation filter with default parameters.
conv3DBackpropFilter :: TF.OneOf '[Word16, Double, Float] t
=> TF.Tensor v1 t -- ^ input
-> TF.Tensor v2 t -- ^ filter
-> TF.Tensor v3 t -- ^ out_backprop
-> TF.Tensor TF.Build t -- ^ output
conv3DBackpropFilter = conv3DBackpropFilter' id PaddingValid ChannelLast
conv3DBackpropFilter' :: TF.OneOf '[Word16, Double, Float] t
=> TF.OpParams
-> Padding
-> DataFormat
-> TF.Tensor v1 t -- ^ input
-> TF.Tensor v2 t -- ^ filter
-> TF.Tensor v3 t -- ^ out_backprop
-> TF.Tensor TF.Build t -- ^ output
conv3DBackpropFilter' params padding dataformat = TF.conv3DBackpropFilter'
(params . (TF.opAttr "data_format" .~ dataFormat3D dataformat))
(paddingToByteString padding)
-- | 3D convolution backpropagation filter with default parameters.
conv3DBackpropFilterV2 :: TF.OneOf '[Word16, Double, Float] t
=> TF.Tensor v1 t -- ^ input
-> TF.Tensor v2 Int32 -- ^ filter_sizes
-> TF.Tensor v3 t -- ^ out_backprop
-> TF.Tensor TF.Build t -- ^ output
conv3DBackpropFilterV2 = conv3DBackpropFilterV2' id PaddingValid ChannelLast
conv3DBackpropFilterV2' :: TF.OneOf '[Word16, Double, Float] t
=> TF.OpParams
-> Padding
-> DataFormat
-> TF.Tensor v1 t -- ^ input
-> TF.Tensor v2 Int32 -- ^ filter_sizes
-> TF.Tensor v3 t -- ^ out_backprop
-> TF.Tensor TF.Build t -- ^ output
conv3DBackpropFilterV2' params padding dataformat = TF.conv3DBackpropFilterV2'
(params . (TF.opAttr "data_format" .~ dataFormat3D dataformat))
(paddingToByteString padding)
-- | 3D convolution backpropagation input with default parameters.
conv3DBackpropInput :: TF.OneOf '[Word16, Double, Float] t
=> TF.Tensor v1 t -- ^ input
-> TF.Tensor v2 t -- ^ filter
-> TF.Tensor v3 t -- ^ out_backprop
-> TF.Tensor TF.Build t -- ^ output
conv3DBackpropInput = conv3DBackpropInput' id PaddingValid ChannelLast
conv3DBackpropInput' :: TF.OneOf '[Word16, Double, Float] t
=> TF.OpParams
-> Padding
-> DataFormat
-> TF.Tensor v1 t -- ^ input
-> TF.Tensor v2 t -- ^ filter
-> TF.Tensor v3 t -- ^ out_backprop
-> TF.Tensor TF.Build t -- ^ output
conv3DBackpropInput' params padding dataformat = TF.conv3DBackpropInput'
(params . (TF.opAttr "data_format" .~ dataFormat3D dataformat))
(paddingToByteString padding)
-- | 3D convolution backpropagation input with default parameters.
conv3DBackpropInputV2 :: (TF.OneOf '[Word16, Double, Float] t, TF.OneOf '[Int32, Int64] tshape)
=> TF.Tensor v1 tshape -- ^ input_sizes
-> TF.Tensor v2 t -- ^ filter
-> TF.Tensor v3 t -- ^ out_backprop
-> TF.Tensor TF.Build t -- ^ output
conv3DBackpropInputV2 = conv3DBackpropInputV2' id PaddingValid ChannelLast
conv3DBackpropInputV2' :: (TF.OneOf '[Word16, Double, Float] t, TF.OneOf '[Int32, Int64] tshape)
=> TF.OpParams
-> Padding
-> DataFormat
-> TF.Tensor v1 tshape -- ^ input_sizes
-> TF.Tensor v2 t -- ^ filter
-> TF.Tensor v3 t -- ^ out_backprop
-> TF.Tensor TF.Build t -- ^ output
conv3DBackpropInputV2' params padding dataformat = TF.conv3DBackpropInputV2'
(params . (TF.opAttr "data_format" .~ dataFormat3D dataformat))
(paddingToByteString padding)
-- | Depth-wise 2D convolution native with default parameters.
depthwiseConv2dNative :: TF.OneOf '[Word16, Double, Float] t
=> TF.Tensor v1 t -- ^ input
-> TF.Tensor v2 t -- ^ filter
-> TF.Tensor TF.Build t -- ^ output
depthwiseConv2dNative = depthwiseConv2dNative' id PaddingValid ChannelLast
depthwiseConv2dNative' :: TF.OneOf '[Word16, Double, Float] t
=> TF.OpParams
-> Padding
-> DataFormat
-> TF.Tensor v1 t -- ^ input
-> TF.Tensor v2 t -- ^ filter
-> TF.Tensor TF.Build t -- ^ output
depthwiseConv2dNative' params padding dataformat = TF.depthwiseConv2dNative'
(params . (TF.opAttr "data_format" .~ dataFormat2D dataformat))
(paddingToByteString padding)
-- | Depth-wise 2D convolution native backpropagation filter with default parameters.
depthwiseConv2dNativeBackpropFilter :: TF.OneOf '[Word16, Double, Float] t
=> TF.Tensor v1 t -- ^ input
-> TF.Tensor v2 Int32 -- ^ filter_sizes
-> TF.Tensor v3 t -- ^ out_backprop
-> TF.Tensor TF.Build t -- ^ output
depthwiseConv2dNativeBackpropFilter = depthwiseConv2dNativeBackpropFilter' id PaddingValid ChannelLast
depthwiseConv2dNativeBackpropFilter' :: TF.OneOf '[Word16, Double, Float] t
=> TF.OpParams
-> Padding
-> DataFormat
-> TF.Tensor v1 t -- ^ input
-> TF.Tensor v2 Int32 -- ^ filter_sizes
-> TF.Tensor v3 t -- ^ out_backprop
-> TF.Tensor TF.Build t -- ^ output
depthwiseConv2dNativeBackpropFilter' params padding dataformat = TF.depthwiseConv2dNativeBackpropFilter'
(params . (TF.opAttr "data_format" .~ dataFormat2D dataformat))
(paddingToByteString padding)
-- | Depth-wise 2D convolution native backpropagation input with default parameters.
depthwiseConv2dNativeBackpropInput :: TF.OneOf '[Word16, Double, Float] t
=> TF.Tensor v1 Int32 -- ^ input_sizes
-> TF.Tensor v2 t -- ^ input
-> TF.Tensor v3 t -- ^ out_backprop
-> TF.Tensor TF.Build t -- ^ output
depthwiseConv2dNativeBackpropInput = depthwiseConv2dNativeBackpropInput' id PaddingValid ChannelLast
depthwiseConv2dNativeBackpropInput' :: TF.OneOf '[Word16, Double, Float] t
=> TF.OpParams
-> Padding
-> DataFormat
-> TF.Tensor v1 Int32 -- ^ input_sizes
-> TF.Tensor v2 t -- ^ input
-> TF.Tensor v3 t -- ^ out_backprop
-> TF.Tensor TF.Build t -- ^ output
depthwiseConv2dNativeBackpropInput' params padding dataformat = TF.depthwiseConv2dNativeBackpropInput'
(params . (TF.opAttr "data_format" .~ dataFormat2D dataformat))
(paddingToByteString padding)

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@ -678,16 +678,14 @@ opGrad "Transpose" _ [_, toT -> p] [dz] =
opGrad "Conv2D" nodeDef [toT -> x, toT -> y] [dz] =
[ Just $ CoreOps.conv2DBackpropInput'
((opAttr "strides" .~ strides)
. (opAttr "padding" .~ padding)
. (opAttr "use_cudnn_on_gpu" .~ useCudnnOnGpu)
. (opAttr "data_format" .~ dataFormat))
(shape x) y dz
padding (shape x) y dz
, Just $ CoreOps.conv2DBackpropFilter'
((opAttr "strides" .~ strides)
. (opAttr "padding" .~ padding)
. (opAttr "use_cudnn_on_gpu" .~ useCudnnOnGpu)
. (opAttr "data_format" .~ dataFormat))
x (shape y) dz
padding x (shape y) dz
]
where
strides = lookupAttr nodeDef "strides" :: [Int64]
@ -699,16 +697,14 @@ opGrad "Conv2DBackpropInput" nodeDef [_, toT -> x, toT -> y] [dz] =
[ Nothing
, Just $ CoreOps.conv2DBackpropFilter'
((opAttr "strides" .~ strides)
. (opAttr "padding" .~ padding)
. (opAttr "use_cudnn_on_gpu" .~ useCudnnOnGpu)
. (opAttr "data_format" .~ dataFormat))
dz (shape x) y
padding dz (shape x) y
, Just $ CoreOps.conv2D'
((opAttr "strides" .~ strides)
. (opAttr "padding" .~ padding)
. (opAttr "use_cudnn_on_gpu" .~ useCudnnOnGpu)
. (opAttr "data_format" .~ dataFormat))
dz x
padding dz x
]
where
strides = lookupAttr nodeDef "strides" :: [Int64]
@ -719,14 +715,12 @@ opGrad "Conv2DBackpropInput" nodeDef [_, toT -> x, toT -> y] [dz] =
opGrad "DepthwiseConv2dNative" nodeDef [toT -> x, toT -> y] [dz] =
[ Just $ CoreOps.depthwiseConv2dNativeBackpropInput'
((opAttr "strides" .~ strides)
. (opAttr "padding" .~ padding)
. (opAttr "data_format" .~ dataFormat))
(shape x) y dz
padding (shape x) y dz
, Just $ CoreOps.depthwiseConv2dNativeBackpropFilter'
((opAttr "strides" .~ strides)
. (opAttr "padding" .~ padding)
. (opAttr "data_format" .~ dataFormat))
x (shape y) dz
padding x (shape y) dz
]
where
strides = lookupAttr nodeDef "strides" :: [Int64]
@ -737,14 +731,12 @@ opGrad "DepthwiseConv2dNativeBackpropInput" nodeDef [_, toT -> x, toT -> y] [dz]
[ Nothing
, Just $ CoreOps.depthwiseConv2dNativeBackpropFilter'
((opAttr "strides" .~ strides)
. (opAttr "padding" .~ padding)
. (opAttr "data_format" .~ dataFormat))
dz (shape x) y
padding dz (shape x) y
, Just $ CoreOps.depthwiseConv2dNative'
((opAttr "strides" .~ strides)
. (opAttr "padding" .~ padding)
. (opAttr "data_format" .~ dataFormat))
dz x
padding dz x
]
where
strides = lookupAttr nodeDef "strides" :: [Int64]
@ -755,9 +747,8 @@ opGrad "MaxPool" nodeDef [toT -> x] [dz] =
[ Just $ CoreOps.maxPoolGrad'
((opAttr "ksize" .~ ksize)
. (opAttr "strides" .~ strides)
. (opAttr "padding" .~ padding)
. (opAttr "data_format" .~ dataFormat))
x output dz
padding x output dz
]
where
output :: Tensor Build a

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@ -12,6 +12,8 @@
-- See the License for the specific language governing permissions and
-- limitations under the License.
{-# LANGUAGE ConstraintKinds #-}
{-# LANGUAGE DataKinds #-}
{-# LANGUAGE FlexibleContexts #-}
{-# LANGUAGE OverloadedStrings #-}
{-# LANGUAGE RankNTypes #-}
@ -22,11 +24,15 @@ module TensorFlow.Minimize
( Minimizer
, minimizeWith
, gradientDescent
, OneOfAdamDataTypes
, AdamConfig(..)
, adam
, adam'
) where
import Data.Complex (Complex)
import Data.Int (Int8,Int16,Int32,Int64)
import Data.Word (Word8,Word16,Word32,Word64)
import Control.Monad (zipWithM)
import Data.Default (Default(..))
import Data.List (zipWith4)
@ -65,16 +71,19 @@ gradientDescent learningRate params grads = TF.withNameScope "gradientDescent" $
TF.assignAdd param (TF.scalar (-learningRate) `TF.mul` grad)
TF.group =<< zipWithM applyGrad params grads
-- TODO: Support more than Float in adam.
data AdamConfig = AdamConfig
{ adamLearningRate :: Float
, adamBeta1 :: Float
, adamBeta2 :: Float
, adamEpsilon :: Float
data AdamConfig t = AdamConfig
{ adamLearningRate :: t
, adamBeta1 :: t
, adamBeta2 :: t
, adamEpsilon :: t
}
instance Default AdamConfig where
type OneOfAdamDataTypes t =
TF.OneOf '[ Complex Double, Complex Float
, Int16, Int32, Int64, Int8, Word16, Word32, Word64, Word8
, Double, Float] t
instance Fractional t => Default (AdamConfig t) where
-- Recommended defaults from the adam paper.
def = AdamConfig 0.001 0.9 0.999 1e-8
@ -83,10 +92,10 @@ instance Default AdamConfig where
-- See https://arxiv.org/abs/1412.6980.
--
-- NOTE: Currently requires all 'TF.Variable's to have an 'TF.initializedValue'.
adam :: Minimizer Float
adam :: (OneOfAdamDataTypes t, Fractional t) => Minimizer t
adam = adam' def
adam' :: AdamConfig -> Minimizer Float
adam' :: OneOfAdamDataTypes t => AdamConfig t -> Minimizer t
adam' config params grads = TF.withNameScope "adam" $ do
let lr = TF.scalar (adamLearningRate config)
beta1 = TF.scalar (adamBeta1 config)

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@ -89,6 +89,8 @@ module TensorFlow.Ops
, CoreOps.identity'
, CoreOps.matMul
, CoreOps.matMul'
, CoreOps.einsum
, CoreOps.einsum'
, matTranspose
, matTranspose'
, CoreOps.mean

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@ -16,12 +16,13 @@ library
hs-source-dirs: src
exposed-modules: TensorFlow.Gradient
, TensorFlow.Ops
, TensorFlow.Convolution
, TensorFlow.EmbeddingOps
, TensorFlow.Minimize
, TensorFlow.NN
, TensorFlow.Queue
, TensorFlow.Variable
build-depends: proto-lens == 0.6.*
build-depends: proto-lens == 0.7.*
, base >= 4.7 && < 5
, bytestring
, fgl

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@ -32,7 +32,8 @@ import Control.Monad(forM_, replicateM, zipWithM)
import Control.Monad.IO.Class (liftIO)
import qualified TensorFlow.Core as TF
import qualified TensorFlow.GenOps.Core as TF (conv2DBackpropInput', max, maximum, resizeBilinear', tile, pad, batchToSpaceND, spaceToBatchND, squeeze, sqrt, slice, shape, diag, depthwiseConv2dNative', depthwiseConv2dNativeBackpropInput', batchMatMul, batchMatMul', conjugateTranspose)
import qualified TensorFlow.GenOps.Core as TF (max, maximum, resizeBilinear', tile, pad, batchToSpaceND, spaceToBatchND, squeeze, sqrt, slice, shape, diag, batchMatMul, batchMatMul', conjugateTranspose)
import qualified TensorFlow.Convolution as TF
import qualified TensorFlow.Gradient as TF
import qualified TensorFlow.Ops as TF hiding (zeroInitializedVariable, shape)
import qualified TensorFlow.Output as TF
@ -42,7 +43,6 @@ import qualified TensorFlow.Variable as TF
import Proto.Tensorflow.Core.Framework.Graph_Fields (node)
import Proto.Tensorflow.Core.Framework.NodeDef_Fields (op)
import qualified Data.ByteString.Char8 as BS
import TensorFlow.Session (SessionT)
testGradientSimple :: Test
@ -715,11 +715,8 @@ testConv2DBackpropInputGrad = testCase "testConv2DBackpropInputGrad" $ do
let filterShape = TF.vector [2, 2, 1, 1 :: Int32] -- [fh, fw, inc, out]
filter' <- TF.render $ TF.fill filterShape (TF.scalar (1::Float))
let y = TF.conv2DBackpropInput'
( (TF.opAttr "strides" .~ [1::Int64, 1, 1, 1])
. (TF.opAttr "padding" .~ (BS.pack "VALID"))
. (TF.opAttr "data_format" .~ (BS.pack "NHWC"))
)
conv_input_shape filter' x
(TF.opAttr "strides" .~ [1::Int64, 1, 1, 1])
TF.PaddingValid TF.ChannelLast conv_input_shape filter' x
[dx] <- TF.gradients y [x]
TF.run (dx, TF.shape dx, TF.shape x)
@ -735,11 +732,8 @@ testDepthwiseConv2dGrad = testCase "testDepthwiseConv2dGrad" $ do
let filterShape = TF.vector [2, 2, 1, 1 :: Int32]
filter' <- TF.render $ TF.fill filterShape (TF.scalar (1 :: Float))
let y = TF.depthwiseConv2dNative'
( (TF.opAttr "strides" .~ [1 :: Int64, 1, 1, 1])
. (TF.opAttr "padding" .~ (BS.pack "VALID"))
. (TF.opAttr "data_format" .~ (BS.pack "NHWC"))
)
x filter'
(TF.opAttr "strides" .~ [1 :: Int64, 1, 1, 1])
TF.PaddingValid TF.ChannelLast x filter'
[dx] <- TF.gradients y [x]
TF.run (dx, TF.shape dx, TF.shape x)
@ -757,11 +751,8 @@ testDepthwiseConv2dBackpropInputGrad = testCase "testDepthwiseConv2dBackpropInpu
let filterShape = TF.vector [2, 2, 1, 1 :: Int32]
filter' <- TF.render $ TF.fill filterShape (TF.scalar (1 :: Float))
let y = TF.depthwiseConv2dNativeBackpropInput'
( (TF.opAttr "strides" .~ [1 :: Int64, 1, 1, 1])
. (TF.opAttr "padding" .~ (BS.pack "VALID"))
. (TF.opAttr "data_format" .~ (BS.pack "NHWC"))
)
conv_input_shape filter' x
(TF.opAttr "strides" .~ [1 :: Int64, 1, 1, 1])
TF.PaddingValid TF.ChannelLast conv_input_shape filter' x
[dx] <- TF.gradients y [x]
TF.run (dx, TF.shape dx, TF.shape x)

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@ -104,6 +104,20 @@ testRereadRef = testCase "testReRunAssign" $ TF.runSession $ do
f1 <- TF.run w
liftIO $ (0.0, 0.1) @=? (TF.unScalar f0, TF.unScalar f1)
-- | Test Einstein summation.
testEinsum :: Test
testEinsum = testCase "testEinsum" $ TF.runSession $ do
-- Matrix multiply
let matA = TF.constant (TF.Shape [3,3]) [1..9 :: Float]
let matB = TF.constant (TF.Shape [3,1]) [1..3 :: Float]
matMulOut <- TF.run $ TF.matMul matA matB
einsumOut <- TF.run $ TF.einsum "ij,jk->ik" [matA,matB]
liftIO $ (matMulOut :: V.Vector Float) @=? einsumOut
-- Hadamard multiply
hadMulOut <- TF.run $ TF.mul matA matA
einsumHad <- TF.run $ TF.einsum "ij,ij->ij" [matA,matA]
liftIO $ (hadMulOut :: V.Vector Float) @=? einsumHad
main :: IO ()
main = defaultMain
[ testSaveRestore
@ -112,4 +126,5 @@ main = defaultMain
, testPlaceholderCse
, testScalarFeedCse
, testRereadRef
, testEinsum
]

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@ -73,6 +73,8 @@ library
, Proto.Tensorflow.Core.Protobuf.ControlFlow_Fields
, Proto.Tensorflow.Core.Protobuf.Debug
, Proto.Tensorflow.Core.Protobuf.Debug_Fields
, Proto.Tensorflow.Core.Protobuf.DeviceFilters
, Proto.Tensorflow.Core.Protobuf.ErrorCodes
, Proto.Tensorflow.Core.Protobuf.MetaGraph
, Proto.Tensorflow.Core.Protobuf.MetaGraph_Fields
, Proto.Tensorflow.Core.Protobuf.NamedTensor
@ -83,12 +85,16 @@ library
, Proto.Tensorflow.Core.Protobuf.RewriterConfig_Fields
, Proto.Tensorflow.Core.Protobuf.SavedModel
, Proto.Tensorflow.Core.Protobuf.SavedModel_Fields
, Proto.Tensorflow.Core.Protobuf.SavedObjectGraph
, Proto.Tensorflow.Core.Protobuf.Saver
, Proto.Tensorflow.Core.Protobuf.Saver_Fields
, Proto.Tensorflow.Core.Protobuf.Struct
, Proto.Tensorflow.Core.Protobuf.TensorBundle
, Proto.Tensorflow.Core.Protobuf.TensorBundle_Fields
, Proto.Tensorflow.Core.Protobuf.TensorflowServer
, Proto.Tensorflow.Core.Protobuf.TensorflowServer_Fields
, Proto.Tensorflow.Core.Protobuf.TrackableObjectGraph
, Proto.Tensorflow.Core.Protobuf.VerifierConfig
, Proto.Tensorflow.Core.Util.Event
, Proto.Tensorflow.Core.Util.Event_Fields
, Proto.Tensorflow.Core.Util.MemmappedFileSystem
@ -125,6 +131,7 @@ library
, Proto.Tensorflow.Core.Framework.OpDef_Fields
, Proto.Tensorflow.Core.Framework.ResourceHandle
, Proto.Tensorflow.Core.Framework.ResourceHandle_Fields
, Proto.Tensorflow.Core.Protobuf.SavedObjectGraph
, Proto.Tensorflow.Core.Framework.StepStats
, Proto.Tensorflow.Core.Framework.StepStats_Fields
, Proto.Tensorflow.Core.Framework.Summary
@ -152,6 +159,8 @@ library
, Proto.Tensorflow.Core.Protobuf.ControlFlow_Fields
, Proto.Tensorflow.Core.Protobuf.Debug
, Proto.Tensorflow.Core.Protobuf.Debug_Fields
, Proto.Tensorflow.Core.Protobuf.DeviceFilters
, Proto.Tensorflow.Core.Protobuf.ErrorCodes
, Proto.Tensorflow.Core.Protobuf.MetaGraph
, Proto.Tensorflow.Core.Protobuf.MetaGraph_Fields
, Proto.Tensorflow.Core.Protobuf.NamedTensor
@ -162,12 +171,16 @@ library
, Proto.Tensorflow.Core.Protobuf.RewriterConfig_Fields
, Proto.Tensorflow.Core.Protobuf.SavedModel
, Proto.Tensorflow.Core.Protobuf.SavedModel_Fields
, Proto.Tensorflow.Core.Protobuf.SavedObjectGraph
, Proto.Tensorflow.Core.Protobuf.Saver
, Proto.Tensorflow.Core.Protobuf.Saver_Fields
, Proto.Tensorflow.Core.Protobuf.Struct
, Proto.Tensorflow.Core.Protobuf.TensorBundle
, Proto.Tensorflow.Core.Protobuf.TensorBundle_Fields
, Proto.Tensorflow.Core.Protobuf.TensorflowServer
, Proto.Tensorflow.Core.Protobuf.TensorflowServer_Fields
, Proto.Tensorflow.Core.Protobuf.TrackableObjectGraph
, Proto.Tensorflow.Core.Protobuf.VerifierConfig
, Proto.Tensorflow.Core.Util.Event
, Proto.Tensorflow.Core.Util.Event_Fields
, Proto.Tensorflow.Core.Util.MemmappedFileSystem
@ -176,9 +189,9 @@ library
, Proto.Tensorflow.Core.Util.SavedTensorSlice_Fields
, Proto.Tensorflow.Core.Util.TestLog
, Proto.Tensorflow.Core.Util.TestLog_Fields
build-depends: proto-lens == 0.6.*
, proto-lens-runtime == 0.6.*
, proto-lens-protobuf-types == 0.6.*
build-depends: proto-lens == 0.7.*
, proto-lens-runtime == 0.7.*
, proto-lens-protobuf-types == 0.7.*
, base >= 4.7 && < 5
default-language: Haskell2010
include-dirs: .

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@ -36,7 +36,7 @@ library
, TensorFlow.Types
other-modules: TensorFlow.Internal.Raw
build-tools: c2hs
build-depends: proto-lens == 0.6.*
build-depends: proto-lens == 0.7.*
, tensorflow-proto == 0.2.*
, base >= 4.7 && < 5
, async

@ -1 +1 @@
Subproject commit 6612da89516247503f03ef76e974b51a434fb52e
Subproject commit b36436b087bd8e8701ef51718179037cccdfc26e