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Gradient of Conv2DBackpropInput

This commit is contained in:
Jarl Christian Berentsen 2017-10-11 11:28:02 +02:00
parent d8bf349962
commit e30d263750
3 changed files with 49 additions and 2 deletions

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@ -650,6 +650,27 @@ opGrad "Conv2D" nodeDef [toT -> x, toT -> y] [dz] =
useCudnnOnGpu = lookupAttr nodeDef "use_cudnn_on_gpu" :: Bool
dataFormat = lookupAttr nodeDef "data_format" :: ByteString
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
, Just $ CoreOps.conv2D'
((opAttr "strides" .~ strides)
. (opAttr "padding" .~ padding)
. (opAttr "use_cudnn_on_gpu" .~ useCudnnOnGpu)
. (opAttr "data_format" .~ dataFormat))
dz x
]
where
strides = lookupAttr nodeDef "strides" :: [Int64]
padding = lookupAttr nodeDef "padding" :: ByteString
useCudnnOnGpu = lookupAttr nodeDef "use_cudnn_on_gpu" :: Bool
dataFormat = lookupAttr nodeDef "data_format" :: ByteString
opGrad "MaxPool" nodeDef [toT -> x] [dz] =
[ Just $ CoreOps.maxPoolGrad'
((opAttr "ksize" .~ ksize)
@ -779,6 +800,7 @@ numOutputs o =
"Const" -> 1
"Concat" -> 1
"Conv2D" -> 1
"Conv2DBackpropInput" -> 1
"Div" -> 1
"DynamicStitch" -> 1
"DynamicPartition" ->

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@ -188,6 +188,7 @@ Test-Suite GradientTest
hs-source-dirs: tests
build-depends: HUnit
, base
, bytestring
, proto-lens
, lens-family
, random

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@ -32,7 +32,7 @@ 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 (max, tile, maximum)
import qualified TensorFlow.GenOps.Core as TF (conv2DBackpropInput', max, maximum, tile)
import qualified TensorFlow.Gradient as TF
import qualified TensorFlow.Ops as TF hiding (zeroInitializedVariable)
import qualified TensorFlow.Output as TF
@ -42,6 +42,8 @@ import qualified TensorFlow.Variable as TF
import Proto.Tensorflow.Core.Framework.Graph (node)
import Proto.Tensorflow.Core.Framework.NodeDef (op)
import qualified Data.ByteString.Char8 as BS
testGradientSimple :: Test
testGradientSimple = testCase "testGradientSimple" $ do
let grads = do
@ -313,7 +315,6 @@ testTile2DGrad = testCase "testTileGrad2D" $ do
shapeX @=? (shapeDX :: V.Vector Int32)
V.fromList [6, 6, 6, 6, 6, 6::Float] @=? (dx :: V.Vector Float)
matMulGradient :: Test
matMulGradient = testCase "matMulGradients" $ do
@ -388,6 +389,28 @@ transAttrs :: (TF.Attribute a,
transAttrs a b =
(TF.opAttr "transpose_a" .~ a) . (TF.opAttr "transpose_b" .~ b)
testConv2DBackpropInputGrad :: Test
testConv2DBackpropInputGrad = testCase "testConv2DBackpropInputGrad" $ do
(dx, shapeDX, shapeX) <- TF.runSession $ do
let conv_input_shape = TF.vector [1, 2, 2, 1 :: Int32] -- [batch, h, w, in_channels]
let conv_out_shape = TF.vector [1, 1, 1, 1 :: Int32] -- [batch, h, w, out_channels]
x <- TF.render $ TF.fill conv_out_shape (TF.scalar (1::Float))
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
[dx] <- TF.gradients y [x]
TF.run (dx, TF.shape dx, TF.shape x)
shapeX @=? (shapeDX :: V.Vector Int32)
V.fromList [4::Float] @=? (dx :: V.Vector Float)
main :: IO ()
main = defaultMain
[ testGradientSimple
@ -413,4 +436,5 @@ main = defaultMain
, matMulTransposeGradient (False, True)
, matMulTransposeGradient (True, False)
, matMulTransposeGradient (True, True)
, testConv2DBackpropInputGrad
]