Added support for the gradient of the pad function.

tensorflow-ops/src/TensorFlow/Gradient.hs

@@ -20,6 +20,7 @@
 {-# LANGUAGE ScopedTypeVariables #-}
 {-# LANGUAGE TypeFamilies #-}
 {-# LANGUAGE ViewPatterns #-}
+{-# LANGUAGE TypeApplications #-}
 
 module TensorFlow.Gradient
     ( GradientCompatible
@@ -693,6 +694,29 @@ opGrad "MaxPool" nodeDef [toT -> x] [dz] =
 
 opGrad "Reshape" _ [toT -> x, _] [dz] = [Just $ reshape dz $ shape (x :: Tensor Build a), Nothing]
 opGrad "ExpandDims" n xs@[toT -> _, _] dzs@[_] = opGrad "Reshape" n xs dzs
+opGrad "Squeeze" _ [toT -> x] [dz] = [Just $ reshape dz $ shape (x :: Tensor Build a)]
+opGrad "Pad" _ [toT -> x, toT -> padPattern] [dz] =
+  [Just $ CoreOps.slice dz gradientSliceBegin gradientSliceSize, Nothing]
+  where
+    v1 = vector [1]
+     -- For some reason rankx' has an empty shape
+    rankx' = CoreOps.rank (x :: Tensor Build Float)
+    rankx = CoreOps.reshape rankx' v1
+    -- Size of column that is sliced from pad pattern
+    padPatternSliceSize = CoreOps.concat 0 [rankx, v1]
+    padPatternSliceBegin = vector [0, 0]
+    padPatternSliced :: Tensor Build Int32 = CoreOps.slice padPattern padPatternSliceBegin padPatternSliceSize
+    -- The slice of the pad pattern has the same rank as the pad pattern itself
+    gradientSliceBegin = CoreOps.reshape padPatternSliced rankx
+    gradientSliceSize = shape (x :: Tensor Build Float)
+
+-- TODO: This could be either Int32 or Int64.
+opGrad "BatchToSpaceND" _ [_, toT @Int32 -> blockShape, toT @Int32 -> crops] [dz] =
+  [Just $ CoreOps.spaceToBatchND dz blockShape crops, Nothing, Nothing]
+
+-- TODO: This could be either Int32 or Int64.
+opGrad "SpaceToBatchND" _ [_, toT @Int32 -> blockShape, toT @Int32 -> paddings] [dz] =
+  [Just $ CoreOps.batchToSpaceND dz blockShape paddings, Nothing, Nothing]
 
 opGrad "OneHot" _ _ _ = [Nothing, Nothing, Nothing, Nothing]
 opGrad "TruncatedNormal" _ _ _ = [Nothing]
@@ -800,6 +824,7 @@ numOutputs o =
         "Abs" -> 1
         "Add" -> 1
         "AddN" -> 1
+        "BatchToSpaceND" -> 1
         "Cast" -> 1
         "Const" -> 1
         "Concat" -> 1
@@ -823,6 +848,7 @@ numOutputs o =
         "Min" -> 1
         "Mul" -> 1
         "Neg" -> 1
+        "Pad" -> 1
         "Placeholder" -> 1
         "OneHot" -> 1
         "ReadVariableOp" -> 1
@@ -833,8 +859,10 @@ numOutputs o =
         "Select" -> 1
         "Size" -> 1
         "SoftmaxCrossEntropyWithLogits" -> 2
-        "Square" -> 1
+        "SpaceToBatchND" -> 1
         "SparseSegmentSum" -> 1
+        "Square" -> 1
+        "Squeeze" -> 1
         "Sub" -> 1
         "Sum" -> 1
         "Tanh" -> 1

tensorflow-ops/tests/GradientTest.hs

@@ -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 (conv2DBackpropInput', max, maximum, tile)
+import qualified TensorFlow.GenOps.Core as TF (conv2DBackpropInput', max, maximum, tile, pad, batchToSpaceND, spaceToBatchND, squeeze)
 import qualified TensorFlow.Gradient as TF
 import qualified TensorFlow.Ops as TF hiding (zeroInitializedVariable)
 import qualified TensorFlow.Output as TF
@@ -313,6 +313,54 @@ testReshape =
     V.fromList [1, 1, 1, 1] @=? dx
     V.fromList [2, 2] @=? s
 
+testPad :: Test
+testPad =
+  testCase "testPad" $ do
+    ([dx], [s]) <-
+      TF.runSession $ do
+        (x :: TF.Tensor TF.Value Float) <- TF.render $ TF.zeros $ TF.Shape [2, 2, 3 :: Int64]
+        let y = TF.pad x $ TF.constant (TF.Shape [3, 2]) [1, 4, 1, 1, 2, 3 :: Int32]
+        calculateGradWithShape y x
+    V.fromList [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] @=? dx
+    V.fromList [2, 2, 3] @=? s
+
+testBatchToSpaceND :: Test
+testBatchToSpaceND =
+  testCase "testBatchToSpaceND" $ do
+    ([dx], [s]) <-
+      TF.runSession $ do
+        (x :: TF.Tensor TF.Value Float) <- TF.render $ TF.constant (TF.Shape [4, 1, 1, 1 :: Int64]) [1, 2, 3, 4]
+        shape  <- TF.render $ TF.vector [2, 2 :: Int32]
+        crops  <- TF.render $ TF.constant (TF.Shape [2, 2]) [0, 0, 0, 0 :: Int32]
+        let y = TF.batchToSpaceND x shape crops
+        calculateGradWithShape y x
+    V.fromList [1, 1, 1, 1] @=? dx
+    V.fromList [4, 1, 1, 1] @=? s
+
+testSpaceToBatchND :: Test
+testSpaceToBatchND =
+  testCase "testSpaceToBatchND" $ do
+    ([dx], [s]) <-
+      TF.runSession $ do
+        (x :: TF.Tensor TF.Value Float) <- TF.render $ TF.constant (TF.Shape [1, 2, 2, 1 :: Int64]) [1, 2, 3, 4]
+        shape  <- TF.render $ TF.vector [2, 2 :: Int32]
+        paddings  <- TF.render $ TF.constant (TF.Shape [2, 2]) [0, 0, 0, 0 :: Int32]
+        let y = TF.spaceToBatchND x shape paddings
+        calculateGradWithShape y x
+    V.fromList [1, 1, 1, 1] @=? dx
+    V.fromList [1, 2, 2, 1] @=? s
+
+testSqueeze :: Test
+testSqueeze =
+  testCase "testSqueeze" $ do
+    ([dx], [s]) <-
+      TF.runSession $ do
+        (x :: TF.Tensor TF.Value Float) <- TF.render $ TF.zeros $ TF.Shape [1, 2, 3 :: Int64]
+        let y = TF.squeeze x
+        calculateGradWithShape y x
+    V.fromList [1, 1, 1, 1, 1, 1] @=? dx
+    V.fromList [1, 2, 3] @=? s
+
 calculateGradWithShape :: TF.Tensor TF.Build Float -> TF.Tensor TF.Value Float -> SessionT IO ([V.Vector Float], [V.Vector Int32])
 calculateGradWithShape y x = do
   gs <- TF.gradients y [x]
@@ -468,6 +516,10 @@ main = defaultMain
             , testTanhGrad
             , testExpandDims
             , testReshape
+            , testPad
+            , testBatchToSpaceND
+            , testSpaceToBatchND
+            , testSqueeze
             , testFillGrad
             , testTileGrad
             , testTile2DGrad
@@ -478,4 +530,4 @@ main = defaultMain
             , matMulTransposeGradient (True, False)
             , matMulTransposeGradient (True, True)
             , testConv2DBackpropInputGrad
-            ]
+            ]