Add gradient for slice function (#234)

tensorflow-ops/src/TensorFlow/Gradient.hs

@@ -710,6 +710,27 @@ opGrad "Pad" _ [toT -> x, toT -> padPattern] [dz] =
     gradientSliceBegin = CoreOps.reshape padPatternSliced rankx
     gradientSliceSize = shape (x :: Tensor Build Float)
 
+-- Gradient for Slice
+-- Create an Nx2 padding where N is the rank of (grad of) Slice and the first
+-- column represents how many zeros are to be prepended for each dimension, and the second
+-- column indicates how many zeros are appended.
+-- The number of zeros to prepend is the shape of the beginvec.
+-- The number of zeros to append is the shape of the inputvec
+-- elementwise-subtracted by both the beginvec and sizevec.
+-- Some more reshaping is needed to assemble this tensor with the
+-- right dimensions.
+opGrad "Slice" _ [toT -> inputvec, toT -> beginvec, _] [dz] =
+   [Just $ CoreOps.pad dz paddings, Nothing, Nothing]
+  where
+    v1 = vector [1 :: Int32]
+    inputRank' = CoreOps.rank (inputvec :: Tensor Build Float)
+    -- For some reason inputRank' has an empty shape
+    inputRank = CoreOps.reshape inputRank' v1
+    padShape = CoreOps.concat 0 [inputRank, v1]
+    beforePad = CoreOps.reshape beginvec padShape
+    afterPad = CoreOps.reshape (shape inputvec - shape dz - beginvec) padShape
+    paddings = CoreOps.concat 1 [beforePad, afterPad]
+
 -- 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]
@@ -862,6 +883,7 @@ numOutputs o =
         "Reshape" -> 1
         "Select" -> 1
         "Size" -> 1
+        "Slice" -> 1
         "SoftmaxCrossEntropyWithLogits" -> 2
         "SpaceToBatchND" -> 1
         "SparseSegmentSum" -> 1

tensorflow-ops/tests/GradientTest.hs

@@ -32,9 +32,9 @@ 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, pad, batchToSpaceND, spaceToBatchND, squeeze, sqrt)
+import qualified TensorFlow.GenOps.Core as TF (conv2DBackpropInput', max, maximum, tile, pad, batchToSpaceND, spaceToBatchND, squeeze, sqrt, slice, shape)
 import qualified TensorFlow.Gradient as TF
-import qualified TensorFlow.Ops as TF hiding (zeroInitializedVariable)
+import qualified TensorFlow.Ops as TF hiding (zeroInitializedVariable, shape)
 import qualified TensorFlow.Output as TF
 import qualified TensorFlow.Types as TF
 import qualified TensorFlow.Variable as TF
@@ -324,6 +324,7 @@ testPad =
     V.fromList [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] @=? dx
     V.fromList [2, 2, 3] @=? s
 
+
 testSqrt :: Test
 testSqrt = testCase "testSqrt" $ do
     [dx] <- TF.runSession $ do
@@ -332,6 +333,25 @@ testSqrt = testCase "testSqrt" $ do
         TF.gradients y [x] >>= TF.run
     V.fromList [2] @=? dx
 
+testSlice :: Test
+testSlice =
+  testCase "testSlice" $ do
+    ([dx], [s]) <-
+      TF.runSession $ do
+        (x :: TF.Tensor TF.Value Float) <- TF.render $ TF.zeros $ TF.Shape [2, 3, 4 :: Int64]
+        (z :: TF.Tensor TF.Value Float) <- TF.render $ TF.zeros $ TF.Shape [1, 2, 2 :: Int64]
+        let y = TF.slice x (TF.constant (TF.Shape [3]) [1, 1, 1 :: Int32]) (TF.shape z)
+        calculateGradWithShape y x
+    let expected =
+         [0, 0, 0, 0,
+          0, 0, 0, 0,
+          0, 0, 0, 0,
+          0, 0, 0, 0,
+          0, 1, 1, 0,
+          0, 1, 1, 0]
+    V.fromList expected @=? dx
+    V.fromList [2, 3, 4] @=? s
+
 testBatchToSpaceND :: Test
 testBatchToSpaceND =
   testCase "testBatchToSpaceND" $ do
@@ -526,6 +546,7 @@ main = defaultMain
             , testReshape
             , testPad
             , testSqrt
+            , testSlice
             , testBatchToSpaceND
             , testSpaceToBatchND
             , testSqueeze