"Slice",
    "Snapshot",
    "SpaceToBatch",
    "SpaceToBatchND",
    "SpaceToDepth",
    "Split",
    "SplitV",
    "Squeeze",
    "StopGradient",
    "StridedSlice",
    "StridedSliceGrad",
    "TensorScatterAdd",
    "TensorScatterMax",
    "TensorScatterMin",
    "TensorScatterSub",
    "TensorStridedSliceUpdate",
    "Tile",
    "TileGrad",
    "Transpose",
    "Unique",

//  tf.StridedSliceGrad
//===--------------------------------------------------------------------===//

func.func @stridedSliceGrad(%dy: tensor<4x8xf32>, %begin: tensor<2xi64>, %end: tensor<2xi64>, %strides: tensor<2xi64>, %shape: tensor<2xi64>) -> tensor<?x?xf32> {
  // CHECK: tf.StridedSliceGrad

  TF_RETURN_IF_ERROR(
      GetNodeAttr(op.node()->attrs(), "shrink_axis_mask", &shrink_axis_mask));
  grad_outputs->push_back(
      StridedSliceGrad(scope, x, begin, end, strides, grad_inputs[0],
                       StridedSliceGrad::BeginMask(begin_mask)
                           .EndMask(end_mask)
                           .EllipsisMask(ellipsis_mask)
                           .NewAxisMask(new_axis_mask)

  auto paddings = Const(scope_, {{1, 1}, {2, 2}});
  TensorShape y_shape({2, 3});
  auto y = MirrorPadGrad(scope_, x, paddings, "SYMMETRIC");
  RunTest(x, x_shape, y, y_shape);
}

TEST_F(ArrayGradTest, StridedSliceGrad) {
  TensorShape x_shape({6, 4, 4});
  auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x_shape));

  // y = x[2:6:2, 1:3, 1:3]
  auto y = StridedSlice(scope_, x, {2, 1, 1}, {6, 3, 3}, {2, 1, 1});

  func.return %1 : tensor<?x2x5xf32>
}

//===----------------------------------------------------------------------===//
// tf.StridedSliceGrad legalization
//===----------------------------------------------------------------------===//

// -----

// CHECK-LABEL: strided_slice_grad
// CHECK-SAME: [[GRAD:%.*]]: tensor<4x16x1022xf32>

      "ConcatOffset", "Const", "MirrorPad", "MirrorPadGrad", "Pack", "Pad",
      "PadV2", "Reverse", "ReverseV2", "ReverseSequence", "Slice", "Split",
      "SplitV", "StridedSlice", "StridedSliceGrad",
      "ResourceStridedSliceAssign", "Tile", "Transpose", "InvertPermutation",
      "Unpack", "DeviceIndex", "TensorStridedSliceUpdate", "XlaConcatND",
      "XlaSplitND",
     }}};
  // clang-format on

                                    input_ty, rewriter);
  }
};

// Converts tf.StridedSliceGrad to HLO reshape, reverse and padding ops.
//
// tf.StridedSlice is taking slice of the input tensor. tf.StridedSliceGrad does
// the reverse: it propagates the graident for the sliced tensor to the original

      ::llvm::SmallVectorImpl<int64_t> *slice_end,
      ::llvm::SmallVectorImpl<int64_t> *slice_stride);
  }];
}

def TF_StridedSliceGradOp : TF_Op<"StridedSliceGrad", [Pure]> {
  let summary = "Returns the gradient of `StridedSlice`.";

  let description = [{
Since `StridedSlice` cuts out pieces of its `input` which is size