Add gradient for tensorflow::ops::Fill

See https://github.com/tensorflow/tensorflow/issues/20926

2 files changed, 26 insertions, 0 deletions

diff --git a/tensorflow/cc/gradients/array_grad.cc b/tensorflow/cc/gradients/array_grad.cc
index b353accddc..e9173227aa 100644
--- a/tensorflow/cc/gradients/array_grad.cc
+++ b/tensorflow/cc/gradients/array_grad.cc
@@ -120,6 +120,24 @@ Status SplitGrad(const Scope& scope, const Operation& op,
 }
 REGISTER_GRADIENT_OP("Split", SplitGrad);
 
+Status FillGrad(const Scope& scope, const Operation& op,
+                const std::vector<Output>& grad_inputs,
+                std::vector<Output>* grad_outputs) {
+  // y = fill(fill_shape, x)
+  // No gradient returned for the fill_shape argument.
+  grad_outputs->push_back(NoGradient());
+  // The gradient for x (which must be a scalar) is just the sum of
+  // all the gradients from the shape it fills.
+  // We use ReduceSum to implement this, which needs an argument providing
+  // the indices of all the dimensions of the incoming gradient.
+  // grad(x) = reduce_sum(grad(y), [0..rank(grad(y))])
+  auto all_dims = Range(scope, Const(scope, 0), Rank(scope, grad_inputs[0]),
+                        Const(scope, 1));
+  grad_outputs->push_back(ReduceSum(scope, grad_inputs[0], all_dims));
+  return scope.status();
+}
+REGISTER_GRADIENT_OP("Fill", FillGrad);
+
 Status DiagGrad(const Scope& scope, const Operation& op,
                 const std::vector<Output>& grad_inputs,
                 std::vector<Output>* grad_outputs) {
diff --git a/tensorflow/cc/gradients/array_grad_test.cc b/tensorflow/cc/gradients/array_grad_test.cc
index d09275b648..f41de3dc20 100644
--- a/tensorflow/cc/gradients/array_grad_test.cc
+++ b/tensorflow/cc/gradients/array_grad_test.cc
@@ -108,6 +108,14 @@ TEST_F(ArrayGradTest, SplitGrad) {
   RunTest({x}, {x_shape}, y.output, {y_shape, y_shape});
 }
 
+TEST_F(ArrayGradTest, FillGrad) {
+  TensorShape x_shape({});
+  auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x_shape));
+  TensorShape y_shape({2, 5, 3});
+  auto y = Fill(scope_, {2, 5, 3}, x);
+  RunTest(x, x_shape, y, y_shape);
+}
+
 TEST_F(ArrayGradTest, DiagGrad) {
   TensorShape x_shape({5, 2});
   auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x_shape));