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-rw-r--r--tensorflow/cc/gradients/math_grad_test.cc8
1 files changed, 4 insertions, 4 deletions
diff --git a/tensorflow/cc/gradients/math_grad_test.cc b/tensorflow/cc/gradients/math_grad_test.cc
index 88aef1fab4..c16938322c 100644
--- a/tensorflow/cc/gradients/math_grad_test.cc
+++ b/tensorflow/cc/gradients/math_grad_test.cc
@@ -33,6 +33,7 @@ using ops::AddN;
using ops::BatchMatMul;
using ops::Const;
using ops::Div;
+using ops::DivNoNan;
using ops::MatMul;
using ops::Max;
using ops::Maximum;
@@ -48,7 +49,6 @@ using ops::SegmentSum;
using ops::SquaredDifference;
using ops::Sub;
using ops::Sum;
-using ops::UnsafeDiv;
// TODO(andydavis) Test gradient function against numeric gradients output.
// TODO(andydavis) As more gradients are added move common test functions
@@ -854,13 +854,13 @@ TEST_F(NaryGradTest, RealDiv) {
RunTest({x}, {x_shape}, {y}, {x_shape});
}
-TEST_F(NaryGradTest, UnsafeDiv) {
+TEST_F(NaryGradTest, DivNoNan) {
{
TensorShape x_shape({3, 2, 5});
const auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x_shape));
// Test x / (1 + |x|) rather than x_1 / x_2 to avoid triggering large
// division errors in the numeric estimator used by the gradient checker.
- const auto y = UnsafeDiv(
+ const auto y = DivNoNan(
scope_, x, Add(scope_, Const<float>(scope_, 1), Abs(scope_, x)));
RunTest({x}, {x_shape}, {y}, {x_shape});
}
@@ -868,7 +868,7 @@ TEST_F(NaryGradTest, UnsafeDiv) {
// Return 0 gradient (rather than NaN) for division by zero.
const auto x = Placeholder(scope_, DT_FLOAT);
const auto zero = Const<float>(scope_, 0.0);
- const auto y = UnsafeDiv(scope_, x, zero);
+ const auto y = DivNoNan(scope_, x, zero);
std::vector<Output> grad_outputs;
TF_EXPECT_OK(AddSymbolicGradients(scope_, {y}, {x}, &grad_outputs));