diff options
Diffstat (limited to 'tensorflow/cc')
-rw-r--r-- | tensorflow/cc/gradients/math_grad.cc | 15 | ||||
-rw-r--r-- | tensorflow/cc/gradients/math_grad_test.cc | 32 |
2 files changed, 47 insertions, 0 deletions
diff --git a/tensorflow/cc/gradients/math_grad.cc b/tensorflow/cc/gradients/math_grad.cc index 35a01e0341..84552e7c5e 100644 --- a/tensorflow/cc/gradients/math_grad.cc +++ b/tensorflow/cc/gradients/math_grad.cc @@ -441,6 +441,21 @@ Status RealDivGrad(const Scope& scope, const Operation& op, } REGISTER_GRADIENT_OP("RealDiv", RealDivGrad); +Status UnsafeDivGrad(const Scope& scope, const Operation& op, + const std::vector<Output>& grad_inputs, + std::vector<Output>* grad_outputs) { + auto x_1 = ConjugateHelper(scope, op.input(0)); + auto x_2 = ConjugateHelper(scope, op.input(1)); + // y = x_1 / x_2 + // dy/dx_1 = 1/x_2 + // dy/dx_2 = -x_1/x_2^2 + auto gx_1 = UnsafeDiv(scope, grad_inputs[0], x_2); + auto gx_2 = Mul(scope, grad_inputs[0], + UnsafeDiv(scope, UnsafeDiv(scope, Neg(scope, x_1), x_2), x_2)); + return BinaryGradCommon(scope, op, grad_outputs, gx_1, gx_2); +} +REGISTER_GRADIENT_OP("UnsafeDiv", UnsafeDivGrad); + Status SquaredDifferenceGrad(const Scope& scope, const Operation& op, const std::vector<Output>& grad_inputs, std::vector<Output>* grad_outputs) { diff --git a/tensorflow/cc/gradients/math_grad_test.cc b/tensorflow/cc/gradients/math_grad_test.cc index 1c9bdff5e1..330d1722af 100644 --- a/tensorflow/cc/gradients/math_grad_test.cc +++ b/tensorflow/cc/gradients/math_grad_test.cc @@ -13,8 +13,10 @@ See the License for the specific language governing permissions and limitations under the License. ==============================================================================*/ +#include "tensorflow/cc/client/client_session.h" #include "tensorflow/cc/framework/grad_op_registry.h" #include "tensorflow/cc/framework/gradient_checker.h" +#include "tensorflow/cc/framework/gradients.h" #include "tensorflow/cc/framework/testutil.h" #include "tensorflow/cc/gradients/grad_testutil.h" #include "tensorflow/cc/ops/standard_ops.h" @@ -45,6 +47,8 @@ using ops::RealDiv; using ops::SquaredDifference; using ops::Sub; using ops::Sum; +using ops::UnsafeDiv; +using ops::Where3; // TODO(andydavis) Test gradient function against numeric gradients output. // TODO(andydavis) As more gradients are added move common test functions @@ -850,6 +854,34 @@ TEST_F(NaryGradTest, RealDiv) { RunTest({x}, {x_shape}, {y}, {x_shape}); } +TEST_F(NaryGradTest, UnsafeDiv) { + { + 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(scope_, x, Add(scope_, Const<float>(scope_, 1), Abs(scope_, x))); + RunTest({x}, {x_shape}, {y}, {x_shape}); + } + { + // 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); + + std::vector<Output> grad_outputs; + TF_EXPECT_OK(AddSymbolicGradients(scope_, {y}, {x}, &grad_outputs)); + ClientSession session(scope_); + std::vector<Tensor> grad_result; + TF_EXPECT_OK(session.Run({{x, {-3.0f, 0.0f, 3.0f}}}, grad_outputs, &grad_result)); + EXPECT_EQ(grad_result.size(), 1); + EXPECT_EQ(grad_result[0].NumElements(), 3); + EXPECT_EQ(grad_result[0].flat<float>()(0), 0.0f); + EXPECT_EQ(grad_result[0].flat<float>()(1), 0.0f); + EXPECT_EQ(grad_result[0].flat<float>()(2), 0.0f); + } +} + TEST_F(NaryGradTest, SquaredDifference) { TensorShape x1_shape({3, 2, 5}); TensorShape x2_shape({2, 5}); |