diff options
author | Yan Facai (颜发才) <facai.yan@gmail.com> | 2018-08-09 19:34:39 +0800 |
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committer | Yan Facai (颜发才) <facai.yan@gmail.com> | 2018-08-09 19:34:39 +0800 |
commit | a90fce71faaa356b531157c2e00804046961b39d (patch) | |
tree | 5f270102fc14a6e52644402b99e16a45fbefb617 /tensorflow/cc | |
parent | 7613b773e03987c89fe5e5883c411588bce59673 (diff) |
CLN: clang-format format cc codes
Diffstat (limited to 'tensorflow/cc')
-rw-r--r-- | tensorflow/cc/gradients/math_grad.cc | 9 | ||||
-rw-r--r-- | tensorflow/cc/gradients/math_grad_test.cc | 6 |
2 files changed, 9 insertions, 6 deletions
diff --git a/tensorflow/cc/gradients/math_grad.cc b/tensorflow/cc/gradients/math_grad.cc index 84552e7c5e..c6e60689fa 100644 --- a/tensorflow/cc/gradients/math_grad.cc +++ b/tensorflow/cc/gradients/math_grad.cc @@ -442,16 +442,17 @@ 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) { + 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)); + 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); diff --git a/tensorflow/cc/gradients/math_grad_test.cc b/tensorflow/cc/gradients/math_grad_test.cc index 330d1722af..12a19bcf28 100644 --- a/tensorflow/cc/gradients/math_grad_test.cc +++ b/tensorflow/cc/gradients/math_grad_test.cc @@ -860,7 +860,8 @@ TEST_F(NaryGradTest, UnsafeDiv) { 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))); + const auto y = UnsafeDiv( + scope_, x, Add(scope_, Const<float>(scope_, 1), Abs(scope_, x))); RunTest({x}, {x_shape}, {y}, {x_shape}); } { @@ -873,7 +874,8 @@ TEST_F(NaryGradTest, UnsafeDiv) { 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)); + 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); |