From a90fce71faaa356b531157c2e00804046961b39d Mon Sep 17 00:00:00 2001
From: "Yan Facai (颜发才)" <facai.yan@gmail.com>
Date: Thu, 9 Aug 2018 19:34:39 +0800
Subject: CLN: clang-format format cc codes

---
 tensorflow/cc/gradients/math_grad.cc      | 9 +++++----
 tensorflow/cc/gradients/math_grad_test.cc | 6 ++++--
 2 files changed, 9 insertions(+), 6 deletions(-)

(limited to 'tensorflow/cc')

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);
-- 
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