Merge remote-tracking branch 'origin'

6 files changed, 17 insertions, 27 deletions

diff --git a/tensorflow/cc/framework/cc_op_gen.cc b/tensorflow/cc/framework/cc_op_gen.cc
index dfdef88945..a32d1b1eb5 100644
--- a/tensorflow/cc/framework/cc_op_gen.cc
+++ b/tensorflow/cc/framework/cc_op_gen.cc
@@ -466,7 +466,7 @@ string AvoidCPPKeywords(StringPiece name) {
   if (IsCPPKeyword(name)) {
     return strings::StrCat(name, "_");
   }
-  return std::string(name);
+  return string(name);
 }
 
 void InferArgAttributes(const OpDef::ArgDef& arg,
@@ -508,15 +508,6 @@ bool HasOptionalAttrs(
   return false;
 }
 
-const ApiDef::Arg* FindInputArg(StringPiece name, const ApiDef& api_def) {
-  for (int i = 0; i < api_def.in_arg_size(); ++i) {
-    if (api_def.in_arg(i).name() == name) {
-      return &api_def.in_arg(i);
-    }
-  }
-  return nullptr;
-}
-
 struct OpInfo {
   // graph_op_def: The OpDef used by the runtime, has the names that
   //   must be used when calling NodeBuilder.
diff --git a/tensorflow/cc/framework/ops.h b/tensorflow/cc/framework/ops.h
index a085e1d6e2..0717e7dd4b 100644
--- a/tensorflow/cc/framework/ops.h
+++ b/tensorflow/cc/framework/ops.h
@@ -150,7 +150,7 @@ class Input {
     Initializer(const std::initializer_list<T>& v, const TensorShape& shape) {
       typedef typename RealType<T>::type RealT;
       Tensor t(DataTypeToEnum<RealT>::v(), shape);
-      if (t.NumElements() != v.size()) {
+      if (t.NumElements() != static_cast<int64>(v.size())) {
         status = errors::InvalidArgument(
             "Cannot construct a tensor with ", t.NumElements(),
             " from an initializer list with ", v.size(), " elements");
diff --git a/tensorflow/cc/framework/scope.cc b/tensorflow/cc/framework/scope.cc
index 8c886f3171..7f6ac4cae7 100644
--- a/tensorflow/cc/framework/scope.cc
+++ b/tensorflow/cc/framework/scope.cc
@@ -225,7 +225,7 @@ std::unordered_set<string> Scope::Impl::GetColocationConstraints(
     for (const string& entry : node_constraints) {
       StringPiece s(entry);
       if (str_util::ConsumePrefix(&s, kColocationGroupPrefix)) {
-        current_constraints.insert(std::string(s));
+        current_constraints.emplace(s);
       }
     }
   } else {
diff --git a/tensorflow/cc/gradients/math_grad.cc b/tensorflow/cc/gradients/math_grad.cc
index 5dcf00857d..1329b568ab 100644
--- a/tensorflow/cc/gradients/math_grad.cc
+++ b/tensorflow/cc/gradients/math_grad.cc
@@ -441,21 +441,20 @@ 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) {
+Status DivNoNanGrad(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));
+  auto gx_1 = DivNoNan(scope, grad_inputs[0], x_2);
+  auto gx_2 = Mul(scope, grad_inputs[0],
+                  DivNoNan(scope, DivNoNan(scope, Neg(scope, x_1), x_2), x_2));
   return BinaryGradCommon(scope, op, grad_outputs, gx_1, gx_2);
 }
-REGISTER_GRADIENT_OP("UnsafeDiv", UnsafeDivGrad);
+REGISTER_GRADIENT_OP("DivNoNan", DivNoNanGrad);
 
 Status SquaredDifferenceGrad(const Scope& scope, const Operation& op,
                              const std::vector<Output>& grad_inputs,
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));
diff --git a/tensorflow/cc/saved_model/loader.cc b/tensorflow/cc/saved_model/loader.cc
index 3830416159..c6abe2f41b 100644
--- a/tensorflow/cc/saved_model/loader.cc
+++ b/tensorflow/cc/saved_model/loader.cc
@@ -148,7 +148,7 @@ Status RunMainOp(const RunOptions& run_options, const string& export_dir,
     AddAssetsTensorsToInputs(export_dir, asset_file_defs, &inputs);
     RunMetadata run_metadata;
     const StringPiece main_op_name = main_op_it->second.node_list().value(0);
-    return RunOnce(run_options, inputs, {}, {main_op_name.ToString()},
+    return RunOnce(run_options, inputs, {}, {string(main_op_name)},
                    nullptr /* outputs */, &run_metadata, session);
   }
   return Status::OK();
@@ -182,12 +182,12 @@ Status RunRestore(const RunOptions& run_options, const string& export_dir,
   variables_path_tensor.scalar<string>()() = variables_path;
 
   std::vector<std::pair<string, Tensor>> inputs = {
-      {variable_filename_const_op_name.ToString(), variables_path_tensor}};
+      {string(variable_filename_const_op_name), variables_path_tensor}};
 
   AddAssetsTensorsToInputs(export_dir, asset_file_defs, &inputs);
 
   RunMetadata run_metadata;
-  return RunOnce(run_options, inputs, {}, {restore_op_name.ToString()},
+  return RunOnce(run_options, inputs, {}, {string(restore_op_name)},
                  nullptr /* outputs */, &run_metadata, session);
 }