Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into mul_op

paddle/framework/backward_test.cc

@@ -32,9 +32,9 @@ class RowWiseAddOpMaker : public OpProtoAndCheckerMaker {
  public:
   RowWiseAddOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
-    AddInput("X", "Input X of Add").AsNoGradient();
-    AddInput("b", "Bias of Add").AsNoGradient();
-    AddOutput("Out", "Out of Add").AsNoGradient();
+    AddInput("X", "Input X of Add").NotInGradient();
+    AddInput("b", "Bias of Add").NotInGradient();
+    AddOutput("Out", "Out of Add").NotInGradient();
     AddComment("Add Op");
   }
 };

paddle/framework/framework.proto

@@ -60,7 +60,7 @@ message OpProto {
 
     optional bool duplicable = 3 [ default = false ];
     optional bool intermediate = 4 [ default = false ];
-    optional bool no_gradient = 5 [ default = false ];
+    optional bool not_in_gradient = 5 [ default = false ];
   }
 
   // AttrProto describes the C++ type Attribute.

paddle/framework/grad_op_builder.cc

@@ -28,7 +28,7 @@ static void TransOpArg(const OperatorBase* src_op, const OpArgType& src_type,
   const auto& src_arg_list =
       src_type == OpArgType::IN ? proto->inputs() : proto->outputs();
   for (const auto& arg : src_arg_list) {
-    if (arg.no_gradient() && !is_grad) continue;
+    if (arg.not_in_gradient() && !is_grad) continue;
     const std::string src_name = arg.name();
     std::string dst_name = is_grad ? GradVarName(src_name) : src_name;
     dst_inout[dst_name].reserve(src_inout.at(src_name).size());

paddle/framework/grad_op_builder_test.cc

@@ -26,10 +26,10 @@ class IOIgnoredOpMaker : public OpProtoAndCheckerMaker {
   IOIgnoredOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("In1", "a single input");
-    AddInput("In2_mult", "a multiple input").AsDuplicable().AsNoGradient();
+    AddInput("In2_mult", "a multiple input").AsDuplicable().NotInGradient();
     AddInput("In3_mult", "another multiple input").AsDuplicable();
     AddOutput("Out1_mult", "a multiple output").AsDuplicable();
-    AddOutput("Out2", "a single output").AsNoGradient();
+    AddOutput("Out2", "a single output").NotInGradient();
     AddComment("op with inputs and outputs ignored in gradient calculating");
   }
 };

paddle/framework/operator.h

@@ -184,11 +184,8 @@ class OpProtoAndCheckerMaker {
       return *this;
     }
 
-    // TODO(FengJiayi, yuyang18): `AsNoGradient` is a very bad name, because it
-    // means that input/output is not needed when calculate gradient. It does
-    // not mean no gradient when backward. It should be changed soon.
-    VariableBuilder& AsNoGradient() {
-      var_->set_no_gradient(true);
+    VariableBuilder& NotInGradient() {
+      var_->set_not_in_gradient(true);
       return *this;
     }
   };

paddle/operators/mean_op.cc

@@ -34,7 +34,7 @@ class MeanOpMaker : public framework::OpProtoAndCheckerMaker {
   MeanOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "The input of mean op");
-    AddOutput("Out", "The output of mean op").AsNoGradient();
+    AddOutput("Out", "The output of mean op").NotInGradient();
     AddComment("Mean Operator");
   }
 };