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

README.md

@@ -62,9 +62,9 @@ Please refer to our [release announcement](https://github.com/PaddlePaddle/Paddl
 ## Installation
 
 It is recommended to check out the
-[Docker installation guide](http://www.paddlepaddle.org/docs/develop/documentation/en/getstarted/build_and_install/docker_install_en.html)
+[Docker installation guide](http://www.paddlepaddle.org/docs/develop/documentation/fluid/en/build_and_install/docker_install_en.html)
 before looking into the
-[build from source guide](http://www.paddlepaddle.org/docs/develop/documentation/en/getstarted/build_and_install/build_from_source_en.html).
+[build from source guide](http://www.paddlepaddle.org/docs/develop/documentation/fluid/en/build_and_install/build_from_source_en.html).
 
 ## Documentation
 

cmake/external/mkldnn.cmake

@@ -45,9 +45,9 @@ IF(${CBLAS_PROVIDER} STREQUAL "MKLML")
 ELSE()
     MESSAGE(FATAL_ERROR "Should enable MKLML when build MKLDNN")
 ENDIF()
-
-SET(MKLDNN_CFLAG "${CMAKE_C_FLAGS} -Wno-error=strict-overflow")
-SET(MKLDNN_CXXFLAG "${CMAKE_CXX_FLAGS} -Wno-error=strict-overflow")
+SET(MKLDNN_FLAG "-Wno-error=strict-overflow -Wno-error=unused-result -Wno-unused-result")
+SET(MKLDNN_CFLAG "${CMAKE_C_FLAGS} ${MKLDNN_FLAG}")
+SET(MKLDNN_CXXFLAG "${CMAKE_CXX_FLAGS} ${MKLDNN_FLAG}")
 ExternalProject_Add(
     ${MKLDNN_PROJECT}
     ${EXTERNAL_PROJECT_LOG_ARGS}
@@ -61,6 +61,7 @@ ExternalProject_Add(
     CMAKE_ARGS          -DMKLROOT=${MKLML_ROOT}
     CMAKE_ARGS          -DCMAKE_C_FLAGS=${MKLDNN_CFLAG}
     CMAKE_ARGS          -DCMAKE_CXX_FLAGS=${MKLDNN_CXXFLAG}
+    CMAKE_ARGS          -DWITH_TEST=OFF -DWITH_EXAMPLE=OFF
     CMAKE_CACHE_ARGS    -DCMAKE_INSTALL_PREFIX:PATH=${MKLDNN_INSTALL_DIR}
                         -DMKLROOT:PATH=${MKLML_ROOT}
 )

cmake/external/mklml.cmake

@@ -27,7 +27,7 @@ ENDIF()
 INCLUDE(ExternalProject)
 
 SET(MKLML_PROJECT       "extern_mklml")
-SET(MKLML_VER           "mklml_lnx_2018.0.1.20171007")
+SET(MKLML_VER           "mklml_lnx_2018.0.3.20180406")
 SET(MKLML_URL           "http://paddlepaddledeps.bj.bcebos.com/${MKLML_VER}.tgz")
 SET(MKLML_SOURCE_DIR    "${THIRD_PARTY_PATH}/mklml")
 SET(MKLML_DOWNLOAD_DIR  "${MKLML_SOURCE_DIR}/src/${MKLML_PROJECT}")

paddle/fluid/framework/CMakeLists.txt

@@ -57,7 +57,7 @@ cc_library(data_transform SRCS data_transform.cc DEPS math_function tensor
 cc_library(attribute SRCS attribute.cc DEPS framework_proto boost)
 cc_test(program_desc_test SRCS program_desc_test.cc DEPS proto_desc
 device_context)
-cc_library(op_proto_maker SRCS op_proto_maker.cc DEPS framework_proto attribute)
+cc_library(op_proto_maker SRCS op_proto_maker.cc DEPS framework_proto attribute glog)
 cc_test(op_proto_maker_test SRCS op_proto_maker_test.cc DEPS op_proto_maker)
 cc_library(op_info SRCS op_info.cc DEPS attribute framework_proto)
 cc_library(shape_inference SRCS shape_inference.cc DEPS ddim attribute device_context)

paddle/fluid/framework/data_device_transform_test.cu

@@ -32,8 +32,7 @@ struct AddFunctor {
 
 class OpKernelTestProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
  public:
-  OpKernelTestProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() {
     AddInput("input", "input1 of test op");
     AddOutput("output", "output of test op");
     AddAttr<bool>("use_gpu", "force to use gpu kernel").SetDefault(false);

paddle/fluid/framework/details/computation_op_handle.h

@@ -36,7 +36,7 @@ struct ComputationOpHandle : public OpHandleBase {
  protected:
   void RunImpl() override;
 
-  virtual bool NeedWait(VarHandleBase *in_var);
+  bool NeedWait(VarHandleBase *in_var) override;
 
  private:
   std::unique_ptr<OperatorBase> op_;

paddle/fluid/framework/details/fetch_op_handle.h

@@ -42,7 +42,7 @@ struct FetchOpHandle : public OpHandleBase {
  protected:
   void RunImpl() override;
 
-  virtual void WaitInputVarGenerated(const platform::Place &place);
+  void WaitInputVarGenerated(const platform::Place &place) override;
 
  private:
   FeedFetchList *data_;

paddle/fluid/framework/details/op_registry.h

@@ -95,7 +95,10 @@ struct OpInfoFiller<T, kOpProtoAndCheckerMaker> {
   void operator()(const char* op_type, OpInfo* info) const {
     info->proto_ = new proto::OpProto;
     info->checker_ = new OpAttrChecker();
-    auto maker = T(info->proto_, info->checker_);
+    T maker;
+    maker.SetProto(info->proto_);
+    maker.SetChecker(info->checker_);
+    maker.Make();
     maker.Validate();
     info->proto_->set_type(op_type);
     PADDLE_ENFORCE(

paddle/fluid/framework/op_proto_maker.h

@@ -14,56 +14,57 @@ limitations under the License. */
 #pragma once
 
 #include <string>
+#include "glog/logging.h"
 #include "paddle/fluid/framework/attribute.h"
 #include "paddle/fluid/framework/framework.pb.h"
-
 namespace paddle {
 namespace framework {
 
 // this class not only make proto but also init attribute checkers.
 class OpProtoAndCheckerMaker {
  public:
-  using OpProto = proto::OpProto;
-  using OpAttrChecker = framework::OpAttrChecker;
-  OpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : proto_(proto), op_checker_(op_checker) {}
+  virtual void Make() = 0;
 
   virtual ~OpProtoAndCheckerMaker() {
-    PADDLE_ENFORCE(validated_, "should call Validate after build");
+    CHECK(validated_) << "should call Validate after build";
   }
 
+  void SetProto(proto::OpProto *proto) { proto_ = proto; }
+
+  void SetChecker(OpAttrChecker *attr_checker) { op_checker_ = attr_checker; }
+
   void Validate();
 
  protected:
   struct VariableBuilder {
-    OpProto::Var* var_;
+    proto::OpProto::Var *var_;
 
-    VariableBuilder& AsDuplicable() {
+    VariableBuilder &AsDuplicable() {
       var_->set_duplicable(true);
       return *this;
     }
 
-    VariableBuilder& AsIntermediate() {
+    VariableBuilder &AsIntermediate() {
       var_->set_intermediate(true);
       return *this;
     }
 
-    VariableBuilder& AsDispensable() {
+    VariableBuilder &AsDispensable() {
       var_->set_dispensable(true);
       return *this;
     }
   };
 
-  VariableBuilder AddInput(const std::string& name, const std::string& comment);
+  VariableBuilder AddInput(const std::string &name, const std::string &comment);
 
-  VariableBuilder AddOutput(const std::string& name,
-                            const std::string& comment);
+  VariableBuilder AddOutput(const std::string &name,
+                            const std::string &comment);
 
   template <typename T>
-  TypedAttrChecker<T>& AddAttr(const std::string& name,
-                               const std::string& comment,
+  TypedAttrChecker<T> &AddAttr(const std::string &name,
+                               const std::string &comment,
                                bool generated = false) {
-    auto* attr = proto_->add_attrs();
+    auto *attr = proto_->add_attrs();
     attr->set_name(name);
     attr->set_comment(comment);
     attr->set_generated(generated);
@@ -71,21 +72,14 @@ class OpProtoAndCheckerMaker {
     return op_checker_->AddAttrChecker<T>(name);
   }
 
-  void AddComment(const std::string& comment) { proto_->set_comment(comment); }
+  void AddComment(const std::string &comment) { proto_->set_comment(comment); }
 
  private:
   void CheckNoDuplicatedInOutAttrs();
 
-  OpProto* proto_;
-  OpAttrChecker* op_checker_;
+  proto::OpProto *proto_;
+  OpAttrChecker *op_checker_;
   bool validated_{false};
 };
-
-class NOPMaker : public OpProtoAndCheckerMaker {
- public:
-  NOPMaker(OpProto* proto, framework::OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {}
-};
-
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/framework/op_proto_maker_test.cc

@@ -18,9 +18,7 @@ limitations under the License. */
 
 class TestAttrProtoMaker : public paddle::framework::OpProtoAndCheckerMaker {
  public:
-  TestAttrProtoMaker(paddle::framework::proto::OpProto* proto,
-                     paddle::framework::OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() {
     AddAttr<float>("scale", "scale of test op");
     AddAttr<float>("scale", "scale of test op");
   }
@@ -29,15 +27,16 @@ class TestAttrProtoMaker : public paddle::framework::OpProtoAndCheckerMaker {
 TEST(ProtoMaker, DuplicatedAttr) {
   paddle::framework::proto::OpProto op_proto;
   paddle::framework::OpAttrChecker op_checker;
-  auto proto_maker = TestAttrProtoMaker(&op_proto, &op_checker);
+  TestAttrProtoMaker proto_maker;
+  proto_maker.SetProto(&op_proto);
+  proto_maker.SetChecker(&op_checker);
+  proto_maker.Make();
   ASSERT_THROW(proto_maker.Validate(), paddle::platform::EnforceNotMet);
 }
 
 class TestInOutProtoMaker : public paddle::framework::OpProtoAndCheckerMaker {
  public:
-  TestInOutProtoMaker(paddle::framework::proto::OpProto* proto,
-                      paddle::framework::OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() {
     AddInput("input", "input of test op");
     AddInput("input", "input of test op");
   }
@@ -46,6 +45,9 @@ class TestInOutProtoMaker : public paddle::framework::OpProtoAndCheckerMaker {
 TEST(ProtoMaker, DuplicatedInOut) {
   paddle::framework::proto::OpProto op_proto;
   paddle::framework::OpAttrChecker op_checker;
-  auto proto_maker = TestInOutProtoMaker(&op_proto, &op_checker);
+  TestAttrProtoMaker proto_maker;
+  proto_maker.SetProto(&op_proto);
+  proto_maker.SetChecker(&op_checker);
+  proto_maker.Make();
   ASSERT_THROW(proto_maker.Validate(), paddle::platform::EnforceNotMet);
 }

paddle/fluid/framework/op_registry_test.cc

@@ -33,8 +33,7 @@ class CosineOp : public OperatorBase {
 
 class CosineOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
  public:
-  CosineOpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() {
     AddInput("input", "input of cosine op");
     AddOutput("output", "output of cosine op");
     AddAttr<float>("scale", "scale of cosine op")
@@ -55,8 +54,7 @@ class MyTestOp : public OperatorBase {
 
 class MyTestOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
  public:
-  MyTestOpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() {
     AddInput("input", "input of cosine op").AsDuplicable();
     AddOutput("output", "output of cosine op").AsIntermediate();
     auto my_checker = [](int i) {
@@ -212,10 +210,7 @@ namespace framework {
 
 class OpKernelTestMaker : public OpProtoAndCheckerMaker {
  public:
-  OpKernelTestMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
-    AddComment("NoGradOp, same input output. no Grad");
-  }
+  void Make() { AddComment("NoGradOp, same input output. no Grad"); }
 };
 
 class OpWithKernelTest : public OperatorWithKernel {
@@ -275,9 +270,9 @@ TEST(OperatorRegistrar, CUDA) {
 
 static int op_test_value = 0;
 
-using paddle::platform::DeviceContext;
 using paddle::platform::CPUDeviceContext;
 using paddle::platform::CUDADeviceContext;
+using paddle::platform::DeviceContext;
 
 namespace paddle {
 namespace framework {

paddle/fluid/framework/operator_test.cc

@@ -46,8 +46,7 @@ class OpWithoutKernelTest : public OperatorBase {
 
 class OpWithoutKernelCheckerMaker : public OpProtoAndCheckerMaker {
  public:
-  OpWithoutKernelCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() {
     AddInput("input", "input of test op");
     AddOutput("output", "output of test op");
     AddAttr<float>("scale", "scale of cosine op");
@@ -98,8 +97,7 @@ namespace framework {
 
 class OpKernelTestProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
  public:
-  OpKernelTestProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() {
     AddInput("x", "input of test op");
     AddOutput("y", "output of test op");
     AddAttr<float>("scale", "scale of cosine op")
@@ -137,9 +135,7 @@ class CPUKernelTest : public OpKernel<float> {
 class OpKernelTestMultiInputsProtoAndCheckerMaker
     : public OpProtoAndCheckerMaker {
  public:
-  OpKernelTestMultiInputsProtoAndCheckerMaker(OpProto* proto,
-                                              OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() {
     AddInput("xs", "inputs of test op").AsDuplicable();
     AddInput("k", "input of test op");
     AddOutput("ys", "outputs of test op").AsDuplicable();

paddle/fluid/framework/var_type_inference_test.cc

@@ -24,8 +24,7 @@ namespace framework {
 
 class SumOpMaker : public OpProtoAndCheckerMaker {
  public:
-  SumOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() {
     AddInput("X", "").AsDuplicable();
     AddOutput("Out", "");
     AddComment("");

paddle/fluid/inference/tensorrt/test_engine.cc

@@ -98,7 +98,7 @@ TEST_F(TensorRTEngineTest, add_layer_multi_dim) {
 
   float x_v[2] = {1.0, 2.0};
   engine_->SetInputFromCPU("x", reinterpret_cast<void*>(&x_v),
-  2 * sizeof(float));
+                           2 * sizeof(float));
   engine_->Execute(1);
 
   LOG(INFO) << "to get output";

paddle/fluid/operators/CMakeLists.txt

@@ -166,6 +166,8 @@ function(op_library TARGET)
       # NOTE(*): activation use macro to regist the kernels, set use_op manually.
       if(${TARGET} STREQUAL "activation")
         file(APPEND ${pybind_file} "USE_OP(relu);\n")
+      elseif(${TARGET} STREQUAL "reduce")
+        file(APPEND ${pybind_file} "USE_OP(reduce_sum);\n")
       else()
         file(APPEND ${pybind_file} "USE_OP(${TARGET});\n")
       endif()

paddle/fluid/operators/accuracy_op.cc

@@ -63,8 +63,7 @@ class AccuracyOp : public framework::OperatorWithKernel {
 
 class AccuracyOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  AccuracyOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     // TODO(typhoonzero): support both inference value and indices.
     AddInput("Out", "The network output of topk (inferences)");
     AddInput("Indices", "The the network output of topk (indices)");

paddle/fluid/operators/activation_op.cc

@@ -19,19 +19,18 @@ limitations under the License. */
 namespace paddle {
 namespace operators {
 
-#define REGISTER_ACTIVATION_OP_MAKER(OP_NAME, OP_COMMENT)                  \
-  class OP_NAME##OpMaker                                                   \
-      : public ::paddle::framework::OpProtoAndCheckerMaker {               \
-   public:                                                                 \
-    OP_NAME##OpMaker(OpProto *proto, OpAttrChecker *op_checker)            \
-        : ::paddle::framework::OpProtoAndCheckerMaker(proto, op_checker) { \
-      AddInput("X", "Input of " #OP_NAME "operator");                      \
-      AddOutput("Out", "Output of" #OP_NAME "operator");                   \
-      AddAttr<bool>("use_mkldnn",                                          \
-                    "(bool, default false) Only used in mkldnn kernel")    \
-          .SetDefault(false);                                              \
-      AddComment(#OP_COMMENT);                                             \
-    }                                                                      \
+#define REGISTER_ACTIVATION_OP_MAKER(OP_NAME, OP_COMMENT)               \
+  class OP_NAME##OpMaker                                                \
+      : public ::paddle::framework::OpProtoAndCheckerMaker {            \
+   public:                                                              \
+    void Make() override {                                              \
+      AddInput("X", "Input of " #OP_NAME "operator");                   \
+      AddOutput("Out", "Output of" #OP_NAME "operator");                \
+      AddAttr<bool>("use_mkldnn",                                       \
+                    "(bool, default false) Only used in mkldnn kernel") \
+          .SetDefault(false);                                           \
+      AddComment(#OP_COMMENT);                                          \
+    }                                                                   \
   }
 
 #define REGISTER_ACTIVATION_OP_GRAD_MAKER(OP_NAME, KERNEL_TYPE)              \
@@ -204,8 +203,7 @@ $$out = \frac{x}{1 + |x|}$$
 
 class LeakyReluOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LeakyReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "Input of LeakyRelu operator");
     AddOutput("Out", "Output of LeakyRelu operator");
     AddAttr<float>("alpha", "The small negative slope").SetDefault(0.02f);
@@ -220,8 +218,7 @@ $out = \max(x, \alpha * x)$
 
 class SoftShrinkOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SoftShrinkOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "Input of Softshrink operator");
     AddOutput("Out", "Output of Softshrink operator");
     AddAttr<float>("lambda", "non-negative offset").SetDefault(0.5f);
@@ -242,8 +239,7 @@ $$
 
 class HardShrinkOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  HardShrinkOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "Input of HardShrink operator");
     AddOutput("Out", "Output of HardShrink operator");
     AddAttr<float>("threshold", "The value of threshold for HardShrink")
@@ -265,8 +261,7 @@ $$
 
 class BReluOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  BReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "Input of BRelu operator");
     AddOutput("Out", "Output of BRelu operator");
     AddAttr<float>("t_min", "The min marginal value of BRelu")
@@ -284,8 +279,7 @@ $out = \max(\min(x, t_{min}), t_{max})$
 
 class SoftReluOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SoftReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "Input of SoftRelu operator");
     AddOutput("Out", "Output of SoftRelu operator");
     AddAttr<float>("threshold", "The threshold value of SoftRelu")
@@ -301,8 +295,7 @@ $out = \ln(1 + \exp(\max(\min(x, threshold), threshold))$
 
 class ELUOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ELUOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "Input of ELU operator");
     AddOutput("Out", "Output of ELU operator");
     AddAttr<float>("alpha", "The alpha value of ELU").SetDefault(1.0f);
@@ -320,8 +313,7 @@ $out = \max(0, x) + \min(0, \alpha * (e^x - 1))$
 
 class Relu6OpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  Relu6OpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "Input of Relu6 operator");
     AddOutput("Out", "Output of Relu6 operator");
     AddAttr<float>("threshold", "The threshold value of Relu6")
@@ -337,8 +329,7 @@ $out = \min(\max(0, x), 6)$
 
 class PowOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  PowOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "Input of Pow operator");
     AddOutput("Out", "Output of Pow operator");
     AddAttr<float>("factor", "The exponential factor of Pow").SetDefault(1.0f);
@@ -353,8 +344,7 @@ $out = x^{factor}$
 
 class STanhOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  STanhOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "Input of STanh operator");
     AddOutput("Out", "Output of STanh operator");
     AddAttr<float>("scale_a", "The scale parameter of a for the input")
@@ -372,8 +362,7 @@ $$out = b * \frac{e^{a * x} - e^{-a * x}}{e^{a * x} + e^{-a * x}}$$
 
 class ThresholdedReluOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ThresholdedReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "Input of ThresholdedRelu operator");
     AddOutput("Out", "Output of ThresholdedRelu operator");
     AddAttr<float>("threshold", "The threshold location of activation")
@@ -394,8 +383,7 @@ $$
 
 class HardSigmoidOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  HardSigmoidOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "Input of HardSigmoid operator");
     AddOutput("Out", "Output of HardSigmoid operator");
     AddAttr<float>("slope", "Slope for linear approximation of sigmoid")
@@ -420,8 +408,7 @@ It is recommended to use the defaults for this activation.
 
 class SwishOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SwishOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "Input of Swish operator");
     AddOutput("Out", "Output of Swish operator");
     AddAttr<float>("beta", "Constant beta of swish operator").SetDefault(1.0f);

paddle/fluid/operators/adadelta_op.cc

@@ -66,8 +66,7 @@ class AdadeltaOp : public framework::OperatorWithKernel {
 
 class AdadeltaOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  AdadeltaOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Param", "(Tensor) Input parameter");
     AddInput("Grad", "(Tensor) Input gradient");
     AddInput("AvgSquaredGrad", "(Tensor) Input average of squared gradient");

paddle/fluid/operators/adagrad_op.cc

@@ -67,8 +67,7 @@ class AdagradOp : public framework::OperatorWithKernel {
 
 class AdagradOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  AdagradOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Param", "(Tensor) Input parameter");
     AddInput("Grad", "(Tensor) Input gradient");
     AddInput("Moment", "(Tensor) Second moment");

paddle/fluid/operators/adam_op.cc

@@ -80,8 +80,7 @@ class AdamOp : public framework::OperatorWithKernel {
 
 class AdamOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  AdamOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Param", "(Tensor) Input parameter");
     AddInput("Grad", "(Tensor) Input gradient");
     AddInput("LearningRate", "(Tensor) Learning rate");

paddle/fluid/operators/adamax_op.cc

@@ -74,8 +74,7 @@ class AdamaxOp : public framework::OperatorWithKernel {
 
 class AdamaxOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  AdamaxOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Param", "(Tensor) Input parameter");
     AddInput("Grad", "(Tensor) Input gradient");
     AddInput("LearningRate", "(Tensor) Learning rate");

paddle/fluid/operators/array_to_lod_tensor_op.cc

@@ -123,8 +123,7 @@ class ArrayToLoDTensorOp : public framework::OperatorBase {
 
 class ArrayToLoDTensorOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ArrayToLoDTensorOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(std::vector<LodTensor>) A vector of tensors that is going to "
              "be casted to a big LoDTensor.");

paddle/fluid/operators/assign_op.cc

@@ -94,8 +94,7 @@ class AssignOp : public framework::OperatorBase {
 
 class AssignOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  AssignOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(LoDTensor, SelectedRows or LoDTensorArray) The input variable "
              "could be LoDTensor, SelectedRows or LoDTensorArray.")

paddle/fluid/operators/assign_value_op.cc

@@ -45,8 +45,7 @@ class AssignValueOp : public framework::OperatorWithKernel {
 
 class AssignValueOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  AssignValueOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddOutput("Out", "(Tensor) Output tensor of assign_value operator.");
     AddAttr<std::vector<int>>("shape",
                               "(vector<int>) "

paddle/fluid/operators/auc_op.cc

@@ -50,8 +50,7 @@ class AucOp : public framework::OperatorWithKernel {
 
 class AucOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  AucOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Out",
              "A floating point 2D tensor, values are in the range [0, 1]."
              "Each row is sorted in descending order. This input should be the"

paddle/fluid/operators/average_accumulates_op.cc

@@ -111,8 +111,7 @@ class AverageAccumulatesOp : public framework::OperatorWithKernel {
 
 class AverageAccumulatesOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  AverageAccumulatesOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("param", "(Tensor), The parameter to be accumulated.");
     AddInput("in_sum_1",
              "(Tensor), A tensor used to store the parameter "

paddle/fluid/operators/batch_norm_op.cc

@@ -126,8 +126,7 @@ class BatchNormOp : public framework::OperatorWithKernel {
 
 class BatchNormOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  BatchNormOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddAttr<bool>("is_test", "").SetDefault(false);
     AddAttr<float>("momentum", "").SetDefault(0.9);
     AddAttr<float>("epsilon", "")

paddle/fluid/operators/batch_size_like.h

@@ -53,8 +53,7 @@ class BatchSizeLikeOp : public framework::OperatorWithKernel {
 
 class BatchSizeLikeOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  BatchSizeLikeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() final {
     AddInput("Input",
              "(Tensor) Tensor "
              "whose input_dim_idx'th dimension specifies the batch_size");
@@ -68,7 +67,11 @@ class BatchSizeLikeOpMaker : public framework::OpProtoAndCheckerMaker {
     AddAttr<int>("output_dim_idx",
                  "(int, default 0) The index of output's batch size dimension")
         .SetDefault(0);
+    Apply();
   }
+
+ protected:
+  virtual void Apply() = 0;
 };
 
 }  // namespace operators

paddle/fluid/operators/beam_search_decode_op.cc

@@ -134,8 +134,7 @@ class BeamSearchDecodeOp : public framework::OperatorBase {
 
 class BeamSearchDecodeOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  BeamSearchDecodeOpProtoMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Ids",
              "(LodTensorArray)"
              "score of the candidate words in each step");

paddle/fluid/operators/beam_search_op.cc

@@ -197,8 +197,7 @@ std::string ItemToString(const BeamSearch::Item &item) {
 
 class BeamSearchOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  BeamSearchOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     // inputs and outputs stored in proto
     AddInput("pre_ids", "ids in previous step");
     AddInput("ids", "a LoDTensor of shape of [None,k]");

paddle/fluid/operators/bilinear_interp_op.cc

@@ -41,8 +41,7 @@ class BilinearInterpOp : public framework::OperatorWithKernel {
 
 class BilinearInterpOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  BilinearInterpOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(Tensor) The input tensor of bilinear interpolation, "
              "This is a 4-D tensor with shape of (N x C x h x w)");

paddle/fluid/operators/bilinear_tensor_product_op.cc

@@ -65,8 +65,7 @@ class BilinearTensorProductOp : public framework::OperatorWithKernel {
 
 class BilinearTensorProductOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  BilinearTensorProductOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The first input of bilinear_tensor_product operator.");
     AddInput("Y", "The second input of bilinear_tensor_product operator.");
     AddInput("Weight",

paddle/fluid/operators/bipartite_match_op.cc

@@ -182,8 +182,7 @@ class BipartiteMatchKernel : public framework::OpKernel<T> {
 
 class BipartiteMatchOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  BipartiteMatchOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(
         "DistMat",
         "(LoDTensor or Tensor) this input is a 2-D LoDTensor with shape "

paddle/fluid/operators/box_coder_op.cc

@@ -60,8 +60,7 @@ class BoxCoderOp : public framework::OperatorWithKernel {
 
 class BoxCoderOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  BoxCoderOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(
         "PriorBox",
         "(Tensor, default Tensor<float>) "

paddle/fluid/operators/cast_op.cc

@@ -21,8 +21,7 @@ namespace operators {
 
 class CastOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  CastOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The input tensor of cast op");
     AddOutput("Out", "The output tensor of cast op");
     AddAttr<int>("out_dtype", "output data type");

paddle/fluid/operators/channel_close_op.cc

@@ -50,8 +50,7 @@ class ChannelCloseOpOpInferShape : public framework::InferShapeBase {
 
 class ChannelCloseOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ChannelCloseOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(kChannel,
              "The Channel Variable that should be closed by"
              " the ChannelClose Op.");

paddle/fluid/operators/channel_create_op.cc

@@ -91,8 +91,7 @@ class ChannelCreateOpOpInferShape : public framework::InferShapeBase {
 
 class ChannelCreateOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ChannelCreateOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddOutput(kOutput,
               "The object of a Channel type created by ChannelCreate Op.");
     AddAttr<int>("capacity", "The size of the buffer of Channel.")

paddle/fluid/operators/channel_recv_op.cc

@@ -72,8 +72,7 @@ class ChannelRecvOp : public framework::OperatorBase {
 
 class ChannelRecvOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ChannelRecvOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(Channel,
              "(Channel) A variable which \"receives\" the a value sent"
              "to it by a channel_send op.")

paddle/fluid/operators/channel_send_op.cc

@@ -57,8 +57,7 @@ class ChannelSendOp : public framework::OperatorBase {
 
 class ChannelSendOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ChannelSendOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(Channel,
              "(Channel) A variable which \"sends\" the passed in value to "
              "a listening receiver.")

paddle/fluid/operators/chunk_eval_op.cc

@@ -66,8 +66,7 @@ class ChunkEvalOp : public framework::OperatorWithKernel {
 
 class ChunkEvalOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ChunkEvalOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Inference",
              "(Tensor, default: Tensor<int64_t>). "
              "Predictions from the network.");

paddle/fluid/operators/clip_by_norm_op.cc

@@ -37,8 +37,7 @@ class ClipByNormOp : public framework::OperatorWithKernel {
 
 class ClipByNormOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ClipByNormOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(Tensor) The input of clip_by_norm op."
              "The number of dimensions must be between [1, 9].");

paddle/fluid/operators/clip_op.cc

@@ -38,8 +38,7 @@ class ClipOp : public framework::OperatorWithKernel {
 template <typename AttrType>
 class ClipOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ClipOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(Tensor)The input of clip op."
              "The number of dimensions must be between [1, 9].");

paddle/fluid/operators/compare_op.cc

@@ -21,8 +21,7 @@ namespace operators {
 template <typename OpComment>
 class CompareOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  CompareOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     OpComment comment;
     AddInput("X",
              string::Sprintf("(LoDTensor) the left hand operand of %s operator",

paddle/fluid/operators/concat_op.cc

@@ -63,8 +63,7 @@ class ConcatOp : public framework::OperatorWithKernel {
 
 class ConcatOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ConcatOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "Input tensors of concat operator.").AsDuplicable();
     AddOutput("Out", "Output tensor of concat operator.");
     AddAttr<int>("axis",

paddle/fluid/operators/conditional_block_op.cc

@@ -108,8 +108,7 @@ class ConditionalBlockOp : public ConditionalOp {
 
 class ConditionalBlockOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ConditionalBlockOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "The conditional variable of this operator. If X is empty, the "
              "whole sub-block will not be executed.")

paddle/fluid/operators/conv_op.cc

@@ -106,8 +106,7 @@ framework::OpKernelType ConvOp::GetExpectedKernelType(
                                  library);
 }
 
-Conv2DOpMaker::Conv2DOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-    : OpProtoAndCheckerMaker(proto, op_checker) {
+void Conv2DOpMaker::Make() {
   AddInput(
       "Input",
       "(Tensor) The input tensor of convolution operator. "
@@ -200,8 +199,7 @@ $$
 )DOC");
 }
 
-Conv3DOpMaker::Conv3DOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-    : OpProtoAndCheckerMaker(proto, op_checker) {
+void Conv3DOpMaker::Make() {
   AddInput(
       "Input",
       "(Tensor) The input tensor of convolution operator. "

paddle/fluid/operators/conv_op.h

@@ -60,12 +60,12 @@ inline bool IsExpand(const std::vector<int64_t>& filter_dim,
 // operator implementations can reuse the code.
 class Conv2DOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  Conv2DOpMaker(OpProto* proto, OpAttrChecker* op_checker);
+  void Make() override;
 };
 
 class Conv3DOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  Conv3DOpMaker(OpProto* proto, OpAttrChecker* op_checker);
+  void Make() override;
 };
 
 class ConvOp : public framework::OperatorWithKernel {

paddle/fluid/operators/conv_shift_op.cc

@@ -75,8 +75,7 @@ class ConvShiftGradOp : public framework::OperatorWithKernel {
 
 class ConvShiftOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ConvShiftOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(Tensor, default Tensor<float>), a 2-D tensor with shape B x M, "
              "where B is the batch size and M is the data dimension.");

paddle/fluid/operators/conv_transpose_op.cc

@@ -84,9 +84,7 @@ framework::OpKernelType ConvTransposeOp::GetExpectedKernelType(
       layout_, library_);
 }
 
-Conv2DTransposeOpMaker::Conv2DTransposeOpMaker(OpProto* proto,
-                                               OpAttrChecker* op_checker)
-    : OpProtoAndCheckerMaker(proto, op_checker) {
+void Conv2DTransposeOpMaker::Make() {
   AddInput(
       "Input",
       "(Tensor) The input tensor of convolution transpose operator. "
@@ -168,9 +166,7 @@ Example:
 )DOC");
 }
 
-Conv3DTransposeOpMaker::Conv3DTransposeOpMaker(OpProto* proto,
-                                               OpAttrChecker* op_checker)
-    : OpProtoAndCheckerMaker(proto, op_checker) {
+void Conv3DTransposeOpMaker::Make() {
   AddInput("Input",
            "(Tensor) The input tensor of convolution transpose operator."
            "The format of input tensor is NCDHW. Where N is batch size, C is "

paddle/fluid/operators/conv_transpose_op.h

@@ -30,12 +30,12 @@ using DDim = framework::DDim;
 // operator implementations can reuse the code.
 class Conv2DTransposeOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  Conv2DTransposeOpMaker(OpProto* proto, OpAttrChecker* op_checker);
+  void Make() override;
 };
 
 class Conv3DTransposeOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  Conv3DTransposeOpMaker(OpProto* proto, OpAttrChecker* op_checker);
+  void Make() override;
 };
 
 class ConvTransposeOp : public framework::OperatorWithKernel {

paddle/fluid/operators/cos_sim_op.cc

@@ -62,8 +62,7 @@ class CosSimOp : public framework::OperatorWithKernel {
 
 class CosSimOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  CosSimOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The 1st input of cos_sim op.");
     AddInput("Y", "The 2nd input of cos_sim op.");
     AddOutput("Out", "The output of cos_sim op.");

paddle/fluid/operators/crf_decoding_op.cc

@@ -18,8 +18,7 @@ namespace paddle {
 namespace operators {
 class CRFDecodingOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  CRFDecodingOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Emission",
              "(LoDTensor, default: LoDTensor<float>). A LoDTensor with shape "
              "[N x D] where N is the size of the mini-batch and D is the total "

paddle/fluid/operators/crop_op.cc

@@ -52,8 +52,7 @@ class CropOp : public framework::OperatorWithKernel {
 
 class CropOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  CropOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "The input of pad op. "
              "The input should be a k-D tensor(k > 0 and k < 7).");

paddle/fluid/operators/cross_entropy_op.cc

@@ -111,8 +111,7 @@ class CrossEntropyGradientOp : public framework::OperatorWithKernel {
 
 class CrossEntropyOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  CrossEntropyOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(Tensor, default Tensor<float>), a 2-D tensor with shape [N x D],"
              " where N is the batch size and D is the number of classes. "

paddle/fluid/operators/ctc_align_op.cc

@@ -44,8 +44,7 @@ class CTCAlignOp : public framework::OperatorWithKernel {
 
 class CTCAlignOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  CTCAlignOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Input",
              "(LodTensor, default: LoDTensor<int>), Its shape is "
              "[Lp, 1], where Lp is the sum of all input sequences' length.");

paddle/fluid/operators/cumsum_op.cc

@@ -29,8 +29,7 @@ class CumOp : public framework::OperatorWithKernel {
 
 class CumsumOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  CumsumOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "Input of Cumsum operator");
     AddOutput("Out", "Output of Cumsum operator");
     AddAttr<int>("axis",

paddle/fluid/operators/decayed_adagrad_op.cc

@@ -62,8 +62,7 @@ class DecayedAdagradOp : public framework::OperatorWithKernel {
 
 class DecayedAdagradOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  DecayedAdagradOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Param", "(Tensor) Input parameter");
     AddInput("Grad", "(Tensor) Input gradient");
     AddInput("Moment", "(Tensor) Second moment");

paddle/fluid/operators/delete_var_op.cc

@@ -34,8 +34,7 @@ class DeleteVarOp : public framework::OperatorBase {
 
 class DeleteVarOpInfoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  DeleteVarOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The input of delete op").AsDuplicable();
     AddComment(R"DOC(
 Delete Operator.

paddle/fluid/operators/detection_map_op.cc

@@ -78,8 +78,7 @@ class DetectionMAPOp : public framework::OperatorWithKernel {
 
 class DetectionMAPOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  DetectionMAPOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("DetectRes",
              "(LoDTensor) A 2-D LoDTensor with shape [M, 6] represents the "
              "detections. Each row has 6 values: "

paddle/fluid/operators/dropout_op.cc

@@ -37,8 +37,7 @@ class DropoutOp : public framework::OperatorWithKernel {
 
 class DropoutOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  DropoutOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The input of dropout op.");
     AddOutput("Out", "The output of dropout op.");
     AddOutput("Mask", "The random sampled dropout mask.").AsIntermediate();

paddle/fluid/operators/edit_distance_op.cc

@@ -49,8 +49,7 @@ class EditDistanceOp : public framework::OperatorWithKernel {
 
 class EditDistanceOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  EditDistanceOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Hyps",
              "(2-D LoDTensor<int64_t>, 2nd dim. equal to 1) "
              "The indices for hypothesis strings.");

paddle/fluid/operators/elementwise_add_op.cc

@@ -14,26 +14,8 @@ limitations under the License. */
 
 #include "paddle/fluid/operators/elementwise_add_op.h"
 #include "paddle/fluid/operators/elementwise_op.h"
-
-namespace paddle {
-namespace operators {
-class ElementwiseAddOpMaker : public ElementwiseOpMaker {
- public:
-  ElementwiseAddOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : ElementwiseOpMaker(proto, op_checker) {
-    SetComment("Add", "Out = X + Y");
-    AddComment(comment_);
-  }
-};
-}  // namespace operators
-}  // namespace paddle
-
 namespace ops = paddle::operators;
-REGISTER_OPERATOR(elementwise_add, ops::ElementwiseOp,
-                  ops::ElementwiseAddOpMaker, ops::ElementwiseOpInferVarType,
-                  paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(elementwise_add_grad, ops::ElementwiseOpGrad);
-
+REGISTER_ELEMWISE_OP(elementwise_add, "Add", "Out = X + Y");
 REGISTER_OP_CPU_KERNEL(
     elementwise_add,
     ops::ElementwiseAddKernel<paddle::platform::CPUDeviceContext, float>,

paddle/fluid/operators/elementwise_div_op.cc

@@ -14,26 +14,8 @@ limitations under the License. */
 
 #include "paddle/fluid/operators/elementwise_div_op.h"
 #include "paddle/fluid/operators/elementwise_op.h"
-
-namespace paddle {
-namespace operators {
-class ElementwiseDivOpMaker : public ElementwiseOpMaker {
- public:
-  ElementwiseDivOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : ElementwiseOpMaker(proto, op_checker) {
-    SetComment("Div", "Out = X / Y");
-    AddComment(comment_);
-  }
-};
-
-}  // namespace operators
-}  // namespace paddle
-
 namespace ops = paddle::operators;
-REGISTER_OPERATOR(elementwise_div, ops::ElementwiseOp,
-                  ops::ElementwiseDivOpMaker,
-                  paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(elementwise_div_grad, ops::ElementwiseOpGrad);
+REGISTER_ELEMWISE_OP(elementwise_div, "Div", "Out = X / Y");
 REGISTER_OP_CPU_KERNEL(
     elementwise_div,
     ops::ElementwiseDivKernel<paddle::platform::CPUDeviceContext, float>,

paddle/fluid/operators/elementwise_max_op.cc

@@ -14,25 +14,8 @@ limitations under the License. */
 
 #include "paddle/fluid/operators/elementwise_max_op.h"
 #include "paddle/fluid/operators/elementwise_op.h"
-
-namespace paddle {
-namespace operators {
-class ElementwiseMaxOpMaker : public ElementwiseOpMaker {
- public:
-  ElementwiseMaxOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : ElementwiseOpMaker(proto, op_checker) {
-    SetComment("Max", "Out = max(X, Y)");
-    AddComment(comment_);
-  }
-};
-}  // namespace operators
-}  // namespace paddle
-
 namespace ops = paddle::operators;
-REGISTER_OPERATOR(elementwise_max, ops::ElementwiseOp,
-                  ops::ElementwiseMaxOpMaker,
-                  paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(elementwise_max_grad, ops::ElementwiseOpGrad);
+REGISTER_ELEMWISE_OP(elementwise_max, "Max", "Out = max(X, Y)");
 REGISTER_OP_CPU_KERNEL(
     elementwise_max,
     ops::ElementwiseMaxKernel<paddle::platform::CPUDeviceContext, float>,

paddle/fluid/operators/elementwise_min_op.cc

@@ -14,25 +14,8 @@ limitations under the License. */
 
 #include "paddle/fluid/operators/elementwise_min_op.h"
 #include "paddle/fluid/operators/elementwise_op.h"
-
-namespace paddle {
-namespace operators {
-class ElementwiseMinOpMaker : public ElementwiseOpMaker {
- public:
-  ElementwiseMinOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : ElementwiseOpMaker(proto, op_checker) {
-    SetComment("Max", "Out = min(X, Y)");
-    AddComment(comment_);
-  }
-};
-}  // namespace operators
-}  // namespace paddle
-
 namespace ops = paddle::operators;
-REGISTER_OPERATOR(elementwise_min, ops::ElementwiseOp,
-                  ops::ElementwiseMinOpMaker,
-                  paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(elementwise_min_grad, ops::ElementwiseOpGrad);
+REGISTER_ELEMWISE_OP(elementwise_min, "Min", "Out = min(X, Y)");
 REGISTER_OP_CPU_KERNEL(
     elementwise_min,
     ops::ElementwiseMinKernel<paddle::platform::CPUDeviceContext, float>,

paddle/fluid/operators/elementwise_mul_op.cc

@@ -14,27 +14,8 @@ limitations under the License. */
 
 #include "paddle/fluid/operators/elementwise_mul_op.h"
 #include "paddle/fluid/operators/elementwise_op.h"
-
-namespace paddle {
-namespace operators {
-
-class ElementwiseMulOpMaker : public ElementwiseOpMaker {
- public:
-  ElementwiseMulOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : ElementwiseOpMaker(proto, op_checker) {
-    SetComment("Mul", "Out = X \\odot\\ Y");
-    AddComment(comment_);
-  }
-};
-
-}  // namespace operators
-}  // namespace paddle
-
 namespace ops = paddle::operators;
-REGISTER_OPERATOR(elementwise_mul, ops::ElementwiseOp,
-                  ops::ElementwiseMulOpMaker,
-                  paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(elementwise_mul_grad, ops::ElementwiseOpGrad);
+REGISTER_ELEMWISE_OP(elementwise_mul, "Mul", "Out = X \\odot\\ Y");
 REGISTER_OP_CPU_KERNEL(
     elementwise_mul,
     ops::ElementwiseMulKernel<paddle::platform::CPUDeviceContext, float>,

paddle/fluid/operators/elementwise_op.h

@@ -54,8 +54,7 @@ class ElementwiseOpInferVarType : public framework::VarTypeInference {
 
 class ElementwiseOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ElementwiseOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() final {
     AddInput("X", "(Tensor), The first input tensor of elementwise op.");
     AddInput("Y", "(Tensor), The second input tensor of elementwise op.");
     AddOutput("Out", "The output of elementwise op.");
@@ -64,12 +63,12 @@ class ElementwiseOpMaker : public framework::OpProtoAndCheckerMaker {
                  "for broadcasting Y onto X.")
         .SetDefault(-1)
         .EqualGreaterThan(-1);
-    comment_ = R"DOC(
-Limited Elementwise {name} Operator.
+    AddComment(string::Sprintf(R"DOC(
+Limited Elementwise %s Operator.
 
 The equation is:
 
-$${equation}$$
+$$%s$$
 
 $X$ is a tensor of any dimension and the dimensions of tensor $Y$ must be
 smaller than or equal to the dimensions of $X$.
@@ -100,26 +99,13 @@ For example
 Either of the inputs $X$ and $Y$ or none can carry the LoD (Level of Details)
 information. However, the output only shares the LoD information with input $X$.
 
-)DOC";
-    AddComment(comment_);
+)DOC",
+                               GetName(), GetEquation()));
   }
 
  protected:
-  std::string comment_;
-
-  void Replace(std::string* src, std::string from, std::string to) {
-    std::size_t len_from = std::strlen(from.c_str());
-    std::size_t len_to = std::strlen(to.c_str());
-    for (std::size_t pos = src->find(from); pos != std::string::npos;
-         pos = src->find(from, pos + len_to)) {
-      src->replace(pos, len_from, to);
-    }
-  }
-
-  void SetComment(std::string name, std::string equation) {
-    Replace(&comment_, "{name}", name);
-    Replace(&comment_, "{equation}", equation);
-  }
+  virtual std::string GetName() const = 0;
+  virtual std::string GetEquation() const = 0;
 };
 
 class ElementwiseOpGrad : public framework::OperatorWithKernel {
@@ -152,3 +138,16 @@ class ElementwiseOpGrad : public framework::OperatorWithKernel {
 };
 }  // namespace operators
 }  // namespace paddle
+
+#define REGISTER_ELEMWISE_OP(op_type, op_name, equation)                \
+  class __ElemwiseOp##op_type##Maker__                                  \
+      : public ::paddle::operators::ElementwiseOpMaker {                \
+   protected:                                                           \
+    virtual std::string GetName() const { return op_name; }             \
+    virtual std::string GetEquation() const { return equation; }        \
+  };                                                                    \
+  REGISTER_OPERATOR(op_type, ::paddle::operators::ElementwiseOp,        \
+                    __ElemwiseOp##op_type##Maker__,                     \
+                    ::paddle::operators::ElementwiseOpInferVarType,     \
+                    ::paddle::framework::DefaultGradOpDescMaker<true>); \
+  REGISTER_OPERATOR(op_type##_grad, ::paddle::operators::ElementwiseOpGrad)

paddle/fluid/operators/elementwise_pow_op.cc

@@ -13,17 +13,15 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #include "paddle/fluid/operators/elementwise_pow_op.h"
+#include <string>
 #include "paddle/fluid/operators/elementwise_op.h"
 
 namespace paddle {
 namespace operators {
 class ElementwisePowOpMaker : public ElementwiseOpMaker {
- public:
-  ElementwisePowOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : ElementwiseOpMaker(proto, op_checker) {
-    SetComment("Pow", "Out = X ^ Y");
-    AddComment(comment_);
-  }
+ protected:
+  std::string GetName() const override { return "Pow"; }
+  std::string GetEquation() const override { return "Out = X ^ Y"; }
 };
 }  // namespace operators
 }  // namespace paddle

paddle/fluid/operators/elementwise_sub_op.cc

@@ -14,25 +14,8 @@ limitations under the License. */
 
 #include "paddle/fluid/operators/elementwise_sub_op.h"
 #include "paddle/fluid/operators/elementwise_op.h"
-
-namespace paddle {
-namespace operators {
-class ElementwiseSubOpMaker : public ElementwiseOpMaker {
- public:
-  ElementwiseSubOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : ElementwiseOpMaker(proto, op_checker) {
-    SetComment("Sub", "Out = X - Y");
-    AddComment(comment_);
-  }
-};
-}  // namespace operators
-}  // namespace paddle
-
 namespace ops = paddle::operators;
-REGISTER_OPERATOR(elementwise_sub, ops::ElementwiseOp,
-                  ops::ElementwiseSubOpMaker,
-                  paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(elementwise_sub_grad, ops::ElementwiseOpGrad);
+REGISTER_ELEMWISE_OP(elementwise_sub, "Sub", "Out = X - Y");
 REGISTER_OP_CPU_KERNEL(
     elementwise_sub,
     ops::ElementwiseSubKernel<paddle::platform::CPUDeviceContext, float>,

paddle/fluid/operators/expand_op.cc

@@ -56,8 +56,7 @@ class ExpandOp : public framework::OperatorWithKernel {
 
 class ExpandOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ExpandOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(Tensor, default Tensor<float>). A tensor with rank in [1, 6]."
              "X is the input to be expanded.");

paddle/fluid/operators/fc_op.cc

@@ -72,8 +72,7 @@ framework::OpKernelType FCOpGrad::GetExpectedKernelType(
       layout, library);
 }
 
-FCOpMaker::FCOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-    : OpProtoAndCheckerMaker(proto, op_checker) {
+void FCOpMaker::Make() {
   AddInput("Input", "(Tensor) The input tensor of fully connected operator. ");
   AddInput("W", "(Tensor), The second input tensor of fc op.");
   AddOutput("Out", "(Tensor) The output tensor of fully connected operator. ");

paddle/fluid/operators/fc_op.h

@@ -45,7 +45,7 @@ class FCOpGrad : public framework::OperatorWithKernel {
 
 class FCOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  FCOpMaker(OpProto* proto, OpAttrChecker* op_checker);
+  void Make() override;
 };
 
 }  // namespace operators

paddle/fluid/operators/feed_op.cc

@@ -66,8 +66,7 @@ class FeedOp : public framework::OperatorBase {
 
 class FeedOpInfoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  FeedOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The input of feed op");
     AddOutput("Out", "The output of feed op");
     AddAttr<int>("col", "(int) The column of feed");

paddle/fluid/operators/fetch_op.cc

@@ -66,8 +66,7 @@ class FetchOp : public framework::OperatorBase {
 
 class FetchOpInfoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  FetchOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The input of fetch op");
     AddOutput("Out", "The output of fetch op");
     AddAttr<int>("col", "(int) The column of fetch");

paddle/fluid/operators/fill_constant_batch_size_like_op.cc

@@ -30,9 +30,8 @@ class FillConstantBatchSizeLikeOp : public BatchSizeLikeOp {
 };
 
 class FillConstantBatchSizeLikeOpMaker : public BatchSizeLikeOpMaker {
- public:
-  FillConstantBatchSizeLikeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : BatchSizeLikeOpMaker(proto, op_checker) {
+ protected:
+  void Apply() override {
     AddAttr<int>("dtype",
                  "(int, default 5 (FP32)) "
                  "Output data type")

paddle/fluid/operators/fill_constant_op.cc

@@ -59,8 +59,7 @@ class FillConstantOp : public framework::OperatorBase {
 
 class FillConstantOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  FillConstantOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddAttr<int>("dtype",
                  "(int, default 5 (FP32)) "
                  "Output data type")

paddle/fluid/operators/fill_op.cc

@@ -82,8 +82,7 @@ class FillOp : public framework::OperatorBase {
 
 class FillOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  FillOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddComment(R"DOC(Fill operator
 
 Fill an tensor with `value` and `shape`. The type of the tensor is specify by

paddle/fluid/operators/fill_zeros_like_op.cc

@@ -33,8 +33,7 @@ class FillZerosLikeOp : public framework::OperatorWithKernel {
 
 class FillZerosLikeOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  FillZerosLikeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The input of fill-zeros-like op.");
     AddOutput("Out", "The variable will be filled up with zeros.");
     AddComment(R"DOC(

paddle/fluid/operators/ftrl_op.cc

@@ -64,8 +64,7 @@ class FTRLOp : public framework::OperatorWithKernel {
 
 class FTRLOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  FTRLOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Param",
              "(Tensor, default Tensor<float>) "
              "Input parameter value that has to be updated.");

paddle/fluid/operators/gather_op.cc

@@ -67,8 +67,7 @@ class GatherGradOp : public framework::OperatorWithKernel {
 
 class GatherOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  GatherOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The source input of gather op");
     AddInput("Index", "The index input of gather op");
     AddOutput("Out", "The output of gather op");

paddle/fluid/operators/gaussian_random_batch_size_like_op.cc

@@ -32,9 +32,8 @@ class GaussianRandomBatchSizeLikeOp : public BatchSizeLikeOp {
 };
 
 class GaussianRandomBatchSizeLikeOpMaker : public BatchSizeLikeOpMaker {
- public:
-  GaussianRandomBatchSizeLikeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : BatchSizeLikeOpMaker(proto, op_checker) {
+ protected:
+  void Apply() override {
     AddAttr<float>("mean",
                    "(float, default 0.0) "
                    "mean of random tensor.")

paddle/fluid/operators/gaussian_random_op.cc

@@ -70,8 +70,7 @@ class GaussianRandomOp : public framework::OperatorWithKernel {
 
 class GaussianRandomOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  GaussianRandomOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddOutput("Out", "Output matrix of gaussian random op");
 
     AddAttr<std::vector<int>>("shape",

paddle/fluid/operators/get_places_op.cc

@@ -78,8 +78,7 @@ class GetPlacesOp : public framework::OperatorBase {
 
 class GetPlacesOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  GetPlacesOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddOutput("Out", "vector of Place");
     AddAttr<int>("device_count", "device count").SetDefault(0);
     AddAttr<std::string>("device_type", "device type")

paddle/fluid/operators/go_op.cc

@@ -89,8 +89,7 @@ class GoOp : public framework::OperatorBase {
 
 class GoOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  GoOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(kX,
              "A set of variables, which are required by operators inside the "
              "block of Go Op.")

paddle/fluid/operators/gru_op.cc

@@ -71,8 +71,7 @@ class GRUOp : public framework::OperatorWithKernel {
 
 class GRUOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  GRUOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Input",
              "(LoDTensor) The first input is a LodTensor, which supports "
              "variable-time length input sequence. The underlying tensor in "

paddle/fluid/operators/gru_unit_op.cc

@@ -71,8 +71,7 @@ class GRUUnitOp : public framework::OperatorWithKernel {
 
 class GRUUnitOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  GRUUnitOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Input",
              "(Tensor) Matrix with shape [batch_size, frame_size * 3] for the "
              "input.");

paddle/fluid/operators/hinge_loss_op.cc

@@ -46,8 +46,7 @@ class HingeLossOp : public framework::OperatorWithKernel {
 template <typename AttrType>
 class HingeLossOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  HingeLossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Logits",
              "The input value (Logits) of Hinge loss op."
              "Logits is a 2-D tensor with shape [batch_size, 1].");

paddle/fluid/operators/huber_loss_op.cc

@@ -45,8 +45,7 @@ class HuberLossOp : public framework::OperatorWithKernel {
 template <typename AttrType>
 class HuberLossOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  HuberLossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "The input value of huber loss op."
              "X is a 2-D tensor with shape [batch_size, 1].");

paddle/fluid/operators/im2sequence_op.cc

@@ -54,8 +54,7 @@ class Im2SequenceOp : public framework::OperatorWithKernel {
 
 class Im2SequenceOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  Im2SequenceOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(Tensor) The input tensor has NCHW format."
              "N: batch size"

paddle/fluid/operators/increment_op.cc

@@ -47,8 +47,7 @@ class IncrementOp : public framework::OperatorWithKernel {
 
 class IncrementOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  IncrementOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(Tensor) The input tensor of increment operator");
     AddOutput("Out", "(Tensor) The output tensor of increment operator.");
     AddAttr<float>("step",

paddle/fluid/operators/iou_similarity_op.cc

@@ -42,8 +42,7 @@ class IOUSimilarityOp : public framework::OperatorWithKernel {
 
 class IOUSimilarityOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  IOUSimilarityOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(LoDTensor, default LoDTensor<float>) "
              "Box list X is a 2-D LoDTensor with shape [N, 4] holds N boxes, "

paddle/fluid/operators/is_empty_op.cc

@@ -48,8 +48,7 @@ class IsEmptyOp : public framework::OperatorBase {
 
 class IsEmptyOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  IsEmptyOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(kInput, "(Tensor) Tensor which is to be checked.");
     AddOutput(kOutput, "(Tensor) a boolean Tensor that indicate empty or not.");
     AddComment(R"DOC(

paddle/fluid/operators/l1_norm_op.cc

@@ -48,8 +48,7 @@ class L1NormGradOp : public framework::OperatorWithKernel {
 
 class L1NormOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  L1NormOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(Tensor) The input of l1_norm op.");
     AddOutput("Out", "(Scalar) The output of l1_norm op.");
     AddComment(R"DOC(

paddle/fluid/operators/label_smooth_op.cc

@@ -47,8 +47,7 @@ class LabelSmoothOp : public framework::OperatorWithKernel {
 
 class LabelSmoothOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LabelSmoothOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(LoDTensor) The input labels of LabelSmooth operator. This "
              "input can be batched labels in one-hot encoding or output from "

paddle/fluid/operators/layer_norm_op.cc

@@ -61,8 +61,7 @@ class LayerNormOp : public framework::OperatorWithKernel {
 
 class LayerNormOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LayerNormOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(LoDTensor) The input tensor.");
     AddInput("Scale",
              "(Tensor, optional) Scale is a 1-dimensional tensor of size "

paddle/fluid/operators/linear_chain_crf_op.cc

@@ -19,8 +19,7 @@ namespace operators {
 
 class LinearChainCRFOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LinearChainCRFOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Emission",
              "(LoDTensor, default LoDTensor<float>) "
              "A 2-D LoDTensor with shape [N x D], where N is the size of the "

paddle/fluid/operators/listen_and_serv_op.cc

@@ -343,8 +343,7 @@ void ListenAndServOp::RunImpl(const framework::Scope &scope,
 
 class ListenAndServOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ListenAndServOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() {
     AddInput("X", "(Tensor) Variables that server recv.").AsDuplicable();
     AddComment(R"DOC(
 ListenAndServ operator

paddle/fluid/operators/load_combine_op.cc

@@ -77,8 +77,7 @@ class LoadCombineOp : public framework::OperatorBase {
 
 class LoadCombineOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LoadCombineOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddOutput(
         "Out",
         "(vector) The output LoDTensors that will be read from the input file.")

paddle/fluid/operators/load_op.cc

@@ -73,8 +73,7 @@ class LoadOp : public framework::OperatorBase {
 
 class LoadOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LoadOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddOutput("Out", "(Tensor) The tensor need to be loaded");
     AddAttr<bool>(
         "load_as_fp16",

paddle/fluid/operators/lod_array_length_op.cc

@@ -40,8 +40,7 @@ class LoDArrayLengthOp : public framework::OperatorBase {
 
 class LoDArrayLengthProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LoDArrayLengthProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(LoDTensorArray) The input tensor array.");
     AddOutput("Out", "(Tensor) 1x1 CPU Tensor of length, int64_t");
     AddComment(R"DOC(

paddle/fluid/operators/lod_rank_table_op.cc

@@ -38,8 +38,7 @@ class LoDRankTableOp : public framework::OperatorBase {
 
 class LoDRankTableOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LoDRankTableOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(LoDTensor) input lod tensor, must contain lod information.");
     AddOutput("Out", "(LoDRankTable) The rank table of specific level.");

paddle/fluid/operators/lod_reset_op.cc

@@ -47,8 +47,7 @@ class LoDResetOp : public framework::OperatorWithKernel {
 
 class LoDResetOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LoDResetOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(Tensor, LoDTensor) Input variable of LoDResetOp which "
              "could be a Tensor or LoDTensor, where the data of output "

paddle/fluid/operators/lod_tensor_to_array_op.cc

@@ -105,8 +105,7 @@ class LoDTensorToArrayOp : public framework::OperatorBase {
 
 class LoDTensorToArrayOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LoDTensorToArrayOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "");
     AddInput("RankTable", "");
     AddOutput("Out", "");

paddle/fluid/operators/log_loss_op.cc

@@ -46,8 +46,7 @@ class LogLossOp : public framework::OperatorWithKernel {
 template <typename AttrType>
 class LogLossOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LogLossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Predicted",
              "The input value (Predicted) of Log loss op."
              "Predicted is a 2-D tensor with shape [batch_size, 1].");

paddle/fluid/operators/logical_op.cc

@@ -21,8 +21,7 @@ namespace operators {
 template <typename OpComment>
 class BinaryLogicalOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  BinaryLogicalOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     OpComment comment;
     AddInput("X",
              string::Sprintf("(LoDTensor) Left hand operand of %s operator",
@@ -45,8 +44,7 @@ Each element of Out is calculated by %s
 template <typename OpComment>
 class UnaryLogicalOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  UnaryLogicalOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     OpComment comment;
     AddInput("X", string::Sprintf("(LoDTensor) Operand of %s operator",
                                   comment.type));

paddle/fluid/operators/lookup_sparse_table_op.cc

@@ -105,8 +105,7 @@ class LookupSparseTableOp : public framework::OperatorBase {
 
 class LookupSparseTableOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LookupSparseTableOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("W",
              "(SelectedRows) The input represents embedding table, "
              "which is a learnable parameter.");

paddle/fluid/operators/lookup_table_op.cc

@@ -58,8 +58,7 @@ class LookupTableOp : public framework::OperatorWithKernel {
 
 class LookupTableOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LookupTableOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("W",
              "(Tensor) The input represents embedding tensors, "
              "which is a learnable parameter.");

paddle/fluid/operators/lrn_op.cc

@@ -169,8 +169,7 @@ class LRNOp : public framework::OperatorWithKernel {
 template <typename T>
 class LRNOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LRNOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(Tensor) The input of LRN operator. "
              "It must be a 4D tenor with NCHW format.");

paddle/fluid/operators/lstm_op.cc

@@ -103,8 +103,7 @@ class LSTMOp : public framework::OperatorWithKernel {
 
 class LSTMOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LSTMOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Input",
              "(LoDTensor) the first input is a LodTensor, which support "
              "variable-time length input sequence. The underlying tensor in "

paddle/fluid/operators/lstm_unit_op.cc

@@ -48,8 +48,7 @@ class LstmUnitOp : public framework::OperatorWithKernel {
 
 class LstmUnitOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LstmUnitOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "Lstm unit only applies non-linear activations, please make sure"
              "that linear tranformation has already been applied to `X`. "

paddle/fluid/operators/lstmp_op.cc

@@ -120,8 +120,7 @@ class LSTMPOp : public framework::OperatorWithKernel {
 
 class LSTMPOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LSTMPOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Input",
              "(LoDTensor) the input for sequence data, which supports "
              "variable-time length input sequence. The underlying tensor in "

paddle/fluid/operators/margin_rank_loss_op.cc

@@ -42,8 +42,7 @@ class MarginRankLossOp : public framework::OperatorWithKernel {
 template <typename T>
 class MarginRankLossOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MarginRankLossOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X1",
              "(2-D tensor with shape [batch_size x 1]) The score for "
              "one item X1 to be ranked, from pairwise ranking model.");

paddle/fluid/operators/matmul_op.cc

@@ -322,8 +322,7 @@ class MatMulOp : public framework::OperatorWithKernel {
 
 class MatMulOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MatMulOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The first input of MatMul op");
     AddInput("Y", "The second input of MatMul op");
     AddOutput("Out", "The output of MatMul op");

paddle/fluid/operators/max_sequence_len_op.cc

@@ -41,8 +41,7 @@ class MaxSeqenceLenOp : public framework::OperatorBase {
 
 class MaxSeqenceLenOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MaxSeqenceLenOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("RankTable", "The lod_rank_table.");
     AddOutput("Out", "The max sequence length.");
     AddComment(

paddle/fluid/operators/maxout_op.cc

@@ -22,8 +22,7 @@ using framework::Tensor;
 
 class MaxOutOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MaxOutOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(
         "X",
         "(Tensor) The input tensor of maxout operator. "

paddle/fluid/operators/mean_op.cc

@@ -32,8 +32,7 @@ class MeanOp : public framework::OperatorWithKernel {
 
 class MeanOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MeanOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The input of mean op");
     AddOutput("Out", "The output of mean op");
     AddComment(R"DOC(

paddle/fluid/operators/merge_lod_tensor_op.cc

@@ -121,8 +121,7 @@ class MergeLoDTensorOp : public framework::OperatorBase {
 
 class MergeLoDTensorOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MergeLoDTensorOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "The input LoDTensor, contains complete lod information to "
              "construct the output");

paddle/fluid/operators/mine_hard_examples_op.cc

@@ -253,8 +253,7 @@ class MineHardExamplesOp : public framework::OperatorWithKernel {
 
 class MineHardExamplesOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MineHardExamplesOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(
         "ClsLoss",
         "(Tensor, default Tensor<float>), The classification loss with shape "

paddle/fluid/operators/minus_op.cc

@@ -48,8 +48,7 @@ class MinusOp : public framework::OperatorWithKernel {
 
 class MinusOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MinusOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The left tensor of minus operator.");
     AddInput("Y", "The right tensor of minus operator.");
     AddOutput("Out", "The output tensor of minus operator.");

paddle/fluid/operators/modified_huber_loss_op.cc

@@ -39,8 +39,7 @@ class ModifiedHuberLossOp : public framework::OperatorWithKernel {
 
 class ModifiedHuberLossOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ModifiedHuberLossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "The input tensor of modified huber loss op. "
              "X is 2-D tensor with shape [batch_size, 1].");

paddle/fluid/operators/momentum_op.cc

@@ -62,8 +62,7 @@ class MomentumOp : public framework::OperatorWithKernel {
 
 class MomentumOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MomentumOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Param",
              "(Tensor, default Tensor<float>) "
              "Input parameter that has to be updated");

paddle/fluid/operators/mul_op.cc

@@ -96,8 +96,7 @@ class MulOp : public framework::OperatorWithKernel {
 
 class MulOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MulOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(Tensor), The first input tensor of mul op.");
     AddInput("Y", "(Tensor), The second input tensor of mul op.");
     AddOutput("Out", "(Tensor), The output tensor of mul op.");

paddle/fluid/operators/multiclass_nms_op.cc

@@ -309,8 +309,7 @@ class MultiClassNMSKernel : public framework::OpKernel<T> {
 
 class MultiClassNMSOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MultiClassNMSOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("BBoxes",
              "(Tensor) A 3-D Tensor with shape [N, M, 4] represents the "
              "predicted locations of M bounding bboxes, N is the batch size. "

paddle/fluid/operators/multiplex_op.cc

@@ -61,8 +61,7 @@ class MultiplexOp : public framework::OperatorWithKernel {
 
 class MultiplexOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MultiplexOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Ids", "The index tensor of multiplex operator.");
     AddInput("X", "The candidate tensors of multiplex operator.")
         .AsDuplicable();

paddle/fluid/operators/nccl_op.cc

@@ -76,8 +76,7 @@ class NCCLInitOpShapeInference : public framework::InferShapeBase {
 
 class NCCLInitOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  NCCLInitOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(kParallelScopes, "The working place of parallel do.");
     AddOutput("Communicator",
               "Create Communicator for communicating between gpus");
@@ -118,8 +117,7 @@ class NCCLAllReduceOp : public framework::OperatorWithKernel {
 // AllReduceOp
 class NCCLAllReduceOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  NCCLAllReduceOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The input of AllReduce op");
     AddInput("Communicator", "Communicator for communicating between gpus");
     AddOutput("Out", "The output of AllReduce op");
@@ -165,8 +163,7 @@ class NCCLReduceOp : public framework::OperatorWithKernel {
 // ReduceOp
 class NCCLReduceOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  NCCLReduceOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The input of Reduce op");
     AddInput("Communicator", "Communicator for communicating between gpus");
     AddOutput("Out", "The output of Reduce op");
@@ -214,8 +211,7 @@ class NCCLBcastOp : public framework::OperatorWithKernel {
 // BcastOp
 class NCCLBcastOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  NCCLBcastOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The input of BcastSend op");
     AddInput("Communicator", "Communicator for communicating between gpus");
     AddOutput("Out", "The output of Bcast");

paddle/fluid/operators/nce_op.cc

@@ -75,8 +75,7 @@ class NCEOp : public framework::OperatorWithKernel {
 
 class NCEOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  NCEOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Input", "(Tensor) A tensor of shape [batch_size, dim].");
     AddInput(
         "Label",

paddle/fluid/operators/norm_op.cc

@@ -19,8 +19,7 @@ namespace operators {
 template <typename AttrType>
 class NormOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  NormOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(
         "X",
         "(Tensor) The input tensor of norm operator. "

paddle/fluid/operators/one_hot_op.cc

@@ -46,8 +46,7 @@ class OneHotOp : public framework::OperatorWithKernel {
 
 class OneHotOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  OneHotOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(LoDTensor, LoDTensor<int>) Input variable with rank at least 2. "
              "The last dimension of X should be 1. Each value of X is an index "

paddle/fluid/operators/pad_op.cc

@@ -48,8 +48,7 @@ class PadOp : public framework::OperatorWithKernel {
 
 class PadOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  PadOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "The input of pad op. "
              "The input should be a k-D tensor(k > 0 and k < 7)");

paddle/fluid/operators/parallel_do_op.cc

@@ -196,8 +196,7 @@ class ParallelDoOp : public framework::OperatorBase {
 
 class ParallelDoOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ParallelDoOpProtoMaker(OpProto *proto, framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(kInputs, "").AsDuplicable();
     AddInput(kParameters, "").AsDuplicable();
     AddInput(kPlaces, "");

paddle/fluid/operators/pool_op.cc

@@ -135,8 +135,7 @@ framework::OpKernelType PoolOpGrad::GetExpectedKernelType(
                                  library_);
 }
 
-Pool2dOpMaker::Pool2dOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-    : OpProtoAndCheckerMaker(proto, op_checker) {
+void Pool2dOpMaker::Make() {
   AddInput(
       "X",
       "(Tensor) The input tensor of pooling operator. "
@@ -229,8 +228,7 @@ Example:
 )DOC");
 }
 
-Pool3dOpMaker::Pool3dOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-    : OpProtoAndCheckerMaker(proto, op_checker) {
+void Pool3dOpMaker::Make() {
   AddInput("X",
            "(Tensor) The input tensor of pooling operator. "
            "The format of input tensor is NCDHW, where N is batch size, C is "

paddle/fluid/operators/pool_op.h

@@ -50,12 +50,12 @@ class PoolOpGrad : public framework::OperatorWithKernel {
 
 class Pool2dOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  Pool2dOpMaker(OpProto* proto, OpAttrChecker* op_checker);
+  void Make() override;
 };
 
 class Pool3dOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  Pool3dOpMaker(OpProto* proto, OpAttrChecker* op_checker);
+  void Make() override;
 };
 
 template <typename DeviceContext, typename T>

paddle/fluid/operators/pool_with_index_op.cc

@@ -100,8 +100,7 @@ class MaxPoolWithIndexOpGrad : public framework::OperatorWithKernel {
 
 class MaxPool2dWithIndexOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MaxPool2dWithIndexOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(
         "X",
         "(Tensor) The input tensor of pooling operator. "
@@ -177,8 +176,7 @@ Example:
 
 class MaxPool3dWithIndexOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MaxPool3dWithIndexOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(Tensor) The input tensor of pooling operator. "
              "The format of input tensor is NCDHW, where N is batch size, C is "

paddle/fluid/operators/positive_negative_pair_op.cc

@@ -95,8 +95,7 @@ class PositiveNegativePairOp : public framework::OperatorWithKernel {
 
 class PositiveNegativePairOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  PositiveNegativePairOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Score",
              "(Tensor, float) Model Score on an item (with "
              "respect to QueryID). It's a 2-D tensor with shape [batch_size, "

paddle/fluid/operators/precision_recall_op.cc

@@ -90,8 +90,7 @@ class PrecisionRecallOp : public framework::OperatorWithKernel {
 
 class PrecisionRecallOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  PrecisionRecallOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("MaxProbs",
              "(Tensor, default Tensor<float>) A 2-D tensor with shape N x 1, "
              "where N is the batch size. Each row contains the max probability "

paddle/fluid/operators/prefetch_op.cc

@@ -64,8 +64,7 @@ class PrefetchOp : public framework::OperatorBase {
 
 class PrefetchOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  PrefetchOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() {
     AddInput("X", "(LoDTensor) Input Id variables to be sent").AsDuplicable();
     AddOutput("RPCClient",
               "(RPCClient) The RPC client object which will be"

paddle/fluid/operators/prelu_op.cc

@@ -38,8 +38,7 @@ class PReluOp : public framework::OperatorWithKernel {
 
 class PReluOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  PReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The input tensor of prelu operator.");
     AddInput("Alpha", "The alpha weight of prelu operator.");
     AddOutput("Out", "The output tensor of prelu operator.");

paddle/fluid/operators/print_op.cc

@@ -209,8 +209,7 @@ class TensorPrintOp : public framework::OperatorBase {
 
 class PrintOpProtoAndCheckMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  PrintOpProtoAndCheckMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("In", "Input tensor to be displayed.");
     AddAttr<int>("first_n", "Only log `first_n` number of times.");
     AddAttr<std::string>("message", "A string message to print as a prefix.");

paddle/fluid/operators/prior_box_op.cc

@@ -79,8 +79,7 @@ class PriorBoxOp : public framework::OperatorWithKernel {
 
 class PriorBoxOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  PriorBoxOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Input",
              "(Tensor, default Tensor<float>), "
              "the input feature data of PriorBoxOp, The layout is NCHW.");

paddle/fluid/operators/proximal_adagrad_op.cc

@@ -66,8 +66,7 @@ class ProximalAdagradOp : public framework::OperatorWithKernel {
 
 class ProximalAdagradOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ProximalAdagradOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Param",
              "(Tensor, default Tensor<float>) "
              "Input parameter that has to be updated.");

paddle/fluid/operators/proximal_gd_op.cc

@@ -54,8 +54,7 @@ class ProximalGDOp : public framework::OperatorWithKernel {
 
 class ProximalGDOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ProximalGDOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Param",
              "(Tensor, default Tensor<float>) "
              "Input parameter value that has to be updated.");

paddle/fluid/operators/rank_loss_op.cc

@@ -46,8 +46,7 @@ class RankLossOp : public framework::OperatorWithKernel {
 
 class RankLossOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  RankLossOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Label",
              "(2-D Tensor with shape [batch_size x 1]) "
              "The label indicating A ranked higher than B or not.");

paddle/fluid/operators/read_op.cc

@@ -79,8 +79,7 @@ class ReadOp : public framework::OperatorBase {
 
 class ReadOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ReadOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(op_proto, op_checker) {
+  void Make() override {
     AddInput("Reader", "(ReaderHolder) The executed reader.");
     AddOutput("Out", "(LoDTensor) The output data.").AsDuplicable();
     AddComment(R"DOC(

paddle/fluid/operators/reader/create_batch_reader_op.cc

@@ -52,9 +52,8 @@ class CreateBatchReaderOp : public framework::OperatorBase {
 };
 
 class CreateBatchReaderOpMaker : public DecoratedReaderMakerBase {
- public:
-  CreateBatchReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
-      : DecoratedReaderMakerBase(op_proto, op_checker) {
+ protected:
+  void Apply() override {
     AddAttr<int>("batch_size",
                  "How many instances the batch reader yields each time.")
         .GreaterThan(0);

paddle/fluid/operators/reader/create_double_buffer_reader_op.cc

@@ -113,14 +113,13 @@ class CreateDoubleBufferReaderOp : public framework::OperatorBase {
 };
 
 class CreateDoubleBufferReaderOpMaker : public DecoratedReaderMakerBase {
- public:
-  CreateDoubleBufferReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
-      : DecoratedReaderMakerBase(op_proto, op_checker) {
+ protected:
+  void Apply() override {
     AddComment(R"DOC(
       CreateDoubleBufferReader Operator
 
       A double buffer reader takes another reader as its 'underlying reader'.
-      It launches another thread to execute the 'underlying reader' asynchronously, 
+      It launches another thread to execute the 'underlying reader' asynchronously,
       which prevents reading process from blocking subsequent training.
     )DOC");
     std::unordered_set<std::string> enum_range;

paddle/fluid/operators/reader/create_multi_pass_reader_op.cc

@@ -65,20 +65,19 @@ class CreateMultiPassReaderOp : public framework::OperatorBase {
 };
 
 class CreateMultiPassReaderOpMaker : public DecoratedReaderMakerBase {
- public:
-  CreateMultiPassReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
-      : DecoratedReaderMakerBase(op_proto, op_checker) {
+ protected:
+  void Apply() override {
     AddAttr<int>("pass_num", "The number of pass to run.").GreaterThan(0);
     AddComment(R"DOC(
       CreateMultiPassReader Operator
 
-      This operator creates a multi-pass reader. A multi-pass reader 
-      is used to yield data for several pass training continuously. 
+      This operator creates a multi-pass reader. A multi-pass reader
+      is used to yield data for several pass training continuously.
       It takes the number of passes to run as one of its attributes
-      ('pass_num'), and maintains a pass counter to record how many 
-      passes it has completed. When the underlying reader reaches the 
-      EOF, the multi-pass reader checks whether it has completed training 
-      of the given number of pass. If not, the underlying reader will 
+      ('pass_num'), and maintains a pass counter to record how many
+      passes it has completed. When the underlying reader reaches the
+      EOF, the multi-pass reader checks whether it has completed training
+      of the given number of pass. If not, the underlying reader will
       be re-initialized and starts a new pass automatically.
     )DOC");
   }

paddle/fluid/operators/reader/create_random_data_generator_op.cc

@@ -84,9 +84,8 @@ class CreateRandomDataGeneratorOp : public framework::OperatorBase {
 };
 
 class CreateRandomDataGeneratorOpMaker : public FileReaderMakerBase {
- public:
-  CreateRandomDataGeneratorOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
-      : FileReaderMakerBase(op_proto, op_checker) {
+ protected:
+  void Apply() override {
     AddAttr<float>("min", "The lower bound of reader's uniform distribution.");
     AddAttr<float>("max", "The upper bound of reader's uniform distribution.");
     AddComment(R"DOC(

paddle/fluid/operators/reader/create_recordio_file_reader_op.cc

@@ -76,9 +76,8 @@ class CreateRecordIOReaderOp : public framework::OperatorBase {
 };
 
 class CreateRecordIOReaderOpMaker : public FileReaderMakerBase {
- public:
-  CreateRecordIOReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
-      : FileReaderMakerBase(op_proto, op_checker) {
+ protected:
+  void Apply() override {
     AddAttr<std::string>("filename", "The filename of record io reader");
     AddComment(R"DOC(
       CreateRecordIOReader Operator

paddle/fluid/operators/reader/create_shuffle_reader_op.cc

@@ -92,9 +92,8 @@ class CreateShuffleReaderOp : public framework::OperatorBase {
 };
 
 class CreateShuffleReaderOpMaker : public DecoratedReaderMakerBase {
- public:
-  CreateShuffleReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
-      : DecoratedReaderMakerBase(op_proto, op_checker) {
+ protected:
+  void Apply() override {
     AddAttr<int>("buffer_size", "The shuffle buffer size.").GreaterThan(0);
     AddComment(R"DOC(
       CreateShuffleReader Operator

paddle/fluid/operators/reader/create_threaded_reader_op.cc

@@ -53,17 +53,16 @@ class CreateThreadedReaderOp : public framework::OperatorBase {
 };
 
 class CreateThreadedReaderOpMaker : public DecoratedReaderMakerBase {
- public:
-  CreateThreadedReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
-      : DecoratedReaderMakerBase(op_proto, op_checker) {
+ protected:
+  void Apply() override {
     AddComment(R"DOC(
       CreateThreadedReader Operator
 
-      This operator creates a threaded reader. A threaded reader's 
-      'ReadNext()' can be invoked by several threads at the same 
-      time. 
-      When the attribute 'safe_mode' is true, the threaded reader's 
-      'ReInit()' is disabled to avoid unexpected bugs in multi-thread 
+      This operator creates a threaded reader. A threaded reader's
+      'ReadNext()' can be invoked by several threads at the same
+      time.
+      When the attribute 'safe_mode' is true, the threaded reader's
+      'ReInit()' is disabled to avoid unexpected bugs in multi-thread
       environment.
     )DOC");
   }

paddle/fluid/operators/reader/open_files_op.cc

@@ -185,9 +185,8 @@ class OpenFilesOp : public framework::OperatorBase {
 };
 
 class OpenFilesOpMaker : public FileReaderMakerBase {
- public:
-  OpenFilesOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
-      : FileReaderMakerBase(op_proto, op_checker) {
+ protected:
+  void Apply() override {
     AddAttr<std::vector<std::string>>("file_names", "Files to be read.");
     AddAttr<int>("thread_num", "The maximal concurrent prefetch thread number.")
         .GreaterThan(0);
@@ -196,7 +195,7 @@ class OpenFilesOpMaker : public FileReaderMakerBase {
     AddComment(R"DOC(
       OpenFiles Operator
 
-      An OpenFilesOp creates a MultiFileReader, which is able to 
+      An OpenFilesOp creates a MultiFileReader, which is able to
       read data multi-threaded from multiple files.
     )DOC");
   }

paddle/fluid/operators/reader/reader_op_registry.cc

@@ -53,10 +53,7 @@ std::unique_ptr<framework::ReaderBase> CreateReaderByFileName(
   return std::unique_ptr<framework::ReaderBase>(reader);
 }
 
-FileReaderMakerBase::FileReaderMakerBase(
-    framework::OpProtoAndCheckerMaker::OpProto* op_proto,
-    framework::OpAttrChecker* op_checker)
-    : OpProtoAndCheckerMaker(op_proto, op_checker) {
+void FileReaderMakerBase::Make() {
   AddOutput("Out", "(ReaderHolder) The created random reader.").AsDuplicable();
   AddAttr<std::vector<int>>("shape_concat", "The concat of all data's shapes.");
   AddAttr<std::vector<int>>(
@@ -68,6 +65,7 @@ FileReaderMakerBase::FileReaderMakerBase(
       "It means the reader will generate two data each time,"
       "whose shapes are [2,3,4] and [5,6] respectively.");
   AddAttr<std::vector<int>>("lod_levels", "The LoD levels of each data.");
+  Apply();
 }
 
 void FileReaderInferShape::operator()(framework::InferShapeContext* ctx) const {
@@ -127,13 +125,11 @@ void DecoratedReaderInferVarType::operator()(
   out_reader->SetDataTypes(in_reader->GetDataTypes());
 }
 
-DecoratedReaderMakerBase::DecoratedReaderMakerBase(
-    framework::OpProtoAndCheckerMaker::OpProto* op_proto,
-    framework::OpAttrChecker* op_checker)
-    : OpProtoAndCheckerMaker(op_proto, op_checker) {
+void DecoratedReaderMakerBase::Make() {
   AddInput("UnderlyingReader",
            "(ReaderHolder) The underlying reader for creating a batch reader.");
   AddOutput("Out", "(ReaderHolder) The created batch reader.");
+  Apply();
 }
 
 }  // namespace reader

paddle/fluid/operators/reader/reader_op_registry.h

@@ -47,7 +47,10 @@ extern std::vector<framework::DDim> RestoreShapes(
 
 class FileReaderMakerBase : public framework::OpProtoAndCheckerMaker {
  public:
-  FileReaderMakerBase(OpProto* op_proto, OpAttrChecker* op_checker);
+  void Make() final;
+
+ protected:
+  virtual void Apply() = 0;
 };
 
 class FileReaderInferShape : public framework::InferShapeBase {
@@ -76,7 +79,10 @@ class DecoratedReaderInferVarType : public framework::VarTypeInference {
 
 class DecoratedReaderMakerBase : public framework::OpProtoAndCheckerMaker {
  public:
-  DecoratedReaderMakerBase(OpProto* op_proto, OpAttrChecker* op_checker);
+  void Make() final;
+
+ protected:
+  virtual void Apply() = 0;
 };
 
 }  // namespace reader

paddle/fluid/operators/recurrent_op.cc

@@ -508,8 +508,7 @@ class RecurrentGradOp : public RecurrentBase {
 
 class RecurrentOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  RecurrentOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(kInputs, "rnn inputs").AsDuplicable();
     AddInput(kInitialStates, "rnn initial states").AsDuplicable();
     AddInput(kParameters,

paddle/fluid/operators/recv_op.cc

@@ -53,8 +53,7 @@ class RecvOp : public framework::OperatorBase {
 
 class RecvOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  RecvOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() {
     AddOutput("Out", "(Tensor) Variables to get from server.").AsDuplicable();
     AddComment(R"DOC(
 Recv operator

paddle/fluid/operators/reduce_op.cc

@@ -90,8 +90,7 @@ class ReduceGradOp : public framework::OperatorWithKernel {
 
 class ReduceOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ReduceOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() final {
     AddInput("X",
              "(Tensor) The input tensor. Tensors with rank at most 6 are "
              "supported.");
@@ -111,78 +110,20 @@ class ReduceOpMaker : public framework::OpProtoAndCheckerMaker {
                   "(bool, default false) "
                   "If true, output a scalar reduced along all dimensions.")
         .SetDefault(false);
-    comment_ = R"DOC(
-{ReduceOp} Operator.
+    AddComment(string::Sprintf(R"DOC(
+%s Operator.
 
-This operator computes the {reduce} of input tensor along the given dimension. 
+This operator computes the %s of input tensor along the given dimension.
 The result tensor has 1 fewer dimension than the input unless keep_dim is true.
 If reduce_all is true, just reduce along all dimensions and output a scalar.
 
-)DOC";
-    AddComment(comment_);
+)DOC",
+                               GetOpType(), GetName()));
   }
 
  protected:
-  std::string comment_;
-
-  void Replace(std::string *src, std::string from, std::string to) {
-    std::size_t len_from = std::strlen(from.c_str());
-    std::size_t len_to = std::strlen(to.c_str());
-    for (std::size_t pos = src->find(from); pos != std::string::npos;
-         pos = src->find(from, pos + len_to)) {
-      src->replace(pos, len_from, to);
-    }
-  }
-
-  void SetComment(std::string name, std::string op) {
-    Replace(&comment_, "{ReduceOp}", name);
-    Replace(&comment_, "{reduce}", op);
-  }
-};
-
-class ReduceSumOpMaker : public ReduceOpMaker {
- public:
-  ReduceSumOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : ReduceOpMaker(proto, op_checker) {
-    SetComment("ReduceSum", "sum");
-    AddComment(comment_);
-  }
-};
-
-class ReduceMeanOpMaker : public ReduceOpMaker {
- public:
-  ReduceMeanOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : ReduceOpMaker(proto, op_checker) {
-    SetComment("ReduceMean", "mean");
-    AddComment(comment_);
-  }
-};
-
-class ReduceMaxOpMaker : public ReduceOpMaker {
- public:
-  ReduceMaxOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : ReduceOpMaker(proto, op_checker) {
-    SetComment("ReduceMax", "max");
-    AddComment(comment_);
-  }
-};
-
-class ReduceMinOpMaker : public ReduceOpMaker {
- public:
-  ReduceMinOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : ReduceOpMaker(proto, op_checker) {
-    SetComment("ReduceMin", "min");
-    AddComment(comment_);
-  }
-};
-
-class ReduceProdOpMaker : public ReduceOpMaker {
- public:
-  ReduceProdOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : ReduceOpMaker(proto, op_checker) {
-    SetComment("ReduceProd", "production");
-    AddComment(comment_);
-  }
+  virtual std::string GetName() const = 0;
+  virtual std::string GetOpType() const = 0;
 };
 
 }  // namespace operators
@@ -190,25 +131,21 @@ class ReduceProdOpMaker : public ReduceOpMaker {
 
 namespace ops = paddle::operators;
 
-REGISTER_OPERATOR(reduce_sum, ops::ReduceOp, ops::ReduceSumOpMaker,
-                  paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(reduce_sum_grad, ops::ReduceGradOp);
-
-REGISTER_OPERATOR(reduce_mean, ops::ReduceOp, ops::ReduceMeanOpMaker,
-                  paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(reduce_mean_grad, ops::ReduceGradOp);
-
-REGISTER_OPERATOR(reduce_max, ops::ReduceOp, ops::ReduceMaxOpMaker,
-                  paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(reduce_max_grad, ops::ReduceGradOp);
-
-REGISTER_OPERATOR(reduce_min, ops::ReduceOp, ops::ReduceMinOpMaker,
-                  paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(reduce_min_grad, ops::ReduceGradOp);
-
-REGISTER_OPERATOR(reduce_prod, ops::ReduceOp, ops::ReduceProdOpMaker,
-                  paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(reduce_prod_grad, ops::ReduceGradOp);
+#define REGISTER_REDUCE_OP(op_name)                                        \
+  class __##op_name##Maker__ : public ops::ReduceOpMaker {                 \
+   protected:                                                              \
+    virtual std::string GetName() const { return #op_name; }               \
+    virtual std::string GetOpType() const { return "Reduce " #op_name; }   \
+  };                                                                       \
+  REGISTER_OPERATOR(reduce_##op_name, ops::ReduceOp, __##op_name##Maker__, \
+                    paddle::framework::DefaultGradOpDescMaker<true>);      \
+  REGISTER_OPERATOR(reduce_##op_name##_grad, ops::ReduceGradOp)
+
+REGISTER_REDUCE_OP(sum);
+REGISTER_REDUCE_OP(mean);
+REGISTER_REDUCE_OP(max);
+REGISTER_REDUCE_OP(min);
+REGISTER_REDUCE_OP(prod);
 
 #define REGISTER_REDUCE_CPU_KERNEL(reduce_type, functor, grad_functor)         \
   REGISTER_OP_CPU_KERNEL(reduce_type,                                          \

paddle/fluid/operators/reorder_lod_tensor_by_rank_op.cc

@@ -23,9 +23,7 @@ namespace operators {
 class ReorderLoDTensorByRankTableOpProtoMaker
     : public framework::OpProtoAndCheckerMaker {
  public:
-  ReorderLoDTensorByRankTableOpProtoMaker(OpProto *proto,
-                                          OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(LoDTensor), the input lod tensor to be reordered according to "
              "Input(RankTable).");

paddle/fluid/operators/reshape_op.cc

@@ -22,8 +22,7 @@ namespace operators {
 
 class ReshapeOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ReshapeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(Tensor). The input tensor of reshape operator.");
     AddInput("Shape",
              "(Tensor<int32>, optional). If provided, reshape according to "

paddle/fluid/operators/rmsprop_op.cc

@@ -63,8 +63,7 @@ class RmspropOp : public framework::OperatorWithKernel {
 
 class RmspropOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  RmspropOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Param",
              "(Tensor, default Tensor<float>) "
              "Input parameter value that has to be updated.");

paddle/fluid/operators/rnn_memory_helper_op.cc

@@ -59,8 +59,7 @@ class RNNMemoryHelperOpShapeInference : public framework::InferShapeBase {
 
 class RNNMemoryHelperOpInfoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  RNNMemoryHelperOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "");
     AddOutput("Out", "");
     AddAttr<int>("dtype",
@@ -117,8 +116,7 @@ class RNNMemoryHelperGradOp : public framework::OperatorBase {
 class RNNMemoryHelperGradOpInfoMaker
     : public framework::OpProtoAndCheckerMaker {
  public:
-  RNNMemoryHelperGradOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(framework::GradVarName("Out"), "");
     AddInput("X", "");
     AddInput("Out", "");

paddle/fluid/operators/roi_pool_op.cc

@@ -98,8 +98,7 @@ class ROIPoolGradOp : public framework::OperatorWithKernel {
 
 class ROIPoolOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ROIPoolOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(Tensor), "
              "the input of ROIPoolOp. "

paddle/fluid/operators/row_conv_op.cc

@@ -76,8 +76,7 @@ class RowConvGradOp : public framework::OperatorWithKernel {
 
 class RowConvOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  RowConvOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(LoDTensor), the input(X) is a LodTensor, which supports "
              "variable time-length input sequences. The underlying tensor "

paddle/fluid/operators/save_combine_op.cc

@@ -127,8 +127,7 @@ class SaveCombineOp : public framework::OperatorBase {
 
 class SaveCombineOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SaveCombineOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(
         "X",
         "(vector) Input LoDTensors that need to be saved together in a file.")

paddle/fluid/operators/save_op.cc

@@ -117,8 +117,7 @@ class SaveOp : public framework::OperatorBase {
 
 class SaveOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SaveOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(Tensor ) Input tensor to be saved");
     AddComment(R"DOC(
 Save operator

paddle/fluid/operators/scale_op.cc

@@ -37,8 +37,7 @@ class ScaleOp : public framework::OperatorWithKernel {
 
 class ScaleOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ScaleOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(Tensor) Input tensor of scale operator.");
     AddOutput("Out", "(Tensor) Output tensor of scale operator.");
     AddComment(R"DOC(

paddle/fluid/operators/scatter_op.cc

@@ -78,8 +78,7 @@ class ScatterGradOp : public framework::OperatorWithKernel {
 
 class ScatterOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ScatterOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The source input of scatter op");
     AddInput("Ids", "The index input of scatter op where X will be updated");
     AddInput("Updates", "The updated value of updates op");

paddle/fluid/operators/select_op.cc

@@ -380,8 +380,7 @@ class SelectOp : public framework::OperatorBase {
 
 class SelectOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SelectOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(kX,
              "A set of variables, which are required by operators inside the "
              "cases of Select Op")

paddle/fluid/operators/send_barrier_op.cc

@@ -57,8 +57,7 @@ class SendBarrierOp : public framework::OperatorBase {
 
 class SendBarrierOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SendBarrierOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() {
     AddOutput("RPCClient",
               "(RPCClient) The RPC client object which is"
               "initialized at most once.");

paddle/fluid/operators/send_op.cc

@@ -92,8 +92,7 @@ class SendOp : public framework::OperatorBase {
 
 class SendOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SendOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() {
     AddInput("X", "(Tensor) Input tensor to be sent").AsDuplicable();
     AddOutput("Out", "(Tensor) Output tensor to be received from server")
         .AsDuplicable();

paddle/fluid/operators/send_vars_op.cc

@@ -66,8 +66,7 @@ class SendVarsOp : public framework::OperatorBase {
 
 class SendVarsOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SendVarsOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() {
     AddInput("X", "(Tensor, SelectedRows) Input variables to be sent")
         .AsDuplicable();
     AddOutput("RPCClient",

paddle/fluid/operators/sequence_concat_op.cc

@@ -43,8 +43,7 @@ class SequenceConcatOp : public framework::OperatorWithKernel {
 
 class SequenceConcatOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SequenceConcatOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(LodTensorArray) Input is a vector of LoDTensor, "
              "each of which is a variable-length sequence or nested sequence.")

paddle/fluid/operators/sequence_conv_op.cc

@@ -102,8 +102,7 @@ class SequenceConvGradOp : public framework::OperatorWithKernel {
 
 class SequenceConvOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SequenceConvOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(
         "X",
         "(LoDTensor) the input(X) is a LodTensor, which supports "

paddle/fluid/operators/sequence_erase_op.cc

@@ -37,8 +37,7 @@ class SequenceEraseOp : public framework::OperatorWithKernel {
 
 class SequenceEraseOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SequenceEraseOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(2-D LoDTensor with the 2nd dim. equal to 1) "
              "Input LoDTensor of SequenceEraseOp.");

paddle/fluid/operators/sequence_expand_op.cc

@@ -94,8 +94,7 @@ class SequenceExpandOp : public framework::OperatorWithKernel {
 
 class SequenceExpandOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SequenceExpandOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(LoDTensor, default LoDTensor<float>) A 2-D LoDTensor whose lod "
              "level is at most 1.");

paddle/fluid/operators/sequence_pool_op.cc

@@ -38,8 +38,7 @@ class SequencePoolOp : public framework::OperatorWithKernel {
 
 class SequencePoolOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SequencePoolOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(LoDTensor) The variable-length input of SequencePoolOp");
     AddOutput("Out",
               "(Tensor) The output of SequencePoolOp does not contain LoD "

paddle/fluid/operators/sequence_reshape_op.cc

@@ -42,8 +42,7 @@ class SequenceReshapeOp : public framework::OperatorWithKernel {
 
 class SequenceReshapeOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SequenceReshapeOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(LoDTensor, default LoDTensor<float>) A 2-D LoDTensor with shape "
              "being [N, M].");

paddle/fluid/operators/sequence_slice_op.cc

@@ -79,8 +79,7 @@ class SequenceSliceGradOp : public framework::OperatorWithKernel {
 
 class SequenceSliceOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SequenceSliceOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(LoDTensor), "
              "the input of SequenceSliceOp.");

paddle/fluid/operators/sequence_softmax_op.cc

@@ -57,8 +57,7 @@ class SequenceSoftmaxOp : public framework::OperatorWithKernel {
 
 class SequenceSoftmaxOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SequenceSoftmaxOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(LoDTensor) 1-D or 2-D input LoDTensor with the 2-nd dimension "
              "of length 1.");

paddle/fluid/operators/sgd_op.cc

@@ -68,8 +68,7 @@ class SGDOpInferVarType : public framework::VarTypeInference {
 
 class SGDOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SGDOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Param", "(Tensor or SelectedRows) Input parameter");
     AddInput("LearningRate", "(Tensor) Learning rate of SGD");
     AddInput("Grad", "(Tensor or SelectedRows) Input gradient");

paddle/fluid/operators/shrink_rnn_memory_op.cc

@@ -69,8 +69,7 @@ class ShrinkRNNMemoryOp : public ArrayOp {
 
 class ShrinkRNNMemoryOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ShrinkRNNMemoryOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(LoDTensor) The RNN step memory to be shrinked.");
     AddInput("RankTable", "(LoDRankTable) The lod_rank_table of dynamic RNN.");
     AddInput("I",

paddle/fluid/operators/sigmoid_cross_entropy_with_logits_op.cc

@@ -86,9 +86,7 @@ class SigmoidCrossEntropyWithLogitsGradOp
 class SigmoidCrossEntropyWithLogitsOpMaker
     : public framework::OpProtoAndCheckerMaker {
  public:
-  SigmoidCrossEntropyWithLogitsOpMaker(OpProto* proto,
-                                       OpAttrChecker* op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(Tensor, default Tensor<float>), a 2-D tensor with shape N x D, "
              "where N is the batch size and D is the number of classes. "

paddle/fluid/operators/sign_op.cc

@@ -34,8 +34,7 @@ class SignOp : public framework::OperatorWithKernel {
 template <typename AttrType>
 class SignOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SignOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(Tensor) Input tensor of sign operator.");
     AddOutput("Out", "(Tensor) Output tensor of sign operator.");
     AddComment(R"DOC(

paddle/fluid/operators/smooth_l1_loss_op.cc

@@ -46,8 +46,7 @@ class SmoothL1LossOp : public framework::OperatorWithKernel {
 
 class SmoothL1LossOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SmoothL1LossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(Tensor, default Tensor<float>) A tensor with rank at least 2. "
              "The input value of smooth l1 loss op with shape "

paddle/fluid/operators/softmax_op.cc

@@ -77,8 +77,7 @@ class SoftmaxOp : public framework::OperatorWithKernel {
 
 class SoftmaxOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SoftmaxOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "The input tensor of softmax. "
              "2-D with shape [batch_size, input_feature_dimensions].");

paddle/fluid/operators/softmax_with_cross_entropy_op.cc

@@ -20,8 +20,7 @@ namespace operators {
 class SoftmaxWithCrossEntropyOpMaker
     : public framework::OpProtoAndCheckerMaker {
  public:
-  SoftmaxWithCrossEntropyOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Logits",
              "(Tensor, default: Tensor<float>), The unscaled log probabilities "
              "which is a 2-D tensor with shape [N x K]. N is the batch_size, "

paddle/fluid/operators/split_byref_op.cc

@@ -64,8 +64,7 @@ class SplitByrefOp : public framework::OperatorWithKernel {
 
 class SplitByrefOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SplitByrefOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(Tensor) Input tensor of the split operator.");
     AddOutput("Out", "(Tensor) Output tensors of the split operator.")
         .AsDuplicable();

paddle/fluid/operators/split_ids_op.cc

@@ -19,8 +19,7 @@ namespace operators {
 
 class SplitIdsOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SplitIdsOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Ids", "(LoDTensor) the input ids with shape{batch_num, 1}");
     AddOutput("Out", "(LoDTensor) The outputs of the input Ids.")
         .AsDuplicable();

paddle/fluid/operators/split_lod_tensor_op.cc

@@ -125,8 +125,7 @@ class SplitLoDTensorOp : public framework::OperatorBase {
 
 class SplitLoDTensorOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SplitLoDTensorOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The input LoDTensor");
     AddInput("Mask", "A bool column vector which mask the input");
     AddOutput("OutTrue", "True branch of input LoDTensor");

paddle/fluid/operators/split_op.cc

@@ -70,8 +70,7 @@ class SplitOp : public framework::OperatorWithKernel {
 
 class SplitOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SplitOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(Tensor) Input tensor of the split operator.");
     AddOutput("Out", "(Tensor) Output tensors of the split operator.")
         .AsDuplicable();

paddle/fluid/operators/split_selected_rows_op.cc

@@ -19,8 +19,7 @@ namespace operators {
 
 class SplitSelectedRowsOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SplitSelectedRowsOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "The input SelectedRows.");
     AddOutput("Out", "The outputs of the input SelectedRows.").AsDuplicable();
     AddAttr<std::vector<int>>("height_sections",

paddle/fluid/operators/spp_op.cc

@@ -20,8 +20,7 @@ namespace operators {
 
 class SppOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SppOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(
         "X",
         "(Tensor) The input tensor of spp operator. "

paddle/fluid/operators/squared_l2_distance_op.cc

@@ -56,8 +56,7 @@ class SquaredL2DistanceOp : public framework::OperatorWithKernel {
 
 class SquaredL2DistanceOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SquaredL2DistanceOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(Tensor) Input of SquaredL2DistanceOp.");
     AddInput("Y", "(Tensor) Target of SquaredL2DistanceOp.");
     AddOutput("sub_result",

paddle/fluid/operators/squared_l2_norm_op.cc

@@ -48,8 +48,7 @@ class SquaredL2NormGradOp : public framework::OperatorWithKernel {
 
 class SquaredL2NormOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SquaredL2NormOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(Tensor) The input of squared_l2_norm op.");
     AddOutput("Out", "(Scalar) The output of squared_l2_norm op.");
     AddComment(R"DOC(

paddle/fluid/operators/sum_op.cc

@@ -112,8 +112,7 @@ class SumOp : public framework::OperatorWithKernel {
 
 class SumOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SumOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(vector<Tensor>) The input tensors of sum operator.")
         .AsDuplicable();
     AddOutput("Out", "(Tensor) The output tensor of sum operator.");

paddle/fluid/operators/target_assign_op.cc

@@ -65,8 +65,7 @@ class TargetAssignOp : public framework::OperatorWithKernel {
 
 class TargetAssignOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  TargetAssignOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X",
              "(LoDTensor), This input is a 3D LoDTensor with shape [M, P, K]. "
              "Some elements in X will be assigned to Out based on the "

paddle/fluid/operators/tensor_array_read_write_op.cc

@@ -57,8 +57,7 @@ class WriteToArrayOp : public ArrayOp {
 
 class WriteToArrayOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  WriteToArrayOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(LoDTensor) the tensor will be written to tensor array");
     AddInput(
         "I",
@@ -148,8 +147,7 @@ class ReadFromArrayOp : public ArrayOp {
 
 class ReadFromArrayProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ReadFromArrayProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(TensorArray) the array will be read from.");
     AddInput("I",
              "(Tensor) the subscript index in tensor array. The number of "

paddle/fluid/operators/top_k_op.cc

@@ -48,8 +48,7 @@ class TopkOp : public framework::OperatorWithKernel {
 
 class TopkOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  TopkOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("X", "(Tensor) The input of Topk op");
     AddOutput("Out", "(Tensor) The output tensor of Topk op");
     AddOutput("Indices", "(Tensor) The indices of Topk elements of input");

paddle/fluid/operators/transpose_op.cc

@@ -56,8 +56,7 @@ class TransposeOp : public framework::OperatorWithKernel {
 
 class TransposeOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  TransposeOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(
         "X",
         "(Tensor) The input tensor, tensors with rank up to 6 are supported.");

paddle/fluid/operators/uniform_random_batch_size_like_op.cc

@@ -32,9 +32,8 @@ class UniformRandomBatchSizeLikeOp : public BatchSizeLikeOp {
 };
 
 class UniformRandomBatchSizeLikeOpMaker : public BatchSizeLikeOpMaker {
- public:
-  UniformRandomBatchSizeLikeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : BatchSizeLikeOpMaker(proto, op_checker) {
+ protected:
+  void Apply() override {
     AddComment(R"DOC(
 Uniform random operator
 

paddle/fluid/operators/uniform_random_op.cc

@@ -85,8 +85,7 @@ class UniformRandomOp : public framework::OperatorWithKernel {
 
 class UniformRandomOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  UniformRandomOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddOutput("Out", "(Tensor) The output tensor of uniform random op");
     AddComment(R"DOC(
 Uniform random operator.

paddle/fluid/operators/unpool_op.cc

@@ -20,8 +20,7 @@ namespace operators {
 
 class Unpool2dOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  Unpool2dOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(
         "X",
         "(Tensor) The input tensor of unpool operator. "

paddle/fluid/operators/warpctc_op.cc

@@ -53,8 +53,7 @@ class WarpCTCOp : public framework::OperatorWithKernel {
 
 class WarpCTCOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  WarpCTCOpMaker(OpProto* proto, OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput("Logits",
              "(LodTensor, default: LoDTensor<float>), the unscaled "
              "probabilities of variable-length sequences, which is a 2-D "

paddle/fluid/operators/while_op.cc

@@ -68,8 +68,7 @@ class WhileOp : public framework::OperatorBase {
 
 class WhileOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  WhileOpMaker(OpProto *proto, OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  void Make() override {
     AddInput(kX,
              "A set of variables, which are required by operators inside the "
              "block of While Op.")

paddle/scripts/paddle_build.sh

@@ -473,6 +473,7 @@ EOF
 }
 
 function main() {
+    set -e
     local CMD=$1
     init
     case $CMD in

paddle/scripts/paddle_docker_build.sh

@@ -59,7 +59,7 @@ EOL
     if [ ! -d "${HOME}/.ccache" ]; then
         mkdir ${HOME}/.ccache
     fi
-    set -x
+    set -ex
     ${DOCKER_CMD} run -it \
         --name $CONTAINER_ID \
         ${DOCKER_ENV} \

python/paddle/fluid/framework.py

@@ -160,6 +160,7 @@ class Variable(object):
                  persistable=None,
                  error_clip=None,
                  stop_gradient=False,
+                 is_data=False,
                  **kwargs):
         self.block = block
         self.error_clip = error_clip
@@ -238,6 +239,7 @@ class Variable(object):
         self.block.vars[name] = self
         self.op = None
         self.stop_gradient = stop_gradient
+        self.is_data = is_data
 
     def __str__(self):
         return self.to_string(True)
@@ -475,7 +477,7 @@ class Operator(object):
                 if isinstance(attrs[attr_name], Block):
                     self.desc.set_block_attr(attr_name, attrs[attr_name].desc)
                 elif isinstance(attrs[attr_name], core.BlockDesc) or \
-                   isinstance(attrs[attr_name], core.ProgramDesc):
+                        isinstance(attrs[attr_name], core.ProgramDesc):
                     self.desc.set_serialized_attr(
                         attr_name, attrs[attr_name].serialize_to_string())
                 else:
@@ -978,7 +980,8 @@ class Block(object):
                 shape=var.shape,
                 dtype=var.dtype,
                 type=var.type,
-                persistable=True)
+                persistable=True,
+                is_data=var.is_data)
         else:
             ret_var = self.create_var(
                 name=var.name,
@@ -986,7 +989,8 @@ class Block(object):
                 dtype=var.dtype,
                 type=var.type,
                 lod_level=var.lod_level,
-                persistable=True)
+                persistable=True,
+                is_data=var.is_data)
         return ret_var
 
 
@@ -1051,6 +1055,7 @@ class Program(object):
             p.sync_with_cpp()
 
         p.copy_param_info_from(self)
+        p.copy_data_info_from(self)
         return p
 
     def prune(self, targets):
@@ -1172,6 +1177,26 @@ class Program(object):
                              "program, with represent the same topology")
         self.global_block().copy_param_info_from(other.global_block())
 
+    def copy_data_info_from(self, other):
+        """
+        Copy the information of data variables from other program.
+        Args:
+            other(Program): Other program
+
+        Returns:
+            None
+        """
+        if not isinstance(other, Program):
+            raise TypeError("copy_param_info_from should be invoked with "
+                            "Program")
+
+        if len(self.blocks) != len(other.blocks):
+            raise ValueError("copy_param_info_from should be invoked with two "
+                             "program, with represent the same topology")
+        for var in other.global_block().vars.itervalues():
+            if var.is_data:
+                self.global_block().var(var.name).is_data = True
+
     def list_vars(self):
         for each_block in self.blocks:
             for each_var in each_block.vars.itervalues():

python/paddle/fluid/layers/io.py

@@ -78,8 +78,8 @@ def data(name,
         dtype=dtype,
         type=type,
         stop_gradient=stop_gradient,
-        lod_level=lod_level)
-    data_var.is_data = True
+        lod_level=lod_level,
+        is_data=True)
     return data_var
 
 

python/paddle/fluid/layers/layer_function_generator.py

@@ -113,7 +113,7 @@ def generate_layer_fn(op_type):
 
     if len(not_intermediate_outputs) != 1:
         raise ValueError("Only one non intermediate output operator can be",
-                         "automatically generated.")
+                         "automatically generated. {0}".format(op_type))
 
     if not_intermediate_outputs[0].duplicable:
         raise ValueError(

python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py

@@ -80,8 +80,11 @@ def inference_program(is_sparse):
 
 
 def train_program(is_sparse):
-    next_word = fluid.layers.data(name='nextw', shape=[1], dtype='int64')
+    # The declaration of 'next_word' must be after the invoking of inference_program,
+    # or the data input order of train program would be [next_word, firstw, secondw,
+    # thirdw, forthw], which is not correct.
     predict_word = inference_program(is_sparse)
+    next_word = fluid.layers.data(name='nextw', shape=[1], dtype='int64')
     cost = fluid.layers.cross_entropy(input=predict_word, label=next_word)
     avg_cost = fluid.layers.mean(cost)
     return avg_cost
@@ -90,14 +93,17 @@ def train_program(is_sparse):
 def train(use_cuda, is_sparse, save_path):
     train_reader = paddle.batch(
         paddle.dataset.imikolov.train(word_dict, N), BATCH_SIZE)
+    test_reader = paddle.batch(
+        paddle.dataset.imikolov.test(word_dict, N), BATCH_SIZE)
 
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
 
     def event_handler(event):
-        print type(event)
+        # print type(event)
         if isinstance(event, fluid.EndEpochEvent):
-            avg_cost = trainer.test(reader=paddle.dataset.imikolov.test(
-                word_dict, N))
+            outs = trainer.test(reader=test_reader)
+            avg_cost = outs[0]
+            print("loss= ", avg_cost)
 
             if avg_cost < 5.0:
                 trainer.save_params(save_path)

python/paddle/fluid/tests/unittests/test_network_with_dtype.py

@@ -24,7 +24,7 @@ BATCH_SIZE = 20
 
 
 class TestNetWithDtype(unittest.TestCase):
-    def setUp(self):
+    def set_network(self):
         self.dtype = "float64"
         self.init_dtype()
         self.x = fluid.layers.data(name='x', shape=[13], dtype=self.dtype)
@@ -55,12 +55,14 @@ class TestNetWithDtype(unittest.TestCase):
         pass
 
     def test_cpu(self):
+        self.set_network()
         place = fluid.CPUPlace()
         self.run_net_on_place(place)
 
     def test_gpu(self):
         if not core.is_compiled_with_cuda():
             return
+        self.set_network()
         place = fluid.CUDAPlace(0)
         self.run_net_on_place(place)
 

python/paddle/fluid/trainer.py

@@ -75,11 +75,15 @@ class Trainer(object):
         self.train_program = framework.Program()
 
         with framework.program_guard(self.train_program, self.startup_program):
-            loss = program_func()
+            program_func_outs = program_func()
+            self.test_outputs = program_func_outs if isinstance(
+                program_func_outs, list) else [program_func_outs]
+            self.test_program = self.train_program.clone()
             if not isinstance(optimizer, opt_module.Optimizer):
                 raise TypeError(
                     "The optimizer should be an instance of Optimizer")
-
+            # The fisrt element of program_func_outs is loss.
+            loss = self.test_outputs[0]
             optimize_ops, params_grads = optimizer.minimize(loss)
 
         self.place = Trainer._check_and_get_place(place)
@@ -168,8 +172,17 @@ class Trainer(object):
 
         self._train_by_executor(num_epochs, event_handler, reader, feed_order)
 
-    def test(self, reader):
-        pass
+    def test(self, reader, feed_order=None):
+        """
+        Test the model on given test data
+
+        Args:
+            reader: The reader that yields test data.
+            feed_order: Feeding order of reader. None will following the defining
+                order in program
+        """
+
+        return self._test_by_executor(reader, feed_order, self.test_outputs)
 
     def save_params(self, param_path):
         # reference: save_persistables in io.py
@@ -225,22 +238,10 @@ class Trainer(object):
 
         """
         with self._prog_and_scope_guard():
-            exe = executor.Executor(self.place)
-            if feed_order is None:
-                feed_var_list = [
-                    var
-                    for var in self.train_program.global_block(
-                    ).vars.itervalues()
-                    if hasattr(var, 'is_data') and var.is_data
-                ]
-            else:
-                feed_var_list = [
-                    self.train_program.global_block().var(var_name)
-                    for var_name in feed_order
-                ]
-
+            feed_var_list = build_feed_var_list(self.train_program, feed_order)
             feeder = data_feeder.DataFeeder(
                 feed_list=feed_var_list, place=self.place)
+            exe = executor.Executor(self.place)
             for epoch_id in range(num_epochs):
                 event_handler(BeginEpochEvent(epoch_id))
                 for step_id, data in enumerate(reader()):
@@ -248,3 +249,48 @@ class Trainer(object):
                     exe.run(feed=feeder.feed(data), fetch_list=[])
                     event_handler(EndStepEvent(epoch_id, step_id))
                 event_handler(EndEpochEvent(epoch_id))
+
+    def _test_by_executor(self, reader, feed_order, fetch_list):
+        with executor.scope_guard(self.scope):
+            feed_var_list = build_feed_var_list(self.test_program, feed_order)
+            feeder = data_feeder.DataFeeder(
+                feed_list=feed_var_list, place=self.place)
+            exe = executor.Executor(self.place)
+            accumulated = len(fetch_list) * [0]
+            count = 0
+            for data in reader():
+                outs = exe.run(program=self.test_program,
+                               feed=feeder.feed(data),
+                               fetch_list=fetch_list)
+                accumulated = [x[0] + x[1][0] for x in zip(accumulated, outs)]
+                count += 1
+
+            return [x / count for x in accumulated]
+
+
+def build_feed_var_list(program, feed_order):
+    if not isinstance(program, framework.Program):
+        raise TypeError("The 'program' should be an object of Program")
+
+    if feed_order is None:
+        feed_var_list = [
+            var for var in program.global_block().vars.itervalues()
+            if var.is_data
+        ]
+    elif isinstance(feed_order, list):
+        feed_var_list = [
+            program.global_block().var(var_name) for var_name in feed_order
+        ]
+    else:
+        if not isinstance(feed_order, dict):
+            raise TypeError(
+                "The 'feed_order' should be either None, list or dict.")
+        if not sorted(feed_order.values()) == range(len(feed_order)):
+            raise ValueError(
+                "The values of 'feed_order' should be a permutation of [0, len(feed_order))"
+            )
+        sorted_pair_list = sorted(feed_order.items(), key=lambda item: item[1])
+        feed_var_list = [
+            program.global_block().var(pair[0]) for pair in sorted_pair_list
+        ]
+    return feed_var_list