Merge pull request #3444 from reyoung/use_ctor_create_op

Using constructor to create an operator.

paddle/framework/backward_test.cc

@@ -30,7 +30,7 @@ using DeviceContext = platform::DeviceContext;
 
 class EmptyOp : public OperatorBase {
  public:
-  DEFINE_OPERATOR_CTOR(EmptyOp, OperatorBase);
+  using OperatorBase::OperatorBase;
   void InferShape(const Scope &scope) const override {}
   void Run(const Scope &scope, const DeviceContext &dev_ctx) const override {}
 };
@@ -79,8 +79,9 @@ class NoGradOpMaker : public OpProtoAndCheckerMaker {
 
 class FcOp : public operators::NetOp {
  public:
-  DEFINE_OPERATOR_CTOR(FcOp, operators::NetOp)
-  void Init() override {
+  FcOp(const std::string &type, const VarNameMap &inputs,
+       const VarNameMap &outputs, const AttributeMap &attrs)
+      : NetOp(type, inputs, outputs, attrs) {
     AddOp(OpRegistry::CreateOp("mul",
                                {{"X", {Input("X")}}, {"Y", {Input("W")}}},
                                {{"Out", {Output("mul_result")}}}, {}));

paddle/framework/grad_op_builder.cc

@@ -20,13 +20,12 @@ namespace paddle {
 namespace framework {
 enum class OpArgType { IN, OUT };
 
-static void TransOpArg(const OperatorBase* src_op, OperatorBase* dst_op,
-                       const OpArgType& src_type, const OpArgType& dst_type,
-                       bool is_grad) {
+static void TransOpArg(const OperatorBase* src_op,
+                       OperatorBase::VarNameMap* vars,
+                       const OpArgType& src_type, bool is_grad) {
   const auto& src_inout =
       src_type == OpArgType::IN ? src_op->inputs_ : src_op->outputs_;
-  auto& dst_inout =
-      dst_type == OpArgType::IN ? dst_op->inputs_ : dst_op->outputs_;
+  auto& dst_inout = *vars;
 
   const OpProto& proto = OpProtos().at(src_op->type_);
   const auto& src_arg_list =
@@ -44,15 +43,22 @@ static void TransOpArg(const OperatorBase* src_op, OperatorBase* dst_op,
 }
 
 OperatorBase* BuildGradOp(const OperatorBase* op) {
-  std::string grad_op_type = OpRegistry::grad_ops().at(op->type_);
-  OperatorBase* grad_op = OpRegistry::op_creators().at(grad_op_type)();
-  grad_op->type_ = grad_op_type;
-  grad_op->attrs_ = op->attrs_;
-  TransOpArg(op, grad_op, OpArgType::IN, OpArgType::IN, false);   // I
-  TransOpArg(op, grad_op, OpArgType::OUT, OpArgType::IN, false);  // O
-  TransOpArg(op, grad_op, OpArgType::OUT, OpArgType::IN, true);   // OG
-  TransOpArg(op, grad_op, OpArgType::IN, OpArgType::OUT, true);   // IG
-  return grad_op;
+  auto gop_type_it = OpRegistry::grad_ops().find(op->type_);
+  PADDLE_ENFORCE(gop_type_it != OpRegistry::grad_ops().end(),
+                 "Operator %s do not register gradient type", op->type_);
+  auto& grad_op_type = gop_type_it->second;
+  OperatorBase::VarNameMap inputs;
+  OperatorBase::VarNameMap outputs;
+  TransOpArg(op, &inputs, OpArgType::IN, false);   // I
+  TransOpArg(op, &inputs, OpArgType::OUT, false);  // O
+  TransOpArg(op, &inputs, OpArgType::OUT, true);   // OG
+  TransOpArg(op, &outputs, OpArgType::IN, true);   // IG
+  auto gop_it = OpRegistry::op_creators().find(grad_op_type);
+  PADDLE_ENFORCE(gop_it != OpRegistry::op_creators().end(),
+                 "Operator %s 's Gradient %s's creator cannot be found",
+                 op->type_, grad_op_type);
+
+  return gop_it->second(grad_op_type, inputs, outputs, op->attrs_);
 }
 
 }  // namespace framework

paddle/framework/grad_op_builder_test.cc

@@ -10,7 +10,7 @@ namespace framework {
 
 class NOP : public OperatorBase {
  public:
-  DEFINE_OPERATOR_CTOR(NOP, OperatorBase);
+  using OperatorBase::OperatorBase;
   void InferShape(const Scope &scope) const override {}
   void Run(const Scope &scope,
            const platform::DeviceContext &dev_ctx) const override {}

paddle/framework/op_registry.h

@@ -120,13 +120,19 @@ class OpProtoAndCheckerMaker {
 };
 
 class OpRegistry {
-  using OpCreator = std::function<OperatorBase*()>;
   using VarNameMap = OperatorBase::VarNameMap;
+  using OpCreator = std::function<OperatorBase*(
+      const std::string& /*type*/, const VarNameMap& /*inputs*/,
+      const VarNameMap& /*outputs*/, const AttributeMap& /*attrs*/)>;
 
  public:
   template <typename OpType, typename ProtoMakerType>
   static void RegisterOp(const std::string& op_type) {
-    op_creators()[op_type] = [] { return new OpType; };
+    op_creators()[op_type] = [](
+        const std::string& type, const VarNameMap& inputs,
+        const VarNameMap& outputs, const AttributeMap& attrs) {
+      return new OpType(type, inputs, outputs, attrs);
+    };
     OpAttrChecker& op_checker = op_checkers()[op_type];
     OpProto& op_proto = OpProtos()[op_type];
     auto maker = ProtoMakerType(&op_proto, &op_checker);
@@ -141,29 +147,25 @@ class OpRegistry {
   template <typename GradOpType>
   static void RegisterGradOp(const std::string& op_type,
                              const std::string& grad_op_type) {
-    op_creators()[grad_op_type] = [] { return new GradOpType; };
+    op_creators()[grad_op_type] = [](
+        const std::string& type, const VarNameMap& inputs,
+        const VarNameMap& outputs, const AttributeMap& attrs) {
+      return new GradOpType(type, inputs, outputs, attrs);
+    };
     grad_ops()[op_type] = grad_op_type;
   }
 
   static std::shared_ptr<OperatorBase> CreateOp(const std::string& type,
                                                 const VarNameMap& inputs,
                                                 const VarNameMap& outputs,
-                                                const AttributeMap& attrs) {
+                                                AttributeMap attrs) {
     auto op_create_it = op_creators().find(type);
     PADDLE_ENFORCE(op_create_it != op_creators().end(),
                    "Operator %s cannot be found.", type);
+    op_checkers().at(type).Check(attrs);
 
-    auto op = op_create_it->second();
-    op->type_ = type;
-    op->inputs_ = inputs;
-    op->outputs_ = outputs;
-
-    op->attrs_ = attrs;
-    op_checkers().at(type).Check(op->attrs_);
-
-    GenerateTempVariableName(op);
+    auto op = op_create_it->second(type, inputs, outputs, attrs);
 
-    op->Init();
     return std::shared_ptr<OperatorBase>(op);
   }
 
@@ -195,7 +197,6 @@ class OpRegistry {
     PADDLE_ENFORCE(!op.IsNetOp(),
                    "Use framework::Backward to get backward ops");
     std::shared_ptr<OperatorBase> grad_op(BuildGradOp(&op));
-    grad_op->Init();
     return grad_op;
   }
 
@@ -214,19 +215,6 @@ class OpRegistry {
     static std::unordered_map<std::string, OpAttrChecker> op_checkers_;
     return op_checkers_;
   }
-
-  static void GenerateTempVariableName(OperatorBase* op) {
-    static std::atomic<size_t> gUniqId(0UL);
-    for (auto& output : op->outputs_) {
-      for (auto& output_name : output.second) {
-        if (output_name == kTempVarName) {
-          output_name += op->type_;
-          output_name += "@";
-          output_name += std::to_string(gUniqId.fetch_add(1));
-        }
-      }
-    }
-  }
 };
 
 class Registrar {

paddle/framework/op_registry_test.cc

@@ -7,7 +7,7 @@ namespace paddle {
 namespace framework {
 class CosineOp : public OperatorBase {
  public:
-  DEFINE_OPERATOR_CTOR(CosineOp, OperatorBase);
+  using OperatorBase::OperatorBase;
   void Run(const Scope& scope,
            const platform::DeviceContext& dev_ctx) const override {}
   void InferShape(const Scope& scope) const override {}
@@ -28,7 +28,7 @@ class CosineOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
 
 class MyTestOp : public OperatorBase {
  public:
-  DEFINE_OPERATOR_CTOR(MyTestOp, OperatorBase);
+  using OperatorBase::OperatorBase;
   void InferShape(const Scope& scope) const override {}
   void Run(const Scope& scope,
            const platform::DeviceContext& dev_ctx) const override {}

paddle/framework/operator.cc

@@ -122,6 +122,23 @@ void OperatorBase::Rename(const std::string& old_name,
   }
 }
 
+OperatorBase::OperatorBase(const std::string& type,
+                           const OperatorBase::VarNameMap& inputs,
+                           const OperatorBase::VarNameMap& outputs,
+                           const AttributeMap& attrs)
+    : type_(type), inputs_(inputs), outputs_(outputs), attrs_(attrs) {
+  static std::atomic<size_t> gUniqId(0UL);
+  for (auto& output : outputs_) {
+    for (auto& output_name : output.second) {
+      if (output_name == kTempVarName) {
+        output_name += type_;
+        output_name += "@";
+        output_name += std::to_string(gUniqId.fetch_add(1));
+      }
+    }
+  }
+}
+
 std::vector<std::string> OperatorBase::OutputVars(bool has_intermediate) const {
   std::vector<std::string> ret_val;
   if (has_intermediate) {

paddle/framework/operator.h

@@ -66,10 +66,8 @@ class OperatorBase {
  public:
   using VarNameMap = std::map<std::string, std::vector<std::string>>;
 
-  OperatorBase() = default;
   OperatorBase(const std::string& type, const VarNameMap& inputs,
-               const VarNameMap& outputs, const AttributeMap& attrs)
-      : type_(type), inputs_(inputs), outputs_(outputs), attrs_(attrs) {}
+               const VarNameMap& outputs, const AttributeMap& attrs);
 
   OperatorBase(const OperatorBase& o) = delete;
   OperatorBase& operator=(const OperatorBase& o) = delete;
@@ -86,10 +84,6 @@ class OperatorBase {
 
   virtual std::string DebugString() const;
 
-  /// Init will be called after CreateOperator, you can put some initialization
-  /// logic here.
-  virtual void Init() {}
-
   /// InferShape infer the size of Variables used by this Operator with
   /// information inside scope
   virtual void InferShape(const Scope& scope) const = 0;
@@ -135,15 +129,6 @@ class OperatorBase {
   AttributeMap attrs_;
 };
 
-#define DEFINE_OPERATOR_CTOR(Class, ParentClass)                               \
- public:                                                                       \
-  Class() : ParentClass() { /* TODO(yi): This constructor is to be removed. */ \
-  }                                                                            \
-  Class(const std::string& type, const VarNameMap& inputs,                     \
-        const VarNameMap& outputs,                                             \
-        const paddle::framework::AttributeMap& attrs)                          \
-      : ParentClass(type, inputs, outputs, attrs) {}
-
 class InferShapeContext {
  public:
   InferShapeContext(const OperatorBase& op, const Scope& scope)
@@ -287,8 +272,6 @@ class OpKernel {
 
 class OperatorWithKernel : public OperatorBase {
  public:
-  DEFINE_OPERATOR_CTOR(OperatorWithKernel, OperatorBase)
-
   struct OpKernelKey {
     platform::Place place_;
 
@@ -312,6 +295,10 @@ class OperatorWithKernel : public OperatorBase {
   using OpKernelMap =
       std::unordered_map<OpKernelKey, std::unique_ptr<OpKernel>, OpKernelHash>;
 
+  OperatorWithKernel(const std::string& type, const VarNameMap& inputs,
+                     const VarNameMap& outputs, const AttributeMap& attrs)
+      : OperatorBase(type, inputs, outputs, attrs) {}
+
   void InferShape(const Scope& scope) const override {
     InferShape(InferShapeContext(*this, scope));
   }

paddle/framework/operator_test.cc

@@ -22,10 +22,10 @@ namespace framework {
 static int op_run_num = 0;
 
 class OpWithoutKernelTest : public OperatorBase {
-  DEFINE_OPERATOR_CTOR(OpWithoutKernelTest, framework::OperatorBase)
-
  public:
-  void Init() override { x = 1; }
+  OpWithoutKernelTest(const std::string& type, const VarNameMap& inputs,
+                      const VarNameMap& outputs, const AttributeMap& attrs)
+      : OperatorBase(type, inputs, outputs, attrs), x(1) {}
   void InferShape(const Scope& scope) const override {}
   void Run(const Scope& scope,
            const platform::DeviceContext& dev_ctx) const override {
@@ -38,7 +38,7 @@ class OpWithoutKernelTest : public OperatorBase {
   }
 
  public:
-  float x = 0;
+  int x{0};
 };
 
 class OpeWithoutKernelTestProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
@@ -109,7 +109,9 @@ class OpKernelTestProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
 static int cpu_kernel_run_num = 0;
 
 class OpWithKernelTest : public OperatorWithKernel {
-  DEFINE_OPERATOR_CTOR(OpWithKernelTest, framework::OperatorWithKernel)
+ public:
+  using OperatorWithKernel::OperatorWithKernel;
+
  protected:
   void InferShape(const framework::InferShapeContext& ctx) const override {}
 };

paddle/operators/add_op.cc

@@ -18,7 +18,8 @@ namespace paddle {
 namespace operators {
 
 class AddOp : public framework::OperatorWithKernel {
-  DEFINE_OPERATOR_CTOR(AddOp, framework::OperatorWithKernel)
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
 
  protected:
   void InferShape(const framework::InferShapeContext &ctx) const override {
@@ -45,7 +46,9 @@ The equation is: Out = X + Y
 };
 
 class AddOpGrad : public framework::OperatorWithKernel {
-  DEFINE_OPERATOR_CTOR(AddOpGrad, framework::OperatorWithKernel)
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
  protected:
   void InferShape(const framework::InferShapeContext &ctx) const override {}
 };

paddle/operators/cross_entropy_op.cc

@@ -18,7 +18,9 @@ namespace paddle {
 namespace operators {
 
 class OnehotCrossEntropyOp : public framework::OperatorWithKernel {
-  DEFINE_OPERATOR_CTOR(OnehotCrossEntropyOp, framework::OperatorWithKernel)
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
  protected:
   void InferShape(const framework::InferShapeContext &ctx) const override {
     auto *X = ctx.Input<Tensor>("X");
@@ -32,8 +34,9 @@ class OnehotCrossEntropyOp : public framework::OperatorWithKernel {
 };
 
 class OnehotCrossEntropyGradientOp : public framework::OperatorWithKernel {
-  DEFINE_OPERATOR_CTOR(OnehotCrossEntropyGradientOp,
-                       framework::OperatorWithKernel)
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
  protected:
   void InferShape(const framework::InferShapeContext &ctx) const override {
     auto X_grad = ctx.Output<Tensor>(framework::GradVarName("X"));

paddle/operators/fill_zeros_like_op.cc

@@ -18,7 +18,8 @@ namespace paddle {
 namespace operators {
 
 class FillZerosLikeOp : public framework::OperatorWithKernel {
-  DEFINE_OPERATOR_CTOR(FillZerosLikeOp, framework::OperatorWithKernel);
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
 
  protected:
   void InferShape(const framework::InferShapeContext &ctx) const override {

paddle/operators/gaussian_random_op.cc

@@ -43,7 +43,8 @@ class GaussianRandomKernel : public framework::OpKernel {
 };
 
 class GaussianRandomOp : public framework::OperatorWithKernel {
-  DEFINE_OPERATOR_CTOR(GaussianRandomOp, framework::OperatorWithKernel);
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
 
  protected:
   void InferShape(const framework::InferShapeContext& context) const override {

paddle/operators/mean_op.cc

@@ -18,7 +18,9 @@ namespace paddle {
 namespace operators {
 
 class MeanOp : public framework::OperatorWithKernel {
-  DEFINE_OPERATOR_CTOR(MeanOp, framework::OperatorWithKernel)
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
  protected:
   void InferShape(const framework::InferShapeContext &ctx) const override {
     PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"),
@@ -38,7 +40,9 @@ class MeanOpMaker : public framework::OpProtoAndCheckerMaker {
 };
 
 class MeanGradOp : public framework::OperatorWithKernel {
-  DEFINE_OPERATOR_CTOR(MeanGradOp, framework::OperatorWithKernel)
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
  protected:
   void InferShape(const framework::InferShapeContext &ctx) const override {
     ctx.Output<Tensor>(framework::GradVarName("X"))

paddle/operators/mul_op.cc

@@ -19,7 +19,8 @@ namespace paddle {
 namespace operators {
 
 class MulOp : public framework::OperatorWithKernel {
-  DEFINE_OPERATOR_CTOR(MulOp, framework::OperatorWithKernel);
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
 
  protected:
   void InferShape(const framework::InferShapeContext &ctx) const override {
@@ -54,7 +55,9 @@ The equation is: Out = X * Y
 };
 
 class MulOpGrad : public framework::OperatorWithKernel {
-  DEFINE_OPERATOR_CTOR(MulOpGrad, framework::OperatorWithKernel)
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
  protected:
   void InferShape(const framework::InferShapeContext &ctx) const override {}
   std::string DebugString() const override {

paddle/operators/net_op.cc

@@ -81,5 +81,11 @@ std::vector<std::string> NetOp::OutputVars(bool has_intermediate) const {
   return ret_val;
 }
 
+NetOp::NetOp(const std::string& type,
+             const framework::OperatorBase::VarNameMap& inputs,
+             const framework::OperatorBase::VarNameMap& outputs,
+             const framework::AttributeMap& attrs)
+    : OperatorBase(type, inputs, outputs, attrs) {}
+
 }  // namespace operators
 }  // namespace paddle

paddle/operators/net_op.h

@@ -37,7 +37,9 @@ namespace operators {
 class NetOp : public framework::OperatorBase {
  public:
   static const char kAll[];
-  DEFINE_OPERATOR_CTOR(NetOp, framework::OperatorBase);
+  NetOp() : framework::OperatorBase("plain_net", {}, {}, {}) {}
+  NetOp(const std::string& type, const VarNameMap& inputs,
+        const VarNameMap& outputs, const framework::AttributeMap& attrs);
 
   /**
    * Infer all the operators' input and output variables' shapes, will be called

paddle/operators/net_op_test.cc

@@ -12,7 +12,7 @@ static int run_cnt = 0;
 
 class TestOp : public framework::OperatorBase {
  public:
-  DEFINE_OPERATOR_CTOR(TestOp, framework::OperatorBase);
+  using framework::OperatorBase::OperatorBase;
   void InferShape(const Scope& scope) const override { ++infer_shape_cnt; }
   void Run(const Scope& scope,
            const platform::DeviceContext& dev_ctx) const override {
@@ -22,7 +22,7 @@ class TestOp : public framework::OperatorBase {
 
 class EmptyOp : public framework::OperatorBase {
  public:
-  DEFINE_OPERATOR_CTOR(EmptyOp, framework::OperatorBase);
+  using framework::OperatorBase::OperatorBase;
   void InferShape(const Scope& scope) const override {}
   void Run(const Scope& scope, const DeviceContext& dev_ctx) const override {}
 };
@@ -44,14 +44,14 @@ TEST(OpKernel, all) {
   auto net = std::make_shared<NetOp>();
   ASSERT_NE(net, nullptr);
 
-  auto op1 = std::make_shared<TestOp>();
-  op1->inputs_ = {{"X", {"x"}}, {"W", {"w1"}}, {"b", {"b1"}}};
-  op1->outputs_ = {{"Out", {"y"}}};
+  auto op1 = std::shared_ptr<TestOp>(
+      new TestOp("test", {{"X", {"x"}}, {"W", {"w1"}}, {"b", {"b1"}}},
+                 {{"Out", {"y"}}}, {}));
   net->AddOp(op1);
 
-  auto op2 = std::make_shared<TestOp>();
-  op2->inputs_ = {{"X", {"y"}}, {"W", {"w2"}}, {"b", {"b2"}}};
-  op2->outputs_ = {{"Out", {"z"}}};
+  auto op2 = std::shared_ptr<TestOp>(
+      new TestOp("test", {{"X", {"y"}}, {"W", {"w2"}}, {"b", {"b2"}}},
+                 {{"Out", {"z"}}}, {}));
   net->AddOp(op2);
 
   net->CompleteAddOp();
@@ -67,9 +67,9 @@ TEST(OpKernel, all) {
 
 TEST(NetOp, insert_op) {
   NetOp net;
-  auto op1 = std::make_shared<EmptyOp>();
-  op1->inputs_ = {{"X", {"x"}}, {"W", {"w1"}}, {"b", {"b1"}}};
-  op1->outputs_ = {{"Out", {"y"}}};
+  auto op1 = std::shared_ptr<EmptyOp>(
+      new EmptyOp("empty", {{"X", {"x"}}, {"W", {"w1"}}, {"b", {"b1"}}},
+                  {{"Out", {"y"}}}, {}));
   net.AddOp(op1);
   net.InsertOp(0, op1);
   ASSERT_EQ(2UL, net.ops_.size());

paddle/operators/recurrent_op.cc

@@ -135,8 +135,11 @@ const rnn::ArgumentName RecurrentGradientOp::kArgName{
     "inlink@grad", "inlink_alias", "outlink_alias",
     "memories",    "pre_memories", "boot_memories@grad"};
 
-void RecurrentOp::Init() {
-  OperatorBase::Init();
+RecurrentOp::RecurrentOp(const std::string& type,
+                         const framework::OperatorBase::VarNameMap& inputs,
+                         const framework::OperatorBase::VarNameMap& outputs,
+                         const framework::AttributeMap& attrs)
+    : OperatorBase(type, inputs, outputs, attrs) {
   std::unique_ptr<rnn::Argument> arg(new rnn::Argument());
   rnn::InitArgument(kArgName, arg.get(), *this);
   alg_.Init(std::move(arg));
@@ -230,8 +233,11 @@ void RecurrentGradientAlgorithm::InferShape(const Scope& scope) const {
   LinkBootMemoryGradients(step_scopes[0], true /*infer_shape_mode*/);
 }
 
-void RecurrentGradientOp::Init() {
-  OperatorBase::Init();
+RecurrentGradientOp::RecurrentGradientOp(
+    const std::string& type, const framework::OperatorBase::VarNameMap& inputs,
+    const framework::OperatorBase::VarNameMap& outputs,
+    const framework::AttributeMap& attrs)
+    : OperatorBase(type, inputs, outputs, attrs) {
   std::unique_ptr<rnn::Argument> arg(new rnn::Argument());
   rnn::InitArgument(kArgName, arg.get(), *this);
   alg_.Init(std::move(arg));

paddle/operators/recurrent_op.h

@@ -101,13 +101,11 @@ class RecurrentGradientAlgorithm {
 
 class RecurrentOp final : public framework::OperatorBase {
  public:
-  DEFINE_OPERATOR_CTOR(RecurrentOp, framework::OperatorBase);
-
-  void Init() override;
-
+  RecurrentOp(const std::string& type, const VarNameMap& inputs,
+              const VarNameMap& outputs, const framework::AttributeMap& attrs);
   /**
-   * InferShape must be called before Run.
-   */
+     * InferShape must be called before Run.
+     */
   void InferShape(const framework::Scope& scope) const override {
     alg_.InferShape(scope);
   }
@@ -125,8 +123,9 @@ class RecurrentOp final : public framework::OperatorBase {
 
 class RecurrentGradientOp final : public framework::OperatorBase {
  public:
-  DEFINE_OPERATOR_CTOR(RecurrentGradientOp, framework::OperatorBase)
-  void Init() override;
+  RecurrentGradientOp(const std::string& type, const VarNameMap& inputs,
+                      const VarNameMap& outputs,
+                      const framework::AttributeMap& attrs);
 
   /**
    * InferShape must be called before Run.

paddle/operators/rowwise_add_op.cc

@@ -18,7 +18,9 @@ namespace paddle {
 namespace operators {
 
 class RowWiseAddOp : public framework::OperatorWithKernel {
-  DEFINE_OPERATOR_CTOR(RowWiseAddOp, framework::OperatorWithKernel)
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
  protected:
   void InferShape(const framework::InferShapeContext &ctx) const override {
     auto dim0 = ctx.Input<Tensor>("X")->dims();

paddle/operators/sgd_op.cc

@@ -18,7 +18,9 @@ namespace paddle {
 namespace operators {
 
 class SGDOp : public framework::OperatorWithKernel {
-  DEFINE_OPERATOR_CTOR(SGDOp, framework::OperatorWithKernel)
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
  protected:
   void InferShape(const framework::InferShapeContext &ctx) const override {
     PADDLE_ENFORCE(

paddle/operators/sigmoid_op.cc

@@ -18,7 +18,9 @@ namespace paddle {
 namespace operators {
 
 class SigmoidOp : public framework::OperatorWithKernel {
-  DEFINE_OPERATOR_CTOR(SigmoidOp, framework::OperatorWithKernel)
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
  protected:
   void InferShape(const framework::InferShapeContext &ctx) const override {
     ctx.Output<Tensor>("Y")->Resize(ctx.Input<Tensor>("X")->dims());
@@ -37,7 +39,9 @@ class SigmoidOpMaker : public framework::OpProtoAndCheckerMaker {
 };
 
 class SigmoidOpGrad : public framework::OperatorWithKernel {
-  DEFINE_OPERATOR_CTOR(SigmoidOpGrad, framework::OperatorWithKernel)
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
  protected:
   void InferShape(const framework::InferShapeContext &ctx) const override {
     ctx.Output<Tensor>(0)->Resize(ctx.Input<Tensor>(0)->dims());

paddle/operators/softmax_op.cc

@@ -18,7 +18,9 @@ namespace paddle {
 namespace operators {
 
 class SoftmaxOp : public framework::OperatorWithKernel {
-  DEFINE_OPERATOR_CTOR(SoftmaxOp, framework::OperatorWithKernel)
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
  protected:
   void InferShape(const framework::InferShapeContext &ctx) const override {
     PADDLE_ENFORCE(ctx.Input<Tensor>("X")->dims().size() == 2UL,
@@ -39,7 +41,9 @@ class SoftmaxOpMaker : public framework::OpProtoAndCheckerMaker {
 };
 
 class SoftmaxOpGrad : public framework::OperatorWithKernel {
-  DEFINE_OPERATOR_CTOR(SoftmaxOpGrad, framework::OperatorWithKernel)
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
  protected:
   void InferShape(const framework::InferShapeContext &ctx) const override {
     PADDLE_ENFORCE(ctx.InputVar("Y") != nullptr, "Input(Y) should not be null");

paddle/operators/uniform_random_op.cc

@@ -46,7 +46,9 @@ class CPUUniformRandomKernel : public framework::OpKernel {
 };
 
 class UniformRandomOp : public framework::OperatorWithKernel {
-  DEFINE_OPERATOR_CTOR(UniformRandomOp, framework::OperatorWithKernel)
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
  protected:
   void InferShape(const framework::InferShapeContext& ctx) const override {
     PADDLE_ENFORCE(GetAttr<float>("min") < GetAttr<float>("max"),