Add Clone Method For OperatorBase

* Clone method will create a new object instance, which is as same as
  itself.
* This is the first step to remove shared_ptr for OperatorBase

paddle/framework/op_registry.h

@@ -271,7 +271,13 @@ class OpKernelRegistrar : public Registrar {
 #define REGISTER_OP(op_type, op_class, op_maker_class)                        \
   STATIC_ASSERT_GLOBAL_NAMESPACE(                                             \
       __reg_op__##op_type, "REGISTER_OP must be called in global namespace"); \
-  static ::paddle::framework::OpRegistrar<op_class, op_maker_class>           \
+  class _OpClass_##op_type##_ : public op_class {                             \
+   public:                                                                    \
+    DEFINE_OP_CLONE_METHOD(_OpClass_##op_type##_);                            \
+    DEFINE_OP_CTOR(_OpClass_##op_type##_, op_class);                          \
+  };                                                                          \
+  static ::paddle::framework::OpRegistrar<_OpClass_##op_type##_,              \
+                                          op_maker_class>                     \
       __op_registrar_##op_type##__(#op_type);                                 \
   int TouchOpRegistrar_##op_type() {                                          \
     __op_registrar_##op_type##__.Touch();                                     \
@@ -285,7 +291,12 @@ class OpKernelRegistrar : public Registrar {
   STATIC_ASSERT_GLOBAL_NAMESPACE(                                            \
       __reg_gradient_op__##op_type##_##grad_op_type,                         \
       "REGISTER_GRADIENT_OP must be called in global namespace");            \
-  static ::paddle::framework::GradOpRegistrar<grad_op_class>                 \
+  class _OpGradClass_##op_type##_ : public grad_op_class {                   \
+   public:                                                                   \
+    DEFINE_OP_CLONE_METHOD(_OpGradClass_##op_type##_);                       \
+    DEFINE_OP_CTOR(_OpGradClass_##op_type##_, grad_op_class);                \
+  };                                                                         \
+  static ::paddle::framework::GradOpRegistrar<_OpGradClass_##op_type##_>     \
       __op_gradient_registrar_##op_type##_##grad_op_type##__(#op_type,       \
                                                              #grad_op_type); \
   int TouchOpGradientRegistrar_##op_type() {                                 \

paddle/framework/operator.h

@@ -69,10 +69,6 @@ class OperatorBase {
   OperatorBase(const std::string& type, const VarNameMap& inputs,
                const VarNameMap& outputs, const AttributeMap& attrs);
 
-  OperatorBase(const OperatorBase& o) = delete;
-  OperatorBase& operator=(const OperatorBase& o) = delete;
-  OperatorBase(OperatorBase&& o) = delete;
-
   virtual ~OperatorBase() {}
 
   template <typename T>
@@ -115,6 +111,8 @@ class OperatorBase {
   std::string Type() const { return type_; }
   const AttributeMap& Attrs() const { return attrs_; }
 
+  virtual OperatorBase* Clone() const = 0;
+
  public:
   std::string type_;
   // NOTE: in case of OpGrad, inputs_ contains:
@@ -129,6 +127,14 @@ class OperatorBase {
   AttributeMap attrs_;
 };
 
+#define DEFINE_OP_CLONE_METHOD(CLS) \
+  OperatorBase* Clone() const final { return new CLS(*this); }
+
+#define DEFINE_OP_CTOR(CLS, PARENT_CLS)                                        \
+  CLS(const std::string& type, const VarNameMap& inputs,                       \
+      const VarNameMap& outputs, const paddle::framework::AttributeMap& attrs) \
+      : PARENT_CLS(type, inputs, outputs, attrs) {}
+
 class InferShapeContext {
  public:
   InferShapeContext(const OperatorBase& op, const Scope& scope)

paddle/framework/operator_test.cc

@@ -242,3 +242,22 @@ TEST(OpKernel, multi_inputs) {
   auto op = paddle::framework::OpRegistry::CreateOp(op_desc);
   op->Run(scope, cpu_device_context);
 }
+
+class OperatorClone : public paddle::framework::OperatorBase {
+ public:
+  DEFINE_OP_CLONE_METHOD(OperatorClone);
+  OperatorClone(const std::string& type, const VarNameMap& inputs,
+                const VarNameMap& outputs,
+                const paddle::framework::AttributeMap& attrs)
+      : OperatorBase(type, inputs, outputs, attrs) {}
+  void InferShape(const paddle::framework::Scope& scope) const override {}
+  void Run(const paddle::framework::Scope& scope,
+           const paddle::platform::DeviceContext& dev_ctx) const override {}
+};
+
+TEST(Operator, Clone) {
+  OperatorClone a("ABC", {}, {}, {});
+  auto* b = a.Clone();
+  ASSERT_EQ(a.Type(), b->Type());
+  delete b;
+}
\ No newline at end of file

paddle/operators/net_op.cc

@@ -87,5 +87,12 @@ NetOp::NetOp(const std::string& type,
              const framework::AttributeMap& attrs)
     : OperatorBase(type, inputs, outputs, attrs) {}
 
+framework::OperatorBase* NetOp::Clone() const {
+  PADDLE_ENFORCE(
+      add_op_done_,
+      "Must clone a sealed NetOp, invoke Net::CompleteAddOp before clone");
+  return new NetOp(*this);
+}
+
 }  // namespace operators
 }  // namespace paddle

paddle/operators/net_op.h

@@ -41,6 +41,18 @@ class NetOp : public framework::OperatorBase {
   NetOp(const std::string& type, const VarNameMap& inputs,
         const VarNameMap& outputs, const framework::AttributeMap& attrs);
 
+  NetOp(const NetOp& o)
+      : framework::OperatorBase(
+            static_cast<const framework::OperatorBase&>(o)) {
+    this->ops_.reserve(o.ops_.size());
+    std::transform(o.ops_.begin(), o.ops_.end(), std::back_inserter(this->ops_),
+                   [](const std::shared_ptr<OperatorBase>& op)
+                       -> std::shared_ptr<OperatorBase> {
+                         return std::shared_ptr<OperatorBase>(op->Clone());
+                       });
+    this->CompleteAddOp();
+  }
+
   /**
    * Infer all the operators' input and output variables' shapes, will be called
    * before every mini-batch
@@ -97,6 +109,7 @@ class NetOp : public framework::OperatorBase {
 
   bool IsNetOp() const override;
   std::vector<std::string> OutputVars(bool has_intermediate) const override;
+  framework::OperatorBase* Clone() const override;
 
   std::vector<std::shared_ptr<OperatorBase>> ops_;
 

paddle/operators/net_op_test.cc

@@ -13,6 +13,7 @@ static int run_cnt = 0;
 class TestOp : public framework::OperatorBase {
  public:
   using framework::OperatorBase::OperatorBase;
+  DEFINE_OP_CLONE_METHOD(TestOp);
   void InferShape(const Scope& scope) const override { ++infer_shape_cnt; }
   void Run(const Scope& scope,
            const platform::DeviceContext& dev_ctx) const override {
@@ -23,6 +24,7 @@ class TestOp : public framework::OperatorBase {
 class EmptyOp : public framework::OperatorBase {
  public:
   using framework::OperatorBase::OperatorBase;
+  DEFINE_OP_CLONE_METHOD(EmptyOp);
   void InferShape(const Scope& scope) const override {}
   void Run(const Scope& scope, const DeviceContext& dev_ctx) const override {}
 };
@@ -77,5 +79,20 @@ TEST(NetOp, insert_op) {
   ASSERT_EQ(3UL, net.ops_.size());
 }
 
+TEST(NetOp, Clone) {
+  NetOp net;
+  net.AddOp(std::shared_ptr<EmptyOp>(new EmptyOp{"empty", {}, {}, {}}));
+  net.AddOp(std::shared_ptr<EmptyOp>(new EmptyOp{"empty2", {}, {}, {}}));
+  net.CompleteAddOp(true);
+  auto* new_net_op = net.Clone();
+  ASSERT_NE(new_net_op, nullptr);
+  ASSERT_TRUE(new_net_op->IsNetOp());
+  auto* new_net = static_cast<NetOp*>(new_net_op);
+  ASSERT_EQ(2, new_net->ops_.size());
+  ASSERT_EQ(new_net->ops_[0]->Type(), "empty");
+  ASSERT_EQ(new_net->ops_[1]->Type(), "empty2");
+  delete new_net;
+}
+
 }  // namespace operators
 }  // namespace paddle

paddle/operators/recurrent_op.h

@@ -99,10 +99,17 @@ class RecurrentGradientAlgorithm {
   mutable size_t seq_len_;
 };
 
-class RecurrentOp final : public framework::OperatorBase {
+class RecurrentOp : public framework::OperatorBase {
  public:
   RecurrentOp(const std::string& type, const VarNameMap& inputs,
               const VarNameMap& outputs, const framework::AttributeMap& attrs);
+
+  RecurrentOp(const RecurrentOp& o)
+      : framework::OperatorBase(
+            static_cast<const framework::OperatorBase&>(o)) {
+    // TODO(yuyang18): Implement copy ctor well.
+    PADDLE_THROW("Not implemented");
+  }
   /**
    * InferShape must be called before Run.
    */
@@ -121,12 +128,19 @@ class RecurrentOp final : public framework::OperatorBase {
   RecurrentAlgorithm alg_;
 };
 
-class RecurrentGradientOp final : public framework::OperatorBase {
+class RecurrentGradientOp : public framework::OperatorBase {
  public:
   RecurrentGradientOp(const std::string& type, const VarNameMap& inputs,
                       const VarNameMap& outputs,
                       const framework::AttributeMap& attrs);
 
+  RecurrentGradientOp(const RecurrentGradientOp& o)
+      : framework::OperatorBase(
+            static_cast<const framework::OperatorBase&>(o)) {
+    // TODO(yuyang18): Implement Copy ctor.
+    PADDLE_THROW("Not Implemented");
+  }
+
   /**
    * InferShape must be called before Run.
    */