Move framework.proto to proto namespace (#6718)

* Move framework.proto to proto namespace

* Fix compile

* Fix compile

* Fix Compile

doc/howto/dev/new_op_cn.md

@@ -53,7 +53,7 @@ Kernel实现       | CPU、CUDA共享Kernel实现在`.h`文件中，否则，CPU
 ```cpp
 class MulOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MulOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  MulOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "(Tensor), 2D tensor of size (M x K)");
     AddInput("Y", "(Tensor), 2D tensor of size (K x N)");
@@ -82,7 +82,7 @@ The equation is: Out = X * Y
 template <typename AttrType>
 class ScaleOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ScaleOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  ScaleOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "The input tensor of scale operator.").NotInGradient();
     AddOutput("Out", "The output tensor of scale operator.").NotInGradient();

doc/howto/dev/new_op_en.md

@@ -50,7 +50,7 @@ First, define `ProtoMaker` to describe the Operator's input, output, and additio
 ```cpp
 class MulOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MulOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  MulOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "(Tensor), 2D tensor of size (M x K)");
     AddInput("Y", "(Tensor), 2D tensor of size (K x N)");
@@ -79,7 +79,7 @@ An additional example [`ScaleOp`](https://github.com/PaddlePaddle/Paddle/blob/de
 template <typename AttrType>
 class ScaleOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ScaleOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  ScaleOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "The input tensor of scale operator.").NotInGradient();
     AddOutput("Out", "The output tensor of scale operator.").NotInGradient();

paddle/framework/attribute.cc

@@ -19,42 +19,42 @@ limitations under the License. */
 namespace paddle {
 namespace framework {
 
-Attribute GetAttrValue(const OpDesc::Attr& attr_desc) {
+Attribute GetAttrValue(const proto::OpDesc::Attr& attr_desc) {
   switch (attr_desc.type()) {
-    case framework::AttrType::BOOLEAN: {
+    case proto::AttrType::BOOLEAN: {
       return attr_desc.b();
     }
-    case framework::AttrType::INT: {
+    case proto::AttrType::INT: {
       return attr_desc.i();
     }
-    case framework::AttrType::FLOAT: {
+    case proto::AttrType::FLOAT: {
       return attr_desc.f();
     }
-    case framework::AttrType::STRING: {
+    case proto::AttrType::STRING: {
       return attr_desc.s();
     }
-    case framework::AttrType::BOOLEANS: {
+    case proto::AttrType::BOOLEANS: {
       std::vector<bool> val(attr_desc.bools_size());
       for (int i = 0; i < attr_desc.bools_size(); ++i) {
         val[i] = attr_desc.bools(i);
       }
       return val;
     }
-    case framework::AttrType::INTS: {
+    case proto::AttrType::INTS: {
       std::vector<int> val(attr_desc.ints_size());
       for (int i = 0; i < attr_desc.ints_size(); ++i) {
         val[i] = attr_desc.ints(i);
       }
       return val;
     }
-    case framework::AttrType::FLOATS: {
+    case proto::AttrType::FLOATS: {
       std::vector<float> val(attr_desc.floats_size());
       for (int i = 0; i < attr_desc.floats_size(); ++i) {
         val[i] = attr_desc.floats(i);
       }
       return val;
     }
-    case framework::AttrType::STRINGS: {
+    case proto::AttrType::STRINGS: {
       std::vector<std::string> val(attr_desc.strings_size());
       for (int i = 0; i < attr_desc.strings_size(); ++i) {
         val[i] = attr_desc.strings(i);

paddle/framework/attribute.h

@@ -27,12 +27,12 @@ limitations under the License. */
 namespace paddle {
 namespace framework {
 template <typename T>
-inline AttrType AttrTypeID() {
+inline proto::AttrType AttrTypeID() {
   Attribute tmp = T();
-  return static_cast<AttrType>(tmp.which() - 1);
+  return static_cast<proto::AttrType>(tmp.which() - 1);
 }
 
-Attribute GetAttrValue(const OpDesc::Attr& attr_desc);
+Attribute GetAttrValue(const proto::OpDesc::Attr& attr_desc);
 
 class AttrReader {
  public:

paddle/framework/backward.cc

@@ -341,7 +341,7 @@ static void CreateGradVarInBlock(
       auto* param = block_desc->FindVarRecursive(pname);
       auto* grad = block_desc->FindVar(arg);
       if (param == nullptr) {
-        grad->SetDataType(DataType::FP32);
+        grad->SetDataType(proto::DataType::FP32);
       } else {
         grad->SetDataType(param->GetDataType());
       }

paddle/framework/backward_test.cc

@@ -166,7 +166,7 @@ class FillZeroOpMaker : public OpProtoAndCheckerMaker {
 
 class SumOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SumOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  SumOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "the input tensors of sum operator.").AsDuplicable();
     AddOutput("Out", "the output tensor of sum operator.");

paddle/framework/block_desc.cc

@@ -128,22 +128,22 @@ BlockDescBind *BlockDescBind::ParentBlock() const {
   return prog_->MutableBlock(static_cast<size_t>(this->desc_->parent_idx()));
 }
 
-BlockDesc *BlockDescBind::Proto() {
+proto::BlockDesc *BlockDescBind::Proto() {
   Flush();
   return desc_;
 }
 
-BlockDescBind::BlockDescBind(ProgramDescBind *prog, BlockDesc *desc)
+BlockDescBind::BlockDescBind(ProgramDescBind *prog, proto::BlockDesc *desc)
     : prog_(prog), desc_(desc), need_update_(false) {
-  for (const VarDesc &var_desc : desc_->vars()) {
+  for (const proto::VarDesc &var_desc : desc_->vars()) {
     vars_[var_desc.name()].reset(new VarDescBind(var_desc));
   }
-  for (const OpDesc &op_desc : desc_->ops()) {
+  for (const proto::OpDesc &op_desc : desc_->ops()) {
     ops_.emplace_back(new OpDescBind(op_desc, prog));
   }
 }
 
-BlockDescBind::BlockDescBind(const BlockDescBind &other, BlockDesc *desc,
+BlockDescBind::BlockDescBind(const BlockDescBind &other, proto::BlockDesc *desc,
                              ProgramDescBind *prog)
     : prog_(prog), desc_(desc) {
   need_update_ = true;

paddle/framework/block_desc.h

@@ -36,9 +36,9 @@ class ProgramDescBind;
 
 class BlockDescBind {
  public:
-  BlockDescBind(ProgramDescBind *prog, BlockDesc *desc);
+  BlockDescBind(ProgramDescBind *prog, proto::BlockDesc *desc);
 
-  BlockDescBind(const BlockDescBind &other, BlockDesc *desc,
+  BlockDescBind(const BlockDescBind &other, proto::BlockDesc *desc,
                 ProgramDescBind *prog);
 
   ~BlockDescBind() {
@@ -88,7 +88,7 @@ class BlockDescBind {
 
   void Flush();
 
-  BlockDesc *Proto();
+  proto::BlockDesc *Proto();
 
   ProgramDescBind *Program() { return this->prog_; }
 
@@ -97,8 +97,8 @@ class BlockDescBind {
   void ClearPBVars();
 
  private:
-  ProgramDescBind *prog_;  // not_own
-  BlockDesc *desc_;        // not_own
+  ProgramDescBind *prog_;   // not_own
+  proto::BlockDesc *desc_;  // not_own
   bool need_update_;
 
   std::deque<std::unique_ptr<OpDescBind>> ops_;

paddle/framework/data_type.h

@@ -20,7 +20,8 @@
 namespace paddle {
 namespace framework {
 
-inline DataType ToDataType(std::type_index type) {
+inline proto::DataType ToDataType(std::type_index type) {
+  using namespace paddle::framework::proto;
   if (typeid(float).hash_code() == type.hash_code()) {
     return DataType::FP32;
   } else if (typeid(double).hash_code() == type.hash_code()) {
@@ -36,7 +37,8 @@ inline DataType ToDataType(std::type_index type) {
   }
 }
 
-inline std::type_index ToTypeIndex(DataType type) {
+inline std::type_index ToTypeIndex(proto::DataType type) {
+  using namespace paddle::framework::proto;
   switch (type) {
     case DataType::FP32:
       return typeid(float);
@@ -54,7 +56,8 @@ inline std::type_index ToTypeIndex(DataType type) {
 }
 
 template <typename Visitor>
-inline void VisitDataType(DataType type, Visitor visitor) {
+inline void VisitDataType(proto::DataType type, Visitor visitor) {
+  using namespace paddle::framework::proto;
   switch (type) {
     case DataType::FP32:
       visitor.template operator()<float>();

paddle/framework/details/op_registry.h

@@ -90,7 +90,7 @@ struct OpInfoFiller<T, kOperator> {
 template <typename T>
 struct OpInfoFiller<T, kOpProtoAndCheckerMaker> {
   void operator()(const char* op_type, OpInfo* info) const {
-    info->proto_ = new OpProto;
+    info->proto_ = new proto::OpProto;
     info->checker_ = new OpAttrChecker();
     auto maker = T(info->proto_, info->checker_);
     maker.Validate();

paddle/framework/executor.cc

@@ -41,20 +41,20 @@ Executor::Executor(const std::vector<platform::Place>& places) {
   device_contexts_.swap(borrowed_contexts);
 }
 
-static void CreateTensor(Variable* var, VarDesc::VarType var_type) {
-  if (var_type == VarDesc::LOD_TENSOR) {
+static void CreateTensor(Variable* var, proto::VarDesc::VarType var_type) {
+  if (var_type == proto::VarDesc::LOD_TENSOR) {
     var->GetMutable<LoDTensor>();
-  } else if (var_type == VarDesc::SELECTED_ROWS) {
+  } else if (var_type == proto::VarDesc::SELECTED_ROWS) {
     var->GetMutable<SelectedRows>();
-  } else if (var_type == VarDesc::FEED_MINIBATCH) {
+  } else if (var_type == proto::VarDesc::FEED_MINIBATCH) {
     var->GetMutable<FeedFetchList>();
-  } else if (var_type == VarDesc::FETCH_LIST) {
+  } else if (var_type == proto::VarDesc::FETCH_LIST) {
     var->GetMutable<FeedFetchList>();
-  } else if (var_type == VarDesc::STEP_SCOPES) {
+  } else if (var_type == proto::VarDesc::STEP_SCOPES) {
     var->GetMutable<std::vector<framework::Scope>>();
-  } else if (var_type == VarDesc::LOD_RANK_TABLE) {
+  } else if (var_type == proto::VarDesc::LOD_RANK_TABLE) {
     var->GetMutable<LoDRankTable>();
-  } else if (var_type == VarDesc::LOD_TENSOR_ARRAY) {
+  } else if (var_type == proto::VarDesc::LOD_TENSOR_ARRAY) {
     var->GetMutable<LoDTensorArray>();
   } else {
     PADDLE_THROW(

paddle/framework/framework.proto

@@ -14,7 +14,7 @@ limitations under the License. */
 
 syntax = "proto2";
 option optimize_for = LITE_RUNTIME;
-package paddle.framework;
+package paddle.framework.proto;
 
 enum AttrType {
   INT = 0;

paddle/framework/lod_tensor.cc

@@ -197,7 +197,7 @@ void SerializeToStream(std::ostream &os, const LoDTensor &tensor,
   {  // the 2nd field, tensor description
      // int32_t  size
      // void*    protobuf message
-    framework::TensorDesc desc;
+    proto::TensorDesc desc;
     desc.set_data_type(framework::ToDataType(tensor.type()));
     auto dims = framework::vectorize(tensor.dims());
     auto *pb_dims = desc.mutable_dims();
@@ -262,7 +262,7 @@ void DeserializeFromStream(std::istream &is, LoDTensor *tensor) {
   uint32_t version;
   is.read(reinterpret_cast<char *>(&version), sizeof(version));
   PADDLE_ENFORCE_EQ(version, 0U, "Only version 0 is supported");
-  framework::TensorDesc desc;
+  proto::TensorDesc desc;
   {  // int32_t size
      // proto buffer
     int32_t size;
@@ -281,16 +281,16 @@ void DeserializeFromStream(std::istream &is, LoDTensor *tensor) {
     void *buf;
     platform::Place cpu = platform::CPUPlace();
     switch (desc.data_type()) {
-      case framework::FP32:
+      case proto::FP32:
         buf = tensor->mutable_data<float>(cpu);
         break;
-      case framework::FP64:
+      case proto::FP64:
         buf = tensor->mutable_data<double>(cpu);
         break;
-      case framework::INT32:
+      case proto::INT32:
         buf = tensor->mutable_data<int>(cpu);
         break;
-      case framework::INT64:
+      case proto::INT64:
         buf = tensor->mutable_data<int64_t>(cpu);
         break;
       default:

paddle/framework/op_desc.cc

@@ -58,11 +58,11 @@ class CompileTimeInferShapeContext : public InferShapeContext {
     PADDLE_ENFORCE_LT(j, Outputs(out).size());
     auto *in_var = block_.FindVarRecursive(Inputs(in)[i]);
     auto *out_var = block_.FindVarRecursive(Outputs(out)[j]);
-    if (in_var->GetType() != VarDesc::LOD_TENSOR) {
+    if (in_var->GetType() != proto::VarDesc::LOD_TENSOR) {
       VLOG(3) << "input " << in << " is not LodTensor";
       return;
     }
-    PADDLE_ENFORCE_EQ(in_var->GetType(), VarDesc::LOD_TENSOR,
+    PADDLE_ENFORCE_EQ(in_var->GetType(), proto::VarDesc::LOD_TENSOR,
                       "The %d-th output of Output(%s) must be LoDTensor.", j,
                       out);
     out_var->SetLoDLevel(in_var->GetLodLevel());
@@ -70,7 +70,7 @@ class CompileTimeInferShapeContext : public InferShapeContext {
   bool IsRuntime() const override;
 
  protected:
-  VarDesc::VarType GetVarType(const std::string &name) const override;
+  proto::VarDesc::VarType GetVarType(const std::string &name) const override;
 
   DDim GetDim(const std::string &name) const override;
 
@@ -90,12 +90,12 @@ OpDescBind::OpDescBind(const std::string &type, const VariableNameMap &inputs,
   need_update_ = true;
 }
 
-OpDescBind::OpDescBind(const OpDesc &desc, ProgramDescBind *prog)
+OpDescBind::OpDescBind(const proto::OpDesc &desc, ProgramDescBind *prog)
     : desc_(desc), need_update_(false) {
   // restore inputs_
   int input_size = desc_.inputs_size();
   for (int i = 0; i < input_size; ++i) {
-    const OpDesc::Var &var = desc_.inputs(i);
+    const proto::OpDesc::Var &var = desc_.inputs(i);
     std::vector<std::string> &args = inputs_[var.parameter()];
     int argu_size = var.arguments_size();
     args.reserve(argu_size);
@@ -106,7 +106,7 @@ OpDescBind::OpDescBind(const OpDesc &desc, ProgramDescBind *prog)
   // restore outputs_
   int output_size = desc_.outputs_size();
   for (int i = 0; i < output_size; ++i) {
-    const OpDesc::Var &var = desc_.outputs(i);
+    const proto::OpDesc::Var &var = desc_.outputs(i);
     std::vector<std::string> &args = outputs_[var.parameter()];
     int argu_size = var.arguments_size();
     args.reserve(argu_size);
@@ -115,9 +115,9 @@ OpDescBind::OpDescBind(const OpDesc &desc, ProgramDescBind *prog)
     }
   }
   // restore attrs_
-  for (const OpDesc::Attr &attr : desc_.attrs()) {
+  for (const proto::OpDesc::Attr &attr : desc_.attrs()) {
     std::string attr_name = attr.name();
-    if (attr.type() != AttrType::BLOCK) {
+    if (attr.type() != proto::AttrType::BLOCK) {
       attrs_[attr_name] = GetAttrValue(attr);
     } else {
       auto bid = attr.block_idx();
@@ -126,7 +126,7 @@ OpDescBind::OpDescBind(const OpDesc &desc, ProgramDescBind *prog)
   }
 }
 
-OpDesc *OpDescBind::Proto() {
+proto::OpDesc *OpDescBind::Proto() {
   Flush();
   return &desc_;
 }
@@ -175,10 +175,10 @@ void OpDescBind::SetOutput(const std::string &param_name,
   this->outputs_[param_name] = args;
 }
 
-AttrType OpDescBind::GetAttrType(const std::string &name) const {
+proto::AttrType OpDescBind::GetAttrType(const std::string &name) const {
   auto it = attrs_.find(name);
   PADDLE_ENFORCE(it != attrs_.end(), "Attribute %s is not found", name);
-  return static_cast<AttrType>(it->second.which() - 1);
+  return static_cast<proto::AttrType>(it->second.which() - 1);
 }
 
 std::vector<std::string> OpDescBind::AttrNames() const {
@@ -253,8 +253,8 @@ void OpDescBind::RenameInput(const std::string &old_name,
 }
 
 struct SetAttrDescVisitor : public boost::static_visitor<void> {
-  explicit SetAttrDescVisitor(OpDesc::Attr *attr) : attr_(attr) {}
-  mutable OpDesc::Attr *attr_;
+  explicit SetAttrDescVisitor(proto::OpDesc::Attr *attr) : attr_(attr) {}
+  mutable proto::OpDesc::Attr *attr_;
   void operator()(int v) const { attr_->set_i(v); }
   void operator()(float v) const { attr_->set_f(v); }
   void operator()(const std::string &v) const { attr_->set_s(v); }
@@ -272,7 +272,9 @@ struct SetAttrDescVisitor : public boost::static_visitor<void> {
   void operator()(const std::vector<bool> &v) const {
     VectorToRepeated(v, attr_->mutable_bools());
   }
-  void operator()(BlockDesc *desc) const { attr_->set_block_idx(desc->idx()); }
+  void operator()(proto::BlockDesc *desc) const {
+    attr_->set_block_idx(desc->idx());
+  }
   void operator()(boost::blank) const { PADDLE_THROW("Unexpected branch"); }
 };
 
@@ -297,7 +299,7 @@ void OpDescBind::Flush() {
       auto *attr_desc = desc_.add_attrs();
       attr_desc->set_name(attr.first);
       attr_desc->set_type(
-          static_cast<framework::AttrType>(attr.second.which() - 1));
+          static_cast<proto::AttrType>(attr.second.which() - 1));
       SetAttrDescVisitor visitor(attr_desc);
       boost::apply_visitor(visitor, attr.second);
     }
@@ -375,7 +377,7 @@ void OpDescBind::InferVarType(BlockDescBind *block) const {
     for (auto &out_pair : this->outputs_) {
       for (auto &out_var_name : out_pair.second) {
         block->FindRecursiveOrCreateVar(out_var_name)
-            ->SetType(VarDesc::LOD_TENSOR);
+            ->SetType(proto::VarDesc::LOD_TENSOR);
       }
     }
   }
@@ -484,7 +486,7 @@ void CompileTimeInferShapeContext::SetDim(const std::string &name,
 }
 bool CompileTimeInferShapeContext::IsRuntime() const { return false; }
 
-VarDesc::VarType CompileTimeInferShapeContext::GetVarType(
+proto::VarDesc::VarType CompileTimeInferShapeContext::GetVarType(
     const std::string &name) const {
   return block_.FindVarRecursive(name)->GetType();
 }

paddle/framework/op_desc.h

@@ -33,9 +33,9 @@ class OpDescBind {
   OpDescBind(const std::string &type, const VariableNameMap &inputs,
              const VariableNameMap &outputs, const AttributeMap &attrs);
 
-  OpDescBind(const OpDesc &desc, ProgramDescBind *prog);
+  OpDescBind(const proto::OpDesc &desc, ProgramDescBind *prog);
 
-  OpDesc *Proto();
+  proto::OpDesc *Proto();
 
   std::string Type() const { return desc_.type(); }
 
@@ -59,7 +59,7 @@ class OpDescBind {
     return attrs_.find(name) != attrs_.end();
   }
 
-  AttrType GetAttrType(const std::string &name) const;
+  proto::AttrType GetAttrType(const std::string &name) const;
 
   std::vector<std::string> AttrNames() const;
 
@@ -126,7 +126,7 @@ class OpDescBind {
     return ret_val;
   }
 
-  OpDesc desc_;
+  proto::OpDesc desc_;
   VariableNameMap inputs_;
   VariableNameMap outputs_;
   AttributeMap attrs_;

paddle/framework/op_info.h

@@ -34,7 +34,7 @@ class InferShapeBase {
 struct OpInfo {
   OpCreator creator_;
   GradOpMakerFN grad_op_maker_;
-  OpProto* proto_{nullptr};
+  proto::OpProto* proto_{nullptr};
   OpAttrChecker* checker_{nullptr};
   InferVarTypeFN infer_var_type_;
   InferShapeFN infer_shape_;
@@ -43,7 +43,7 @@ struct OpInfo {
     return proto_ != nullptr && checker_ != nullptr;
   }
 
-  const OpProto& Proto() const {
+  const proto::OpProto& Proto() const {
     PADDLE_ENFORCE_NOT_NULL(proto_, "Operator Proto has not been registered");
     PADDLE_ENFORCE(proto_->IsInitialized(),
                    "Operator Proto must be initialized in op info");

paddle/framework/op_proto_maker.h

@@ -22,6 +22,8 @@ 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) {}
 
@@ -80,7 +82,7 @@ class OpProtoAndCheckerMaker {
 
 class NOPMaker : public OpProtoAndCheckerMaker {
  public:
-  NOPMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
+  NOPMaker(OpProto* proto, framework::OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {}
 };
 

paddle/framework/op_proto_maker_test.cc

@@ -18,7 +18,7 @@ limitations under the License. */
 
 class TestAttrProtoMaker : public paddle::framework::OpProtoAndCheckerMaker {
  public:
-  TestAttrProtoMaker(paddle::framework::OpProto* proto,
+  TestAttrProtoMaker(paddle::framework::proto::OpProto* proto,
                      paddle::framework::OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddAttr<float>("scale", "scale of test op");
@@ -27,7 +27,7 @@ class TestAttrProtoMaker : public paddle::framework::OpProtoAndCheckerMaker {
 };
 
 TEST(ProtoMaker, DuplicatedAttr) {
-  paddle::framework::OpProto op_proto;
+  paddle::framework::proto::OpProto op_proto;
   paddle::framework::OpAttrChecker op_checker;
   auto proto_maker = TestAttrProtoMaker(&op_proto, &op_checker);
   ASSERT_THROW(proto_maker.Validate(), paddle::platform::EnforceNotMet);
@@ -35,7 +35,7 @@ TEST(ProtoMaker, DuplicatedAttr) {
 
 class TestInOutProtoMaker : public paddle::framework::OpProtoAndCheckerMaker {
  public:
-  TestInOutProtoMaker(paddle::framework::OpProto* proto,
+  TestInOutProtoMaker(paddle::framework::proto::OpProto* proto,
                       paddle::framework::OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("input", "input of test op");
@@ -44,7 +44,7 @@ class TestInOutProtoMaker : public paddle::framework::OpProtoAndCheckerMaker {
 };
 
 TEST(ProtoMaker, DuplicatedInOut) {
-  paddle::framework::OpProto op_proto;
+  paddle::framework::proto::OpProto op_proto;
   paddle::framework::OpAttrChecker op_checker;
   auto proto_maker = TestInOutProtoMaker(&op_proto, &op_checker);
   ASSERT_THROW(proto_maker.Validate(), paddle::platform::EnforceNotMet);

paddle/framework/op_registry.cc

@@ -31,7 +31,8 @@ std::unique_ptr<OperatorBase> OpRegistry::CreateOp(
 }
 
 static VariableNameMap ConvertOpDescVarsToVarNameMap(
-    const google::protobuf::RepeatedPtrField<OpDesc::Var>& op_desc_vars) {
+    const google::protobuf::RepeatedPtrField<proto::OpDesc::Var>&
+        op_desc_vars) {
   VariableNameMap ret_val;
   for (auto& var : op_desc_vars) {
     auto& var_names = ret_val[var.parameter()];
@@ -43,7 +44,8 @@ static VariableNameMap ConvertOpDescVarsToVarNameMap(
   return ret_val;
 }
 
-std::unique_ptr<OperatorBase> OpRegistry::CreateOp(const OpDesc& op_desc) {
+std::unique_ptr<OperatorBase> OpRegistry::CreateOp(
+    const proto::OpDesc& op_desc) {
   VLOG(1) << "CreateOp directly from OpDesc is deprecated. It should only be"
              "used in unit tests. Use CreateOp(const OpDescBind& op_desc) "
              "instead.";

paddle/framework/op_registry.h

@@ -77,7 +77,7 @@ class OpRegistry {
                                                 const VariableNameMap& outputs,
                                                 AttributeMap attrs);
 
-  static std::unique_ptr<OperatorBase> CreateOp(const OpDesc& op_desc);
+  static std::unique_ptr<OperatorBase> CreateOp(const proto::OpDesc& op_desc);
 
   static std::unique_ptr<OperatorBase> CreateOp(const OpDescBind& op_desc);
 };

paddle/framework/op_registry_test.cc

@@ -51,7 +51,7 @@ class MyTestOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
 
 static void BuildVar(const std::string& param_name,
                      std::initializer_list<const char*> arguments,
-                     paddle::framework::OpDesc::Var* var) {
+                     paddle::framework::proto::OpDesc::Var* var) {
   var->set_parameter(param_name);
   for (auto& arg_name : arguments) {
     var->add_arguments(arg_name);
@@ -63,7 +63,7 @@ REGISTER_OP_WITHOUT_GRADIENT(my_test_op, paddle::framework::MyTestOp,
                              paddle::framework::MyTestOpProtoAndCheckerMaker);
 
 TEST(OpRegistry, CreateOp) {
-  paddle::framework::OpDesc op_desc;
+  paddle::framework::proto::OpDesc op_desc;
   op_desc.set_type("cos_sim");
   BuildVar("input", {"aa"}, op_desc.add_inputs());
   BuildVar("output", {"bb"}, op_desc.add_outputs());
@@ -71,7 +71,7 @@ TEST(OpRegistry, CreateOp) {
   float scale = 3.3;
   auto attr = op_desc.mutable_attrs()->Add();
   attr->set_name("scale");
-  attr->set_type(paddle::framework::AttrType::FLOAT);
+  attr->set_type(paddle::framework::proto::AttrType::FLOAT);
   attr->set_f(scale);
 
   auto op = paddle::framework::OpRegistry::CreateOp(op_desc);
@@ -83,14 +83,14 @@ TEST(OpRegistry, CreateOp) {
 }
 
 TEST(OpRegistry, IllegalAttr) {
-  paddle::framework::OpDesc op_desc;
+  paddle::framework::proto::OpDesc op_desc;
   op_desc.set_type("cos_sim");
   BuildVar("input", {"aa"}, op_desc.add_inputs());
   BuildVar("output", {"bb"}, op_desc.add_outputs());
 
   auto attr = op_desc.mutable_attrs()->Add();
   attr->set_name("scale");
-  attr->set_type(paddle::framework::AttrType::FLOAT);
+  attr->set_type(paddle::framework::proto::AttrType::FLOAT);
   attr->set_f(-2.0);
 
   bool caught = false;
@@ -108,7 +108,7 @@ TEST(OpRegistry, IllegalAttr) {
 }
 
 TEST(OpRegistry, DefaultValue) {
-  paddle::framework::OpDesc op_desc;
+  paddle::framework::proto::OpDesc op_desc;
   op_desc.set_type("cos_sim");
   BuildVar("input", {"aa"}, op_desc.add_inputs());
   BuildVar("output", {"bb"}, op_desc.add_outputs());
@@ -123,7 +123,7 @@ TEST(OpRegistry, DefaultValue) {
 }
 
 TEST(OpRegistry, CustomChecker) {
-  paddle::framework::OpDesc op_desc;
+  paddle::framework::proto::OpDesc op_desc;
   op_desc.set_type("my_test_op");
   BuildVar("input", {"ii"}, op_desc.add_inputs());
   BuildVar("output", {"oo"}, op_desc.add_outputs());
@@ -145,7 +145,7 @@ TEST(OpRegistry, CustomChecker) {
   // set 'test_attr' set to an illegal value
   auto attr = op_desc.mutable_attrs()->Add();
   attr->set_name("test_attr");
-  attr->set_type(paddle::framework::AttrType::INT);
+  attr->set_type(paddle::framework::proto::AttrType::INT);
   attr->set_i(3);
   caught = false;
   try {
@@ -164,7 +164,7 @@ TEST(OpRegistry, CustomChecker) {
   op_desc.mutable_attrs()->Clear();
   attr = op_desc.mutable_attrs()->Add();
   attr->set_name("test_attr");
-  attr->set_type(paddle::framework::AttrType::INT);
+  attr->set_type(paddle::framework::proto::AttrType::INT);
   attr->set_i(4);
   auto op = paddle::framework::OpRegistry::CreateOp(op_desc);
   paddle::platform::CPUDeviceContext dev_ctx;

paddle/framework/operator.cc

@@ -377,7 +377,7 @@ class RuntimeInferShapeContext : public InferShapeContext {
     }
   }
 
-  VarDesc::VarType GetVarType(const std::string& name) const override {
+  proto::VarDesc::VarType GetVarType(const std::string& name) const override {
     auto* var = scope_.FindVar(name);
     return ToVarType(var->Type());
   }
@@ -417,7 +417,7 @@ OpKernelType OperatorWithKernel::GetKernelType(
     const ExecutionContext& ctx) const {
   return OpKernelType(IndicateDataType(ctx), ctx.GetPlace());
 }
-DataType OperatorWithKernel::IndicateDataType(
+proto::DataType OperatorWithKernel::IndicateDataType(
     const ExecutionContext& ctx) const {
   auto& scope = ctx.scope();
   int data_type = -1;
@@ -443,7 +443,7 @@ DataType OperatorWithKernel::IndicateDataType(
     }
   }
   PADDLE_ENFORCE(data_type != -1, "DataType should be indicated by input");
-  return static_cast<DataType>(data_type);
+  return static_cast<proto::DataType>(data_type);
 }
 
 }  // namespace framework

paddle/framework/operator.h

@@ -358,12 +358,13 @@ struct OpKernelType {
   };
 
   platform::Place place_;
-  DataType data_type_;
+  proto::DataType data_type_;
 
-  OpKernelType(DataType data_type, platform::Place place)
+  OpKernelType(proto::DataType data_type, platform::Place place)
       : place_(place), data_type_(data_type) {}
 
-  OpKernelType(DataType data_type, const platform::DeviceContext& dev_ctx)
+  OpKernelType(proto::DataType data_type,
+               const platform::DeviceContext& dev_ctx)
       : place_(dev_ctx.GetPlace()), data_type_(data_type) {}
 
   bool operator==(const OpKernelType& o) const {
@@ -409,7 +410,7 @@ class OperatorWithKernel : public OperatorBase {
  private:
   // indicate kernel DataType by input data. Defaultly all input data must be
   // same.
-  DataType IndicateDataType(const ExecutionContext& ctx) const;
+  proto::DataType IndicateDataType(const ExecutionContext& ctx) const;
 };
 
 std::ostream& operator<<(std::ostream& os, const OpKernelType& kernel_key);

paddle/framework/operator_test.cc

@@ -58,7 +58,7 @@ class OpeWithoutKernelTestProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
 
 static void BuildVar(const std::string& param_name,
                      std::initializer_list<const char*> arguments,
-                     paddle::framework::OpDesc::Var* var) {
+                     paddle::framework::proto::OpDesc::Var* var) {
   var->set_parameter(param_name);
   for (auto& arg_name : arguments) {
     *var->mutable_arguments()->Add() = arg_name;
@@ -70,14 +70,14 @@ REGISTER_OP_WITHOUT_GRADIENT(
     paddle::framework::OpeWithoutKernelTestProtoAndCheckerMaker);
 
 TEST(OperatorBase, all) {
-  paddle::framework::OpDesc op_desc;
+  paddle::framework::proto::OpDesc op_desc;
   op_desc.set_type("test_operator");
   BuildVar("input", {"IN1"}, op_desc.add_inputs());
   BuildVar("output", {"OUT1"}, op_desc.add_outputs());
 
   auto attr = op_desc.mutable_attrs()->Add();
   attr->set_name("scale");
-  attr->set_type(paddle::framework::AttrType::FLOAT);
+  attr->set_type(paddle::framework::proto::AttrType::FLOAT);
   attr->set_f(3.14);
 
   paddle::platform::CPUDeviceContext device_context;
@@ -115,7 +115,7 @@ class OpWithKernelTest : public OperatorWithKernel {
  protected:
   void InferShape(framework::InferShapeContext* ctx) const override {}
   OpKernelType GetKernelType(const ExecutionContext& ctx) const override {
-    return OpKernelType(DataType::FP32, ctx.GetPlace());
+    return OpKernelType(proto::DataType::FP32, ctx.GetPlace());
   }
 };
 
@@ -195,14 +195,14 @@ REGISTER_OP_CPU_KERNEL(op_with_kernel,
 
 // test with single input
 TEST(OpKernel, all) {
-  paddle::framework::OpDesc op_desc;
+  paddle::framework::proto::OpDesc op_desc;
   op_desc.set_type("op_with_kernel");
   BuildVar("x", {"IN1"}, op_desc.add_inputs());
   BuildVar("y", {"OUT1"}, op_desc.add_outputs());
 
   auto attr = op_desc.mutable_attrs()->Add();
   attr->set_name("scale");
-  attr->set_type(paddle::framework::AttrType::FLOAT);
+  attr->set_type(paddle::framework::proto::AttrType::FLOAT);
   attr->set_f(3.14);
 
   paddle::platform::CPUDeviceContext cpu_device_context;
@@ -224,7 +224,7 @@ REGISTER_OP_CPU_KERNEL(op_multi_inputs_with_kernel,
 TEST(OpKernel, multi_inputs) {
   using namespace paddle::framework;
 
-  OpDesc op_desc;
+  proto::OpDesc op_desc;
   op_desc.set_type("op_multi_inputs_with_kernel");
   BuildVar("xs", {"x0", "x1", "x2"}, op_desc.add_inputs());
   BuildVar("k", {"k0"}, op_desc.add_inputs());
@@ -232,7 +232,7 @@ TEST(OpKernel, multi_inputs) {
 
   auto attr = op_desc.mutable_attrs()->Add();
   attr->set_name("scale");
-  attr->set_type(paddle::framework::AttrType::FLOAT);
+  attr->set_type(paddle::framework::proto::AttrType::FLOAT);
   attr->set_f(3.14);
 
   paddle::platform::CPUDeviceContext cpu_device_context;

paddle/framework/program_desc.cc

@@ -26,7 +26,7 @@ BlockDescBind *ProgramDescBind::AppendBlock(const BlockDescBind &parent) {
   return blocks_.back().get();
 }
 
-ProgramDesc *ProgramDescBind::Proto() {
+proto::ProgramDesc *ProgramDescBind::Proto() {
   for (auto &block : blocks_) {
     block->Flush();
   }
@@ -49,7 +49,7 @@ ProgramDescBind::ProgramDescBind(const ProgramDescBind &o) {
   }
 }
 
-ProgramDescBind::ProgramDescBind(const ProgramDesc &desc) {
+ProgramDescBind::ProgramDescBind(const proto::ProgramDesc &desc) {
   desc_ = desc;
   for (auto &block_desc : *desc_.mutable_blocks()) {
     blocks_.emplace_back(new BlockDescBind(this, &block_desc));

paddle/framework/program_desc.h

@@ -29,7 +29,7 @@ class ProgramDescBind {
  public:
   ProgramDescBind();
 
-  explicit ProgramDescBind(const ProgramDesc &desc);
+  explicit ProgramDescBind(const proto::ProgramDesc &desc);
 
   ProgramDescBind(const ProgramDescBind &o);
 
@@ -43,10 +43,10 @@ class ProgramDescBind {
 
   size_t Size() const { return blocks_.size(); }
 
-  ProgramDesc *Proto();
+  proto::ProgramDesc *Proto();
 
  private:
-  ProgramDesc desc_;
+  proto::ProgramDesc desc_;
 
   std::vector<std::unique_ptr<BlockDescBind>> blocks_;
 };

paddle/framework/program_desc_test.cc

@@ -22,15 +22,15 @@ TEST(ProgramDesc, copy_ctor) {
   ProgramDescBind program;
   auto* global_block = program.MutableBlock(0);
   auto* x = global_block->Var("X");
-  x->SetType(VarDesc_VarType_LOD_TENSOR);
+  x->SetType(proto::VarDesc_VarType_LOD_TENSOR);
   x->SetLoDLevel(0);
-  x->SetDataType(FP32);
+  x->SetDataType(proto::FP32);
   x->SetShape({1000, 784});
 
   auto* y = global_block->Var("Y");
-  y->SetType(VarDesc_VarType_LOD_TENSOR);
+  y->SetType(proto::VarDesc_VarType_LOD_TENSOR);
   y->SetLoDLevel(0);
-  y->SetDataType(FP32);
+  y->SetDataType(proto::FP32);
   y->SetShape({784, 100});
 
   auto* op = global_block->AppendOp();
@@ -39,7 +39,7 @@ TEST(ProgramDesc, copy_ctor) {
   op->SetInput("Y", {y->Name()});
 
   auto* out = global_block->Var("Out");
-  out->SetType(VarDesc_VarType_LOD_TENSOR);
+  out->SetType(proto::VarDesc_VarType_LOD_TENSOR);
   op->SetOutput("Y", {out->Name()});
 
   ProgramDescBind program_copy(program);
@@ -84,15 +84,15 @@ TEST(ProgramDescBind, serialize_and_deserialize) {
   ProgramDescBind program_origin;
   auto* global_block = program_origin.MutableBlock(0);
   auto* x = global_block->Var("X");
-  x->SetType(VarDesc_VarType_LOD_TENSOR);
+  x->SetType(proto::VarDesc_VarType_LOD_TENSOR);
   x->SetLoDLevel(0);
-  x->SetDataType(FP32);
+  x->SetDataType(proto::FP32);
   x->SetShape({1000, 784});
 
   auto* y = global_block->Var("Y");
-  y->SetType(VarDesc_VarType_LOD_TENSOR);
+  y->SetType(proto::VarDesc_VarType_LOD_TENSOR);
   y->SetLoDLevel(0);
-  y->SetDataType(FP32);
+  y->SetDataType(proto::FP32);
   y->SetShape({784, 100});
 
   auto* op = global_block->AppendOp();
@@ -101,7 +101,7 @@ TEST(ProgramDescBind, serialize_and_deserialize) {
   op->SetInput("Y", {y->Name()});
 
   auto* out = global_block->Var("Out");
-  out->SetType(VarDesc_VarType_LOD_TENSOR);
+  out->SetType(proto::VarDesc_VarType_LOD_TENSOR);
   op->SetOutput("Y", {out->Name()});
 
   std::string binary_str;

paddle/framework/prune.cc

@@ -29,7 +29,7 @@ const std::string kFetchOpType = "fetch";
 const std::string kDropOutOpType = "dropout";
 const std::string kBatchNormOpType = "batch_norm";
 
-bool HasDependentVar(const OpDesc& op_desc,
+bool HasDependentVar(const proto::OpDesc& op_desc,
                      const std::set<std::string>& dependent_vars) {
   for (auto& var : op_desc.outputs()) {
     for (auto& argu : var.arguments()) {
@@ -41,14 +41,15 @@ bool HasDependentVar(const OpDesc& op_desc,
   return false;
 }
 
-bool IsTarget(const OpDesc& op_desc) {
+bool IsTarget(const proto::OpDesc& op_desc) {
   if (op_desc.has_is_target()) {
     return op_desc.is_target();
   }
   return false;
 }
 
-void prune_impl(const ProgramDesc& input, ProgramDesc* output, int block_id) {
+void prune_impl(const proto::ProgramDesc& input, proto::ProgramDesc* output,
+                int block_id) {
   // TODO(tonyyang-svail):
   //    - will change to use multiple blocks for RNN op and Cond Op
 
@@ -104,12 +105,12 @@ void prune_impl(const ProgramDesc& input, ProgramDesc* output, int block_id) {
 }
 
 // TODO(fengjiayi): Prune() could be inplaced to avoid unnecessary copies
-void Prune(const ProgramDesc& input, ProgramDesc* output) {
+void Prune(const proto::ProgramDesc& input, proto::ProgramDesc* output) {
   prune_impl(input, output, 0);
 }
 
-void inference_optimize_impl(const ProgramDesc& input, ProgramDesc* output,
-                             int block_id) {
+void inference_optimize_impl(const proto::ProgramDesc& input,
+                             proto::ProgramDesc* output, int block_id) {
   *output = input;
   auto* op_field = output->mutable_blocks(block_id)->mutable_ops();
   for (auto& op_desc : *op_field) {
@@ -125,7 +126,8 @@ void inference_optimize_impl(const ProgramDesc& input, ProgramDesc* output,
   }
 }
 
-void InferenceOptimize(const ProgramDesc& input, ProgramDesc* output) {
+void InferenceOptimize(const proto::ProgramDesc& input,
+                       proto::ProgramDesc* output) {
   inference_optimize_impl(input, output, 0);
 }
 

paddle/framework/prune.h

@@ -20,9 +20,10 @@ limitations under the License. */
 namespace paddle {
 namespace framework {
 
-void Prune(const ProgramDesc& input, ProgramDesc* output);
+void Prune(const proto::ProgramDesc& input, proto::ProgramDesc* output);
 
-void InferenceOptimize(const ProgramDesc& input, ProgramDesc* output);
+void InferenceOptimize(const proto::ProgramDesc& input,
+                       proto::ProgramDesc* output);
 
 }  // namespace framework
 }  // namespace paddle

paddle/framework/prune_test.cc

@@ -34,7 +34,7 @@ void AddOp(const std::string &type, const f::VariableNameMap &inputs,
   for (auto kv : outputs) {
     for (auto v : kv.second) {
       auto var = block->Var(v);
-      var->SetDataType(paddle::framework::DataType::FP32);
+      var->SetDataType(paddle::framework::proto::DataType::FP32);
     }
   }
 
@@ -57,14 +57,14 @@ TEST(Prune, one_operator) {
   AddOp("one_one", {{"input", {"a"}}}, {{"output", {"b"}}}, f::AttributeMap{},
         block);
 
-  f::ProgramDesc *pdesc = program.Proto();
-  f::ProgramDesc pruned;
+  f::proto::ProgramDesc *pdesc = program.Proto();
+  f::proto::ProgramDesc pruned;
 
-  Prune(*pdesc, &pruned);
+  f::Prune(*pdesc, &pruned);
   PADDLE_ENFORCE_EQ(pruned.blocks(0).ops_size(), 0);
 
   pdesc->mutable_blocks(0)->mutable_ops(0)->set_is_target(true);
-  Prune(*pdesc, &pruned);
+  f::Prune(*pdesc, &pruned);
   PADDLE_ENFORCE_EQ(pruned.blocks(0).ops_size(), 1);
 }
 
@@ -81,12 +81,12 @@ TEST(Prune, forward) {
   AddOp("one_one", {{"input", {"d"}}}, {{"output", {"e"}}}, f::AttributeMap{},
         block);
 
-  f::ProgramDesc *pdesc = program.Proto();
+  f::proto::ProgramDesc *pdesc = program.Proto();
 
   for (int i = 0; i < pdesc->blocks(0).ops_size(); ++i) {
-    f::ProgramDesc pruned;
+    f::proto::ProgramDesc pruned;
     pdesc->mutable_blocks(0)->mutable_ops(i)->set_is_target(true);
-    Prune(*pdesc, &pruned);
+    f::Prune(*pdesc, &pruned);
     PADDLE_ENFORCE_EQ(pruned.blocks(0).ops_size(), i + 1);
   }
 }
@@ -104,11 +104,11 @@ TEST(Prune, multi_input_op) {
   AddOp("three_one", {{"input", {"b0", "b1", "b2"}}}, {{"output", {"c"}}},
         f::AttributeMap{}, block);
 
-  f::ProgramDesc *pdesc = program.Proto();
+  f::proto::ProgramDesc *pdesc = program.Proto();
   pdesc->mutable_blocks(0)->mutable_ops(3)->set_is_target(true);
 
-  f::ProgramDesc pruned;
-  Prune(*pdesc, &pruned);
+  f::proto::ProgramDesc pruned;
+  f::Prune(*pdesc, &pruned);
   PADDLE_ENFORCE_EQ(pruned.blocks(0).ops_size(), 4);
 }
 
@@ -123,11 +123,11 @@ TEST(Prune, multi_output_op) {
   AddOp("one_one", {{"input", {"c"}}}, {{"output", {"c1"}}}, f::AttributeMap{},
         block);
 
-  f::ProgramDesc *pdesc = program.Proto();
+  f::proto::ProgramDesc *pdesc = program.Proto();
   pdesc->mutable_blocks(0)->mutable_ops(2)->set_is_target(true);
 
-  f::ProgramDesc pruned;
-  Prune(*pdesc, &pruned);
+  f::proto::ProgramDesc pruned;
+  f::Prune(*pdesc, &pruned);
   PADDLE_ENFORCE_EQ(pruned.blocks(0).ops_size(), 2);
 }
 
@@ -142,11 +142,11 @@ TEST(Prune, multi_target) {
   AddOp("one_one", {{"input", {"c"}}}, {{"output", {"c1"}}}, f::AttributeMap{},
         block);
 
-  f::ProgramDesc *pdesc = program.Proto();
+  f::proto::ProgramDesc *pdesc = program.Proto();
   pdesc->mutable_blocks(0)->mutable_ops(1)->set_is_target(true);
   pdesc->mutable_blocks(0)->mutable_ops(2)->set_is_target(true);
 
-  f::ProgramDesc pruned;
-  Prune(*pdesc, &pruned);
+  f::proto::ProgramDesc pruned;
+  f::Prune(*pdesc, &pruned);
   PADDLE_ENFORCE_EQ(pruned.blocks(0).ops_size(), 3);
 }

paddle/framework/shape_inference.cc

@@ -57,17 +57,17 @@ void InferShapeContext::SetDims(const std::vector<std::string> &names,
     SetDim(names[i], dims[i]);
   }
 }
-std::vector<VarDesc::VarType> InferShapeContext::GetInputsVarType(
+std::vector<proto::VarDesc::VarType> InferShapeContext::GetInputsVarType(
     const std::string &name) const {
   return GetVarTypes(Inputs(name));
 }
-std::vector<VarDesc::VarType> InferShapeContext::GetOutputsVarType(
+std::vector<proto::VarDesc::VarType> InferShapeContext::GetOutputsVarType(
     const std::string &name) const {
   return GetVarTypes(Outputs(name));
 }
-std::vector<VarDesc::VarType> InferShapeContext::GetVarTypes(
+std::vector<proto::VarDesc::VarType> InferShapeContext::GetVarTypes(
     const std::vector<std::string> &names) const {
-  std::vector<VarDesc::VarType> retv;
+  std::vector<proto::VarDesc::VarType> retv;
   retv.resize(names.size());
   std::transform(names.begin(), names.end(), retv.begin(),
                  std::bind(std::mem_fn(&InferShapeContext::GetVarType), this,

paddle/framework/shape_inference.h

@@ -27,8 +27,9 @@ class InferShapeContext {
   virtual bool HasInput(const std::string &name) const = 0;
   virtual bool HasOutput(const std::string &name) const = 0;
 
-  std::vector<VarDesc::VarType> GetInputsVarType(const std::string &name) const;
-  std::vector<VarDesc::VarType> GetOutputsVarType(
+  std::vector<proto::VarDesc::VarType> GetInputsVarType(
+      const std::string &name) const;
+  std::vector<proto::VarDesc::VarType> GetOutputsVarType(
       const std::string &name) const;
 
   virtual bool HasInputs(const std::string &name) const = 0;
@@ -65,10 +66,10 @@ class InferShapeContext {
   std::vector<framework::DDim> GetDims(
       const std::vector<std::string> &names) const;
 
-  std::vector<VarDesc::VarType> GetVarTypes(
+  std::vector<proto::VarDesc::VarType> GetVarTypes(
       const std::vector<std::string> &names) const;
 
-  virtual VarDesc::VarType GetVarType(const std::string &name) const = 0;
+  virtual proto::VarDesc::VarType GetVarType(const std::string &name) const = 0;
 };
 
 }  // namespace framework

paddle/framework/var_desc.cc

@@ -18,15 +18,17 @@ limitations under the License. */
 namespace paddle {
 namespace framework {
 
-VarDesc::VarType VarDescBind::GetType() const { return desc_.type(); }
+proto::VarDesc::VarType VarDescBind::GetType() const { return desc_.type(); }
 
-void VarDescBind::SetType(VarDesc::VarType type) { desc_.set_type(type); }
+void VarDescBind::SetType(proto::VarDesc::VarType type) {
+  desc_.set_type(type);
+}
 
 void VarDescBind::SetShape(const std::vector<int64_t> &dims) {
   VectorToRepeated(dims, mutable_tensor_desc()->mutable_dims());
 }
 
-void VarDescBind::SetDataType(DataType data_type) {
+void VarDescBind::SetDataType(proto::DataType data_type) {
   mutable_tensor_desc()->set_data_type(data_type);
 }
 
@@ -34,14 +36,16 @@ std::vector<int64_t> VarDescBind::Shape() const {
   return RepeatedToVector(tensor_desc().dims());
 }
 
-DataType VarDescBind::GetDataType() const { return tensor_desc().data_type(); }
+proto::DataType VarDescBind::GetDataType() const {
+  return tensor_desc().data_type();
+}
 
 void VarDescBind::SetLoDLevel(int32_t lod_level) {
   switch (desc_.type()) {
-    case VarDesc::LOD_TENSOR:
+    case proto::VarDesc::LOD_TENSOR:
       desc_.mutable_lod_tensor()->set_lod_level(lod_level);
       break;
-    case VarDesc::LOD_TENSOR_ARRAY:
+    case proto::VarDesc::LOD_TENSOR_ARRAY:
       desc_.mutable_tensor_array()->set_lod_level(lod_level);
       break;
     default:
@@ -52,9 +56,9 @@ void VarDescBind::SetLoDLevel(int32_t lod_level) {
 
 int32_t VarDescBind::GetLodLevel() const {
   switch (desc_.type()) {
-    case VarDesc::LOD_TENSOR:
+    case proto::VarDesc::LOD_TENSOR:
       return desc_.lod_tensor().lod_level();
-    case VarDesc::LOD_TENSOR_ARRAY:
+    case proto::VarDesc::LOD_TENSOR_ARRAY:
       return desc_.tensor_array().lod_level();
     default:
       PADDLE_THROW("Tensor type=%d does not support LoDLevel",
@@ -62,29 +66,29 @@ int32_t VarDescBind::GetLodLevel() const {
   }
 }
 
-const TensorDesc &VarDescBind::tensor_desc() const {
+const proto::TensorDesc &VarDescBind::tensor_desc() const {
   PADDLE_ENFORCE(desc_.has_type(), "invoke TensorDesc must after set type");
   switch (desc_.type()) {
-    case VarDesc::SELECTED_ROWS:
+    case proto::VarDesc::SELECTED_ROWS:
       return desc_.selected_rows();
-    case VarDesc::LOD_TENSOR:
+    case proto::VarDesc::LOD_TENSOR:
       return desc_.lod_tensor().tensor();
-    case VarDesc::LOD_TENSOR_ARRAY:
+    case proto::VarDesc::LOD_TENSOR_ARRAY:
       return desc_.tensor_array().tensor();
     default:
       PADDLE_THROW("Unexpected branch.");
   }
 }
 
-TensorDesc *VarDescBind::mutable_tensor_desc() {
+proto::TensorDesc *VarDescBind::mutable_tensor_desc() {
   PADDLE_ENFORCE(desc_.has_type(),
                  "invoke MutableTensorDesc must after set type");
   switch (desc_.type()) {
-    case VarDesc::SELECTED_ROWS:
+    case proto::VarDesc::SELECTED_ROWS:
       return desc_.mutable_selected_rows();
-    case VarDesc::LOD_TENSOR:
+    case proto::VarDesc::LOD_TENSOR:
       return desc_.mutable_lod_tensor()->mutable_tensor();
-    case VarDesc::LOD_TENSOR_ARRAY:
+    case proto::VarDesc::LOD_TENSOR_ARRAY:
       return desc_.mutable_tensor_array()->mutable_tensor();
     default:
       PADDLE_THROW("Unexpected branch.");

paddle/framework/var_desc.h

@@ -57,40 +57,40 @@ class VarDescBind {
  public:
   explicit VarDescBind(const std::string &name) {
     desc_.set_name(name);
-    desc_.set_type(VarDesc::LOD_TENSOR);
+    desc_.set_type(proto::VarDesc::LOD_TENSOR);
   }
 
-  explicit VarDescBind(const VarDesc &desc) : desc_(desc) {}
+  explicit VarDescBind(const proto::VarDesc &desc) : desc_(desc) {}
 
-  VarDesc *Proto() { return &desc_; }
+  proto::VarDesc *Proto() { return &desc_; }
 
   std::string Name() const { return desc_.name(); }
 
   void SetShape(const std::vector<int64_t> &dims);
 
-  void SetDataType(DataType data_type);
+  void SetDataType(proto::DataType data_type);
 
   std::vector<int64_t> Shape() const;
 
-  DataType GetDataType() const;
+  proto::DataType GetDataType() const;
 
   void SetLoDLevel(int32_t lod_level);
 
   int32_t GetLodLevel() const;
 
-  VarDesc::VarType GetType() const;
+  proto::VarDesc::VarType GetType() const;
 
-  void SetType(VarDesc::VarType type);
+  void SetType(proto::VarDesc::VarType type);
 
   bool Persistable() const { return desc_.persistable(); }
 
   void SetPersistable(bool persistable) { desc_.set_persistable(persistable); }
 
  private:
-  const TensorDesc &tensor_desc() const;
-  TensorDesc *mutable_tensor_desc();
+  const proto::TensorDesc &tensor_desc() const;
+  proto::TensorDesc *mutable_tensor_desc();
 
-  VarDesc desc_;
+  proto::VarDesc desc_;
 };
 }  // namespace framework
 }  // namespace paddle

paddle/framework/var_type.h

@@ -20,15 +20,15 @@
 
 namespace paddle {
 namespace framework {
-inline VarDesc::VarType ToVarType(std::type_index type) {
+inline proto::VarDesc::VarType ToVarType(std::type_index type) {
   if (type.hash_code() == typeid(LoDTensor).hash_code()) {
-    return VarDesc_VarType_LOD_TENSOR;
+    return proto::VarDesc_VarType_LOD_TENSOR;
   } else if (type.hash_code() == typeid(LoDRankTable).hash_code()) {
-    return VarDesc_VarType_LOD_RANK_TABLE;
+    return proto::VarDesc_VarType_LOD_RANK_TABLE;
   } else if (type.hash_code() == typeid(LoDTensorArray).hash_code()) {
-    return VarDesc_VarType_LOD_TENSOR_ARRAY;
+    return proto::VarDesc_VarType_LOD_TENSOR_ARRAY;
   } else if (type.hash_code() == typeid(SelectedRows).hash_code()) {
-    return VarDesc_VarType_SELECTED_ROWS;
+    return proto::VarDesc_VarType_SELECTED_ROWS;
   } else {
     PADDLE_THROW("ToVarType:Unsupported type %s", type.name());
   }
@@ -37,16 +37,16 @@ inline VarDesc::VarType ToVarType(std::type_index type) {
 template <typename Visitor>
 inline void VisitVarType(const Variable& var, Visitor visitor) {
   switch (ToVarType(var.Type())) {
-    case VarDesc_VarType_LOD_TENSOR:
+    case proto::VarDesc_VarType_LOD_TENSOR:
       visitor(var.Get<framework::LoDTensor>());
       return;
-    case VarDesc_VarType_LOD_RANK_TABLE:
+    case proto::VarDesc_VarType_LOD_RANK_TABLE:
       visitor(var.Get<LoDRankTable>());
       return;
-    case VarDesc_VarType_LOD_TENSOR_ARRAY:
+    case proto::VarDesc_VarType_LOD_TENSOR_ARRAY:
       visitor(var.Get<LoDTensorArray>());
       return;
-    case VarDesc_VarType_SELECTED_ROWS:
+    case proto::VarDesc_VarType_SELECTED_ROWS:
       visitor(var.Get<SelectedRows>());
       return;
     default:

paddle/framework/var_type_inference_test.cc

@@ -36,14 +36,14 @@ class SumOpVarTypeInference : public VarTypeInference {
   void operator()(const OpDescBind &op_desc,
                   BlockDescBind *block) const override {
     auto &inputs = op_desc.Input("X");
-    auto default_var_type = VarDesc::SELECTED_ROWS;
+    auto default_var_type = proto::VarDesc::SELECTED_ROWS;
 
     bool any_input_is_lod_tensor = std::any_of(
         inputs.begin(), inputs.end(), [block](const std::string &name) {
-          return block->Var(name)->GetType() == VarDesc::LOD_TENSOR;
+          return block->Var(name)->GetType() == proto::VarDesc::LOD_TENSOR;
         });
     if (any_input_is_lod_tensor) {
-      default_var_type = VarDesc::LOD_TENSOR;
+      default_var_type = proto::VarDesc::LOD_TENSOR;
     }
 
     auto out_var_name = op_desc.Output("Out").front();
@@ -68,19 +68,19 @@ TEST(InferVarType, sum_op) {
   op->SetInput("X", {"test_a", "test_b", "test_c"});
   op->SetOutput("Out", {"test_out"});
 
-  prog.MutableBlock(0)->Var("test_a")->SetType(VarDesc::SELECTED_ROWS);
-  prog.MutableBlock(0)->Var("test_b")->SetType(VarDesc::SELECTED_ROWS);
-  prog.MutableBlock(0)->Var("test_c")->SetType(VarDesc::SELECTED_ROWS);
+  prog.MutableBlock(0)->Var("test_a")->SetType(proto::VarDesc::SELECTED_ROWS);
+  prog.MutableBlock(0)->Var("test_b")->SetType(proto::VarDesc::SELECTED_ROWS);
+  prog.MutableBlock(0)->Var("test_c")->SetType(proto::VarDesc::SELECTED_ROWS);
   prog.MutableBlock(0)->Var("test_out");
 
   op->InferVarType(prog.MutableBlock(0));
 
-  ASSERT_EQ(VarDesc::SELECTED_ROWS,
+  ASSERT_EQ(proto::VarDesc::SELECTED_ROWS,
             prog.MutableBlock(0)->Var("test_out")->GetType());
 
-  prog.MutableBlock(0)->Var("test_b")->SetType(VarDesc::LOD_TENSOR);
+  prog.MutableBlock(0)->Var("test_b")->SetType(proto::VarDesc::LOD_TENSOR);
   op->InferVarType(prog.MutableBlock(0));
-  ASSERT_EQ(VarDesc::LOD_TENSOR,
+  ASSERT_EQ(proto::VarDesc::LOD_TENSOR,
             prog.MutableBlock(0)->Var("test_out")->GetType());
 }
 
@@ -91,14 +91,14 @@ TEST(InferVarType, sum_op_without_infer_var_type) {
   op->SetInput("X", {"test2_a", "test2_b", "test2_c"});
   op->SetOutput("Out", {"test2_out"});
 
-  prog.MutableBlock(0)->Var("test2_a")->SetType(VarDesc::SELECTED_ROWS);
-  prog.MutableBlock(0)->Var("test2_b")->SetType(VarDesc::SELECTED_ROWS);
-  prog.MutableBlock(0)->Var("test2_c")->SetType(VarDesc::SELECTED_ROWS);
+  prog.MutableBlock(0)->Var("test2_a")->SetType(proto::VarDesc::SELECTED_ROWS);
+  prog.MutableBlock(0)->Var("test2_b")->SetType(proto::VarDesc::SELECTED_ROWS);
+  prog.MutableBlock(0)->Var("test2_c")->SetType(proto::VarDesc::SELECTED_ROWS);
   prog.MutableBlock(0)->Var("test2_out");
 
   op->InferVarType(prog.MutableBlock(0));
 
-  ASSERT_EQ(VarDesc_VarType_LOD_TENSOR,
+  ASSERT_EQ(proto::VarDesc_VarType_LOD_TENSOR,
             prog.MutableBlock(0)->Var("test2_out")->GetType());
 }
 

paddle/operators/accuracy_op.cc

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

paddle/operators/activation_op.cc

@@ -38,9 +38,8 @@ class ActivationOpGrad : public framework::OperatorWithKernel {
 
 class SigmoidOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SigmoidOpMaker(framework::OpProto *proto,
-                 framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  SigmoidOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of Sigmoid operator");
     AddOutput("Y", "Output of Sigmoid operator");
     AddComment(R"DOC(
@@ -54,9 +53,8 @@ $$y = \frac{1}{1 + e^{-x}}$$
 
 class LogSigmoidOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LogSigmoidOpMaker(framework::OpProto *proto,
-                    framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  LogSigmoidOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of LogSigmoid operator");
     AddOutput("Y", "Output of LogSigmoid operator");
     AddComment(R"DOC(
@@ -70,8 +68,8 @@ $$y = \log \frac{1}{1 + e^{-x}}$$
 
 class ExpOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ExpOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  ExpOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of Exp operator");
     AddOutput("Y", "Output of Exp operator");
     AddComment(R"DOC(
@@ -85,8 +83,8 @@ $y = e^x$
 
 class ReluOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ReluOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  ReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of Relu operator");
     AddOutput("Y", "Output of Relu operator");
     AddComment(R"DOC(
@@ -100,9 +98,8 @@ $y = \max(x, 0)$
 
 class LeakyReluOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LeakyReluOpMaker(framework::OpProto *proto,
-                   framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  LeakyReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of LeakyRelu operator");
     AddOutput("Y", "Output of LeakyRelu operator");
     AddAttr<float>("alpha", "The small negative slope").SetDefault(0.02f);
@@ -117,9 +114,8 @@ $y = \max(x, \alpha * x)$
 
 class SoftShrinkOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SoftShrinkOpMaker(framework::OpProto *proto,
-                    framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  SoftShrinkOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of Softshrink operator");
     AddOutput("Y", "Output of Softshrink operator");
     AddAttr<float>("lambda", "non-negative offset").SetDefault(0.5f);
@@ -140,8 +136,8 @@ $$
 
 class TanhOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  TanhOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  TanhOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of Tanh operator");
     AddOutput("Y", "Output of Tanh operator");
     AddComment(R"DOC(
@@ -155,9 +151,8 @@ $$y = \frac{e^{x} - e^{-x}}{e^{x} + e^{-x}}$$
 
 class TanhShrinkOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  TanhShrinkOpMaker(framework::OpProto *proto,
-                    framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  TanhShrinkOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of TanhShrink operator");
     AddOutput("Y", "Output of TanhShrink operator");
     AddComment(R"DOC(
@@ -171,9 +166,8 @@ $$y = x - \frac{e^{x} - e^{-x}}{e^{x} + e^{-x}}$$
 
 class HardShrinkOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  HardShrinkOpMaker(framework::OpProto *proto,
-                    framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  HardShrinkOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of HardShrink operator");
     AddOutput("Y", "Output of HardShrink operator");
     AddAttr<float>("threshold", "The value of threshold for HardShrink")
@@ -195,8 +189,8 @@ $$
 
 class SqrtOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SqrtOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  SqrtOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of Sqrt operator");
     AddOutput("Y", "Output of Sqrt operator");
     AddComment(R"DOC(
@@ -210,8 +204,8 @@ $y = \sqrt{x}$
 
 class AbsOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  AbsOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  AbsOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of Abs operator");
     AddOutput("Y", "Output of Abs operator");
     AddComment(R"DOC(
@@ -225,8 +219,8 @@ $y = |x|$
 
 class CeilOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  CeilOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  CeilOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of Ceil operator");
     AddOutput("Y", "Output of Ceil operator");
     AddComment(R"DOC(
@@ -240,8 +234,8 @@ $y = ceil(x)$
 
 class FloorOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  FloorOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  FloorOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of Floor operator");
     AddOutput("Y", "Output of Floor operator");
     AddComment(R"DOC(
@@ -255,8 +249,8 @@ $y = floor(x)$
 
 class RoundOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  RoundOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  RoundOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of Round operator");
     AddOutput("Y", "Output of Round operator");
     AddComment(R"DOC(
@@ -270,9 +264,8 @@ $y = [x]$
 
 class ReciprocalOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ReciprocalOpMaker(framework::OpProto *proto,
-                    framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  ReciprocalOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of Reciprocal operator");
     AddOutput("Y", "Output of Reciprocal operator");
     AddComment(R"DOC(
@@ -286,8 +279,8 @@ $$y = \frac{1}{x}$$
 
 class LogOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LogOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  LogOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of Log operator");
     AddOutput("Y", "Output of Log operator");
     AddComment(R"DOC(
@@ -303,8 +296,8 @@ Natural logarithm of x.
 
 class SquareOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SquareOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  SquareOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of Square operator");
     AddOutput("Y", "Output of Square operator");
     AddComment(R"DOC(
@@ -318,9 +311,8 @@ $y = x^2$
 
 class SoftplusOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SoftplusOpMaker(framework::OpProto *proto,
-                  framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  SoftplusOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of Softplus operator");
     AddOutput("Y", "Output of Softplus operator");
     AddComment(R"DOC(
@@ -334,9 +326,8 @@ $y = \ln(1 + e^{x})$
 
 class SoftsignOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SoftsignOpMaker(framework::OpProto *proto,
-                  framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  SoftsignOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of Softsign operator");
     AddOutput("Y", "Output of Softsign operator");
     AddComment(R"DOC(
@@ -350,8 +341,8 @@ $$y = \frac{x}{1 + |x|}$$
 
 class BReluOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  BReluOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  BReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of BRelu operator");
     AddOutput("Y", "Output of BRelu operator");
     AddAttr<float>("t_min", "The min marginal value of BRelu")
@@ -369,9 +360,8 @@ $y = \max(\min(x, t_{min}), t_{max})$
 
 class SoftReluOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SoftReluOpMaker(framework::OpProto *proto,
-                  framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  SoftReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of SoftRelu operator");
     AddOutput("Y", "Output of SoftRelu operator");
     AddAttr<float>("threshold", "The threshold value of SoftRelu")
@@ -387,8 +377,8 @@ $y = \ln(1 + \exp(\max(\min(x, threshold), threshold))$
 
 class ELUOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ELUOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  ELUOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of ELU operator");
     AddOutput("Y", "Output of ELU operator");
     AddAttr<float>("alpha", "The alpha value of ELU").SetDefault(1.0f);
@@ -406,8 +396,8 @@ $y = \max(0, x) + \min(0, \alpha * (e^x - 1))$
 
 class Relu6OpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  Relu6OpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  Relu6OpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of Relu6 operator");
     AddOutput("Y", "Output of Relu6 operator");
     AddAttr<float>("threshold", "The threshold value of Relu6")
@@ -423,8 +413,8 @@ $y = \min(\max(0, x), 6)$
 
 class PowOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  PowOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  PowOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of Pow operator");
     AddOutput("Y", "Output of Pow operator");
     AddAttr<float>("factor", "The exponential factor of Pow").SetDefault(1.0f);
@@ -439,8 +429,8 @@ $y = x^{factor}$
 
 class STanhOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  STanhOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  STanhOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of STanh operator");
     AddOutput("Y", "Output of STanh operator");
     AddAttr<float>("scale_a", "The scale parameter of a for the input")
@@ -458,9 +448,8 @@ $$y = b * \frac{e^{a * x} - e^{-a * x}}{e^{a * x} + e^{-a * x}}$$
 
 class ThresholdedReluOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ThresholdedReluOpMaker(framework::OpProto *proto,
-                         framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  ThresholdedReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of ThresholdedRelu operator");
     AddOutput("Y", "Output of ThresholdedRelu operator");
     AddAttr<float>("threshold", "The threshold location of activation")
@@ -481,9 +470,8 @@ $$
 
 class HardSigmoidOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  HardSigmoidOpMaker(framework::OpProto *proto,
-                     framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  HardSigmoidOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of HardSigmoid operator");
     AddOutput("Y", "Output of HardSigmoid operator");
     AddAttr<float>("slope", "Slope for linear approximation of sigmoid")
@@ -508,8 +496,8 @@ It is recommended to use the defaults for this activation.
 
 class SwishOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SwishOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  SwishOpMaker(OpProto *proto, OpAttrChecker *op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input of Swish operator");
     AddOutput("Y", "Output of Swish operator");
     AddAttr<float>("beta", "Constant beta of swish operator").SetDefault(1.0f);

paddle/operators/adadelta_op.cc

@@ -59,8 +59,7 @@ class AdadeltaOp : public framework::OperatorWithKernel {
 
 class AdadeltaOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  AdadeltaOpMaker(framework::OpProto *proto,
-                  framework::OpAttrChecker *op_checker)
+  AdadeltaOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Param", "(Tensor) Input parameter");
     AddInput("Grad", "(Tensor) Input gradient");

paddle/operators/adagrad_op.cc

@@ -59,8 +59,7 @@ class AdagradOp : public framework::OperatorWithKernel {
 
 class AdagradOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  AdagradOpMaker(framework::OpProto* proto,
-                 framework::OpAttrChecker* op_checker)
+  AdagradOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Param", "(Tensor) Input parameter");
     AddInput("Grad", "(Tensor) Input gradient");

paddle/operators/adam_op.cc

@@ -73,7 +73,7 @@ class AdamOp : public framework::OperatorWithKernel {
 
 class AdamOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  AdamOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  AdamOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Param", "(Tensor) Input parameter");
     AddInput("Grad", "(Tensor) Input gradient");

paddle/operators/adamax_op.cc

@@ -67,7 +67,7 @@ class AdamaxOp : public framework::OperatorWithKernel {
 
 class AdamaxOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  AdamaxOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  AdamaxOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Param", "(Tensor) Input parameter");
     AddInput("Grad", "(Tensor) Input gradient");

paddle/operators/array_to_lod_tensor_op.cc

@@ -114,8 +114,7 @@ class ArrayToLoDTensorOp : public framework::OperatorBase {
 
 class ArrayToLoDTensorOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ArrayToLoDTensorOpProtoMaker(framework::OpProto *proto,
-                               framework::OpAttrChecker *op_checker)
+  ArrayToLoDTensorOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(std::vector<LodTensor>) A vector of tensors that is going to "

paddle/operators/assign_op.cc

@@ -86,8 +86,7 @@ class AssignOp : public framework::OperatorBase {
 
 class AssignOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  AssignOpProtoMaker(framework::OpProto *proto,
-                     framework::OpAttrChecker *op_checker)
+  AssignOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(LoDTensor, SelectedRows or LoDTensorArray) The input variable "
@@ -109,8 +108,8 @@ class AssignInferShape : public framework::InferShapeBase {
   void operator()(framework::InferShapeContext *context) const override {
     if (context->HasInput("X")) {
       auto type = context->GetInputsVarType("X")[0];
-      if (type == framework::VarDesc_VarType_SELECTED_ROWS ||
-          type == framework::VarDesc_VarType_LOD_TENSOR) {
+      if (type == framework::proto::VarDesc_VarType_SELECTED_ROWS ||
+          type == framework::proto::VarDesc_VarType_LOD_TENSOR) {
         context->SetOutputDim("Out", context->GetInputDim("X"));
       }
     }

paddle/operators/auc_op.cc

@@ -49,7 +49,7 @@ class AucOp : public framework::OperatorWithKernel {
 
 class AucOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  AucOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  AucOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Out",
              "A floating point 2D tensor, values are in the range [0, 1]."

paddle/operators/batch_norm_op.cc

@@ -85,8 +85,7 @@ class BatchNormOp : public framework::OperatorWithKernel {
 
 class BatchNormOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  BatchNormOpMaker(framework::OpProto *proto,
-                   framework::OpAttrChecker *op_checker)
+  BatchNormOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddAttr<bool>("is_test", "").SetDefault(false);
     AddAttr<float>("momentum", "").SetDefault(0.9);

paddle/operators/beam_search_decode_op.cc

@@ -83,9 +83,8 @@ class BeamSearchDecodeOp : public framework::OperatorBase {
 
 class BeamSearchDecodeOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  BeamSearchDecodeOpProtoMaker(framework::OpProto* proto,
-                               framework::OpAttrChecker* op_checker)
-      : OpProtoAndCheckerMaker(proto, op_checker) {
+  BeamSearchDecodeOpProtoMaker(OpProto* proto, OpAttrChecker* op_checker)
+      : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Ids",
              "(LodTensorArray)"
              "score of the candidate words in each step");
@@ -123,10 +122,10 @@ class BeamSearchDecodeInferVarType : public framework::VarTypeInference {
   void operator()(const framework::OpDescBind& op_desc,
                   framework::BlockDescBind* block) const override {
     for (auto& o : op_desc.Output("SentenceIds")) {
-      block->Var(o)->SetType(framework::VarDesc::LOD_TENSOR);
+      block->Var(o)->SetType(framework::proto::VarDesc::LOD_TENSOR);
     }
     for (auto& o : op_desc.Output("SentenceScores")) {
-      block->Var(o)->SetType(framework::VarDesc::LOD_TENSOR);
+      block->Var(o)->SetType(framework::proto::VarDesc::LOD_TENSOR);
     }
   }
 };

paddle/operators/beam_search_op.cc

@@ -153,8 +153,7 @@ bool BeamSearch::NextItemSet(std::vector<BeamSearch::Item> *items) {
 class BeamSearchProtoAndCheckerMaker
     : public framework::OpProtoAndCheckerMaker {
  public:
-  BeamSearchProtoAndCheckerMaker(framework::OpProto *proto,
-                                 framework::OpAttrChecker *op_checker)
+  BeamSearchProtoAndCheckerMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     // inputs and outputs stored in proto
     AddInput("pre_ids", "ids in previous step");

paddle/operators/bilinear_tensor_product_op.cc

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

paddle/operators/cast_op.cc

@@ -20,8 +20,7 @@ namespace operators {
 
 class CastOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  CastOpProtoMaker(framework::OpProto *proto,
-                   framework::OpAttrChecker *op_checker)
+  CastOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "The input tensor of cast op");
     AddOutput("Out", "The output tensor of cast op");

paddle/operators/cast_op.h

@@ -55,7 +55,7 @@ class CastOpKernel : public framework::OpKernel<InT> {
     auto* in = context.Input<framework::Tensor>("X");
     auto* out = context.Output<framework::Tensor>("Out");
     framework::VisitDataType(
-        static_cast<framework::DataType>(context.Attr<int>("out_dtype")),
+        static_cast<framework::proto::DataType>(context.Attr<int>("out_dtype")),
         CastOpFunctor<DeviceContext, InT>(
             in, out, context.template device_context<DeviceContext>()));
   }

paddle/operators/chunk_eval_op.cc

@@ -57,15 +57,14 @@ class ChunkEvalOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetKernelType(
       const framework::ExecutionContext &ctx) const override {
-    return framework::OpKernelType(framework::DataType::FP32,
+    return framework::OpKernelType(framework::proto::DataType::FP32,
                                    ctx.device_context());
   }
 };
 
 class ChunkEvalOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ChunkEvalOpMaker(framework::OpProto *proto,
-                   framework::OpAttrChecker *op_checker)
+  ChunkEvalOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Inference",
              "(Tensor, default: Tensor<int64_t>). "

paddle/operators/clip_by_norm_op.cc

@@ -37,8 +37,7 @@ class ClipByNormOp : public framework::OperatorWithKernel {
 
 class ClipByNormOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ClipByNormOpMaker(framework::OpProto* proto,
-                    framework::OpAttrChecker* op_checker)
+  ClipByNormOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(Tensor) The input of clip_by_norm op."

paddle/operators/clip_op.cc

@@ -38,7 +38,7 @@ class ClipOp : public framework::OperatorWithKernel {
 template <typename AttrType>
 class ClipOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ClipOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
+  ClipOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(Tensor)The input of clip op."

paddle/operators/compare_op.cc

@@ -20,8 +20,7 @@ namespace operators {
 template <typename OpComment>
 class CompareOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  CompareOpProtoMaker(framework::OpProto *proto,
-                      framework::OpAttrChecker *op_checker)
+  CompareOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     OpComment comment;
     AddInput("X",

paddle/operators/concat_op.cc

@@ -58,7 +58,7 @@ class ConcatOp : public framework::OperatorWithKernel {
 
 class ConcatOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ConcatOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  ConcatOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "Input tensors of concat operator.").AsDuplicable();
     AddOutput("Out", "Output tensor of concat operator.");

paddle/operators/cond_op.cc

@@ -205,8 +205,7 @@ void CondOp::Run(const Scope& scope,
 
 class CondOpProtoAndCheckerMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  CondOpProtoAndCheckerMaker(framework::OpProto* proto,
-                             framework::OpAttrChecker* op_checker)
+  CondOpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Cond", "The condition, which is a bool vector");
     AddInput("Xs", "Inputs of Subnets").AsDuplicable();

paddle/operators/conditional_block_op.cc

@@ -74,8 +74,7 @@ class ConditionalBlockOp : public ConditionalOp {
 
 class ConditionalBlockOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ConditionalBlockOpProtoMaker(framework::OpProto *proto,
-                               framework::OpAttrChecker *op_checker)
+  ConditionalBlockOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "The conditional variable of this operator. If X is empty, the "

paddle/operators/conv_cudnn_op.cc

@@ -19,8 +19,7 @@ namespace operators {
 
 class CudnnConv2DOpMaker : public Conv2DOpMaker {
  public:
-  CudnnConv2DOpMaker(framework::OpProto* proto,
-                     framework::OpAttrChecker* op_checker)
+  CudnnConv2DOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : Conv2DOpMaker(proto, op_checker) {
     AddAttr<int>("workspace_size_MB",
                  "workspace size for cudnn, in MB, "
@@ -34,8 +33,7 @@ class CudnnConv2DOpMaker : public Conv2DOpMaker {
 
 class CudnnConv3DOpMaker : public Conv3DOpMaker {
  public:
-  CudnnConv3DOpMaker(framework::OpProto* proto,
-                     framework::OpAttrChecker* op_checker)
+  CudnnConv3DOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : Conv3DOpMaker(proto, op_checker) {
     AddAttr<int>("workspace_size_MB",
                  "workspace size for cudnn, in MB, "

paddle/operators/conv_op.cc

@@ -66,8 +66,7 @@ void ConvOp::InferShape(framework::InferShapeContext* ctx) const {
   ctx->SetOutputDim("Output", framework::make_ddim(output_shape));
 }
 
-Conv2DOpMaker::Conv2DOpMaker(framework::OpProto* proto,
-                             framework::OpAttrChecker* op_checker)
+Conv2DOpMaker::Conv2DOpMaker(OpProto* proto, OpAttrChecker* op_checker)
     : OpProtoAndCheckerMaker(proto, op_checker) {
   AddInput(
       "Input",
@@ -138,8 +137,7 @@ $$
 )DOC");
 }
 
-Conv3DOpMaker::Conv3DOpMaker(framework::OpProto* proto,
-                             framework::OpAttrChecker* op_checker)
+Conv3DOpMaker::Conv3DOpMaker(OpProto* proto, OpAttrChecker* op_checker)
     : OpProtoAndCheckerMaker(proto, op_checker) {
   AddInput(
       "Input",

paddle/operators/conv_op.h

@@ -50,14 +50,12 @@ inline bool IsExpand(std::vector<int64_t>& filter_dim,
 // operator implementations can reuse the code.
 class Conv2DOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  Conv2DOpMaker(framework::OpProto* proto,
-                framework::OpAttrChecker* op_checker);
+  Conv2DOpMaker(OpProto* proto, OpAttrChecker* op_checker);
 };
 
 class Conv3DOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  Conv3DOpMaker(framework::OpProto* proto,
-                framework::OpAttrChecker* op_checker);
+  Conv3DOpMaker(OpProto* proto, OpAttrChecker* op_checker);
 };
 
 class ConvOp : public framework::OperatorWithKernel {

paddle/operators/conv_shift_op.cc

@@ -75,8 +75,7 @@ class ConvShiftGradOp : public framework::OperatorWithKernel {
 
 class ConvShiftOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ConvShiftOpMaker(framework::OpProto *proto,
-                   framework::OpAttrChecker *op_checker)
+  ConvShiftOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(Tensor, default Tensor<float>), a 2-D tensor with shape B x M, "

paddle/operators/conv_transpose_cudnn_op.cc

@@ -19,8 +19,7 @@ namespace operators {
 
 class CudnnConv2DTransposeOpMaker : public Conv2DTransposeOpMaker {
  public:
-  CudnnConv2DTransposeOpMaker(framework::OpProto* proto,
-                              framework::OpAttrChecker* op_checker)
+  CudnnConv2DTransposeOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : Conv2DTransposeOpMaker(proto, op_checker) {
     AddAttr<std::vector<int>>("dilations", "dilations of convolution operator.")
         .SetDefault({1, 1});
@@ -36,8 +35,7 @@ class CudnnConv2DTransposeOpMaker : public Conv2DTransposeOpMaker {
 
 class CudnnConv3DTransposeOpMaker : public Conv3DTransposeOpMaker {
  public:
-  CudnnConv3DTransposeOpMaker(framework::OpProto* proto,
-                              framework::OpAttrChecker* op_checker)
+  CudnnConv3DTransposeOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : Conv3DTransposeOpMaker(proto, op_checker) {
     AddAttr<std::vector<int>>("dilations", "dilations of convolution operator.")
         .SetDefault({1, 1, 1});

paddle/operators/conv_transpose_op.cc

@@ -53,8 +53,8 @@ void ConvTransposeOp::InferShape(framework::InferShapeContext* ctx) const {
   ctx->SetOutputDim("Output", framework::make_ddim(output_shape));
 }
 
-Conv2DTransposeOpMaker::Conv2DTransposeOpMaker(
-    framework::OpProto* proto, framework::OpAttrChecker* op_checker)
+Conv2DTransposeOpMaker::Conv2DTransposeOpMaker(OpProto* proto,
+                                               OpAttrChecker* op_checker)
     : OpProtoAndCheckerMaker(proto, op_checker) {
   AddInput(
       "Input",
@@ -112,8 +112,8 @@ Example:
 )DOC");
 }
 
-Conv3DTransposeOpMaker::Conv3DTransposeOpMaker(
-    framework::OpProto* proto, framework::OpAttrChecker* op_checker)
+Conv3DTransposeOpMaker::Conv3DTransposeOpMaker(OpProto* proto,
+                                               OpAttrChecker* op_checker)
     : OpProtoAndCheckerMaker(proto, op_checker) {
   AddInput("Input",
            "(Tensor) The input tensor of convolution transpose operator."

paddle/operators/conv_transpose_op.h

@@ -30,14 +30,12 @@ using DDim = framework::DDim;
 // operator implementations can reuse the code.
 class Conv2DTransposeOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  Conv2DTransposeOpMaker(framework::OpProto* proto,
-                         framework::OpAttrChecker* op_checker);
+  Conv2DTransposeOpMaker(OpProto* proto, OpAttrChecker* op_checker);
 };
 
 class Conv3DTransposeOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  Conv3DTransposeOpMaker(framework::OpProto* proto,
-                         framework::OpAttrChecker* op_checker);
+  Conv3DTransposeOpMaker(OpProto* proto, OpAttrChecker* op_checker);
 };
 
 class ConvTransposeOp : public framework::OperatorWithKernel {

paddle/operators/cos_sim_op.cc

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

paddle/operators/crf_decoding_op.cc

@@ -18,8 +18,7 @@ namespace paddle {
 namespace operators {
 class CRFDecodingOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  CRFDecodingOpMaker(framework::OpProto* proto,
-                     framework::OpAttrChecker* op_checker)
+  CRFDecodingOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Emission",
              "(LoDTensor, default: LoDTensor<float>). A LoDTensor with shape "

paddle/operators/crop_op.cc

@@ -52,7 +52,7 @@ class CropOp : public framework::OperatorWithKernel {
 
 class CropOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  CropOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
+  CropOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "The input of pad op. "

paddle/operators/cross_entropy_op.cc

@@ -111,8 +111,7 @@ class CrossEntropyGradientOp : public framework::OperatorWithKernel {
 
 class CrossEntropyOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  CrossEntropyOpMaker(framework::OpProto* proto,
-                      framework::OpAttrChecker* op_checker)
+  CrossEntropyOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(Tensor, default Tensor<float>), a 2-D tensor with shape N x D, "

paddle/operators/decayed_adagrad_op.cc

@@ -55,8 +55,7 @@ class DecayedAdagradOp : public framework::OperatorWithKernel {
 
 class DecayedAdagradOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  DecayedAdagradOpMaker(framework::OpProto *proto,
-                        framework::OpAttrChecker *op_checker)
+  DecayedAdagradOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Param", "(Tensor) Input parameter");
     AddInput("Grad", "(Tensor) Input gradient");

paddle/operators/dropout_op.cc

@@ -40,8 +40,7 @@ class DropoutOp : public framework::OperatorWithKernel {
 template <typename AttrType>
 class DropoutOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  DropoutOpMaker(framework::OpProto* proto,
-                 framework::OpAttrChecker* op_checker)
+  DropoutOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "The input of dropout op.");
     AddOutput("Out", "The output of dropout op.");

paddle/operators/elementwise_add_op.cc

@@ -19,8 +19,7 @@ namespace paddle {
 namespace operators {
 class ElementwiseAddOpMaker : public ElementwiseOpMaker {
  public:
-  ElementwiseAddOpMaker(framework::OpProto* proto,
-                        framework::OpAttrChecker* op_checker)
+  ElementwiseAddOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : ElementwiseOpMaker(proto, op_checker) {
     SetComment("Add", "$Out = X + Y$");
     AddComment(comment_);

paddle/operators/elementwise_div_op.cc

@@ -19,8 +19,7 @@ namespace paddle {
 namespace operators {
 class ElementwiseDivOpMaker : public ElementwiseOpMaker {
  public:
-  ElementwiseDivOpMaker(framework::OpProto* proto,
-                        framework::OpAttrChecker* op_checker)
+  ElementwiseDivOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : ElementwiseOpMaker(proto, op_checker) {
     SetComment("Div", "$Out = X / Y$");
     AddComment(comment_);

paddle/operators/elementwise_mul_op.cc

@@ -20,8 +20,7 @@ namespace operators {
 
 class ElementwiseMulOpMaker : public ElementwiseOpMaker {
  public:
-  ElementwiseMulOpMaker(framework::OpProto* proto,
-                        framework::OpAttrChecker* op_checker)
+  ElementwiseMulOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : ElementwiseOpMaker(proto, op_checker) {
     SetComment("Mul", "$Out = X \\odot\\ Y$");
     AddComment(comment_);

paddle/operators/elementwise_op.h

@@ -43,8 +43,7 @@ class ElementwiseOp : public framework::OperatorWithKernel {
 
 class ElementwiseOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ElementwiseOpMaker(framework::OpProto* proto,
-                     framework::OpAttrChecker* op_checker)
+  ElementwiseOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "(Tensor) The first input tensor of elementwise op");
     AddInput("Y", "(Tensor) The second input tensor of elementwise op");

paddle/operators/elementwise_sub_op.cc

@@ -19,8 +19,7 @@ namespace paddle {
 namespace operators {
 class ElementwiseSubOpMaker : public ElementwiseOpMaker {
  public:
-  ElementwiseSubOpMaker(framework::OpProto* proto,
-                        framework::OpAttrChecker* op_checker)
+  ElementwiseSubOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : ElementwiseOpMaker(proto, op_checker) {
     SetComment("Sub", "$Out = X - Y$");
     AddComment(comment_);

paddle/operators/expand_op.cc

@@ -55,7 +55,7 @@ class ExpandOp : public framework::OperatorWithKernel {
 
 class ExpandOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ExpandOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
+  ExpandOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(Tensor, default Tensor<float>) A tensor with rank in [1, 6]."

paddle/operators/feed_op.cc

@@ -54,8 +54,7 @@ class FeedOp : public framework::OperatorBase {
 
 class FeedOpInfoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  FeedOpInfoMaker(framework::OpProto *proto,
-                  framework::OpAttrChecker *op_checker)
+  FeedOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "The input of feed op");
     AddOutput("Out", "The output of feed op");

paddle/operators/fetch_op.cc

@@ -61,8 +61,7 @@ class FetchOp : public framework::OperatorBase {
 
 class FetchOpInfoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  FetchOpInfoMaker(framework::OpProto *proto,
-                   framework::OpAttrChecker *op_checker)
+  FetchOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "The input of fetch op");
     AddOutput("Out", "The output of fetch op");

paddle/operators/fill_constant_batch_size_like_op.cc

@@ -52,7 +52,7 @@ class FillConstantBatchSizeLikeOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelType(
       const framework::ExecutionContext &ctx) const override {
     return framework::OpKernelType(
-        static_cast<framework::DataType>(ctx.Attr<int>("dtype")),
+        static_cast<framework::proto::DataType>(ctx.Attr<int>("dtype")),
         ctx.device_context());
   }
 };
@@ -60,13 +60,12 @@ class FillConstantBatchSizeLikeOp : public framework::OperatorWithKernel {
 class FillConstantBatchSizeLikeOpMaker
     : public framework::OpProtoAndCheckerMaker {
  public:
-  FillConstantBatchSizeLikeOpMaker(framework::OpProto *proto,
-                                   framework::OpAttrChecker *op_checker)
+  FillConstantBatchSizeLikeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddAttr<int>("dtype",
                  "(int, default 5 (FP32)) "
                  "Output data type")
-        .SetDefault(framework::DataType::FP32);
+        .SetDefault(framework::proto::DataType::FP32);
     AddInput("Input",
              "(Tensor) Tensor "
              "whose dim_idx th dimension is used to specify the batch_size");

paddle/operators/fill_constant_op.cc

@@ -34,7 +34,8 @@ class FillConstantOp : public framework::OperatorBase {
   using framework::OperatorBase::OperatorBase;
   void Run(const framework::Scope &scope,
            const platform::DeviceContext &dev_ctx) const override {
-    auto data_type = static_cast<framework::DataType>(Attr<int>("dtype"));
+    auto data_type =
+        static_cast<framework::proto::DataType>(Attr<int>("dtype"));
     auto value = Attr<float>("value");
     auto force_cpu = Attr<bool>("force_cpu");
     auto &out =
@@ -52,13 +53,12 @@ class FillConstantOp : public framework::OperatorBase {
 
 class FillConstantOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  FillConstantOpMaker(framework::OpProto *proto,
-                      framework::OpAttrChecker *op_checker)
+  FillConstantOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddAttr<int>("dtype",
                  "(int, default 5 (FP32)) "
                  "Output data type")
-        .SetDefault(framework::DataType::FP32);
+        .SetDefault(framework::proto::DataType::FP32);
     AddAttr<std::vector<int>>("shape", "(vector<int>) The shape of the output");
     AddAttr<float>("value", "(float, default 0) The value to be filled")
         .SetDefault(0.0f);

paddle/operators/fill_op.cc

@@ -48,7 +48,7 @@ class FillOp : public framework::OperatorBase {
                                 "Cannot find variable %s", Output("Out"))
                         .GetMutable<framework::LoDTensor>());
     out.Resize(framework::make_ddim(Attr<std::vector<int>>("shape")));
-    auto dtype = static_cast<framework::DataType>(Attr<int>("dtype"));
+    auto dtype = static_cast<framework::proto::DataType>(Attr<int>("dtype"));
     platform::CPUPlace cpu;
     auto force_cpu = Attr<bool>("force_cpu");
     out.mutable_data(force_cpu ? cpu : dev_ctx.GetPlace(),
@@ -76,7 +76,7 @@ class FillOp : public framework::OperatorBase {
 
 class FillOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  FillOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  FillOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddComment(R"DOC(Fill operator
 
@@ -88,7 +88,7 @@ Fill an tensor with `value` and `shape`. The type of the tensor is specify by
         "value", "The float values of tensor, which are flatten in row major");
     AddAttr<std::vector<int>>("shape", "The shape of output tensor");
     AddAttr<int>("dtype", "The data type of output tensor, Default is float")
-        .SetDefault(framework::DataType::FP32);
+        .SetDefault(framework::proto::DataType::FP32);
     AddAttr<bool>("force_cpu",
                   "Whether the output tensor must be at CPU memory or not. "
                   "Default is false.")

paddle/operators/fill_zeros_like_op.cc

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

paddle/operators/ftrl_op.cc

@@ -57,7 +57,7 @@ class FTRLOp : public framework::OperatorWithKernel {
 
 class FTRLOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  FTRLOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  FTRLOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Param",
              "(Tensor, default Tensor<float>) "

paddle/operators/gather_op.cc

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

paddle/operators/gaussian_random_op.cc

@@ -60,15 +60,14 @@ class GaussianRandomOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelType(
       const framework::ExecutionContext& ctx) const override {
     return framework::OpKernelType(
-        static_cast<framework::DataType>(ctx.Attr<int>("dtype")),
+        static_cast<framework::proto::DataType>(ctx.Attr<int>("dtype")),
         ctx.device_context());
   }
 };
 
 class GaussianRandomOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  GaussianRandomOpMaker(framework::OpProto* proto,
-                        framework::OpAttrChecker* op_checker)
+  GaussianRandomOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddOutput("Out", "Output matrix of gaussian random op");
 
@@ -91,7 +90,7 @@ class GaussianRandomOpMaker : public framework::OpProtoAndCheckerMaker {
     AddAttr<int>("dtype",
                  "(int, default 5(FP32)) "
                  "Output data type.")
-        .SetDefault(framework::DataType::FP32);
+        .SetDefault(framework::proto::DataType::FP32);
 
     AddComment(R"DOC(
 GaussianRandom Operator.

paddle/operators/gru_op.cc

@@ -67,7 +67,7 @@ class GRUOp : public framework::OperatorWithKernel {
 
 class GRUOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  GRUOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
+  GRUOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Input",
              "(LoDTensor) The first input is a LodTensor, which supports "

paddle/operators/gru_unit_op.cc

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

paddle/operators/hinge_loss_op.cc

@@ -46,8 +46,7 @@ class HingeLossOp : public framework::OperatorWithKernel {
 template <typename AttrType>
 class HingeLossOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  HingeLossOpMaker(framework::OpProto* proto,
-                   framework::OpAttrChecker* op_checker)
+  HingeLossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Logits",
              "The input value (Logits) of Hinge loss op."

paddle/operators/huber_loss_op.cc

@@ -45,8 +45,7 @@ class HuberLossOp : public framework::OperatorWithKernel {
 template <typename AttrType>
 class HuberLossOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  HuberLossOpMaker(framework::OpProto* proto,
-                   framework::OpAttrChecker* op_checker)
+  HuberLossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "The input value of huber loss op."

paddle/operators/increment_op.cc

@@ -70,8 +70,7 @@ class IncrementOp : public framework::OperatorBase {
 
 class IncrementOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  IncrementOpMaker(framework::OpProto *proto,
-                   framework::OpAttrChecker *op_checker)
+  IncrementOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "(Tensor) The input tensor of increment operator");
     AddOutput("Out", "(Tensor) The output tensor of increment operator.");

paddle/operators/is_empty_op.cc

@@ -47,8 +47,7 @@ class IsEmptyOp : public framework::OperatorBase {
 
 class IsEmptyOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  IsEmptyOpProtoMaker(framework::OpProto *proto,
-                      framework::OpAttrChecker *op_checker)
+  IsEmptyOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput(kInput, "(Tensor) Tensor which is to be checked.");
     AddOutput(kOutput, "(Tensor) a boolean Tensor that indicate empty or not.");

paddle/operators/l1_norm_op.cc

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

paddle/operators/linear_chain_crf_op.cc

@@ -19,8 +19,7 @@ namespace operators {
 
 class LinearChainCRFOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LinearChainCRFOpMaker(framework::OpProto* proto,
-                        framework::OpAttrChecker* op_checker)
+  LinearChainCRFOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Emission",
              "(LoDTensor, default LoDTensor<float>) "

paddle/operators/load_op.cc

@@ -58,8 +58,7 @@ class LoadOp : public framework::OperatorBase {
 
 class LoadOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LoadOpProtoMaker(framework::OpProto *proto,
-                   framework::OpAttrChecker *op_checker)
+  LoadOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddOutput("Out", "(Tensor) The tensor need to be loaded");
     AddAttr<std::string>("file_path",

paddle/operators/lod_array_length_op.cc

@@ -38,8 +38,7 @@ class LoDArrayLengthOp : public framework::OperatorBase {
 
 class LoDArrayLengthProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LoDArrayLengthProtoMaker(framework::OpProto *proto,
-                           framework::OpAttrChecker *op_checker)
+  LoDArrayLengthProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "(LoDTensorArray) The input tensor array.");
     AddOutput("Out", "(Tensor) 1x1 CPU Tensor of length, int64_t");

paddle/operators/lod_rank_table_op.cc

@@ -35,8 +35,7 @@ class LoDRankTableOp : public framework::OperatorBase {
 
 class LoDRankTableOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LoDRankTableOpProtoMaker(framework::OpProto *proto,
-                           framework::OpAttrChecker *op_checker)
+  LoDRankTableOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(LoDTensor) input lod tensor, must contain lod information.");
@@ -67,7 +66,7 @@ class LoDRankTableInferVarType : public framework::VarTypeInference {
                   framework::BlockDescBind *block) const override {
     for (auto &o : op_desc.Output("Out")) {
       block->FindRecursiveOrCreateVar(o)->SetType(
-          framework::VarDesc::LOD_RANK_TABLE);
+          framework::proto::VarDesc::LOD_RANK_TABLE);
     }
   }
 };

paddle/operators/lod_reset_op.cc

@@ -48,8 +48,7 @@ class LoDResetOp : public framework::OperatorWithKernel {
 
 class LoDResetOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LoDResetOpMaker(framework::OpProto *proto,
-                  framework::OpAttrChecker *op_checker)
+  LoDResetOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "(LoDTensor) The input tensor of lod_reset operator.");
     AddInput("TargetLoD",

paddle/operators/lod_tensor_to_array_op.cc

@@ -97,8 +97,7 @@ class LoDTensorToArrayOp : public framework::OperatorBase {
 
 class LoDTensorToArrayOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LoDTensorToArrayOpProtoMaker(framework::OpProto *proto,
-                               framework::OpAttrChecker *op_checker)
+  LoDTensorToArrayOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "");
     AddInput("RankTable", "");
@@ -131,7 +130,7 @@ class LoDTensorToArrayInferVarType : public framework::VarTypeInference {
   void operator()(const framework::OpDescBind &op_desc,
                   framework::BlockDescBind *block) const override {
     for (auto &out_var : op_desc.Output("Out")) {
-      block->Var(out_var)->SetType(framework::VarDesc::LOD_TENSOR_ARRAY);
+      block->Var(out_var)->SetType(framework::proto::VarDesc::LOD_TENSOR_ARRAY);
     }
   }
 };

paddle/operators/log_loss_op.cc

@@ -46,8 +46,7 @@ class LogLossOp : public framework::OperatorWithKernel {
 template <typename AttrType>
 class LogLossOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LogLossOpMaker(framework::OpProto* proto,
-                 framework::OpAttrChecker* op_checker)
+  LogLossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Predicted",
              "The input value (Predicted) of Log loss op."

paddle/operators/logical_op.cc

@@ -20,8 +20,7 @@ namespace operators {
 template <typename OpComment>
 class BinaryLogicalOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  BinaryLogicalOpProtoMaker(framework::OpProto *proto,
-                            framework::OpAttrChecker *op_checker)
+  BinaryLogicalOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     OpComment comment;
     AddInput("X",
@@ -45,8 +44,7 @@ Each element of Out is calculated by %s
 template <typename OpComment>
 class UnaryLogicalOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  UnaryLogicalOpProtoMaker(framework::OpProto *proto,
-                           framework::OpAttrChecker *op_checker)
+  UnaryLogicalOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     OpComment comment;
     AddInput("X", string::Sprintf("(LoDTensor) Operand of %s operator",

paddle/operators/lookup_table_op.cc

@@ -51,8 +51,7 @@ class LookupTableOp : public framework::OperatorWithKernel {
 
 class LookupTableOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LookupTableOpMaker(framework::OpProto* proto,
-                     framework::OpAttrChecker* op_checker)
+  LookupTableOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("W",
              "An input represents embedding tensors, "
@@ -117,11 +116,12 @@ class LookupTableOpGradVarTypeInference : public framework::VarTypeInference {
     if (is_sparse) {
       VLOG(3) << "lookup_table_grad op " << framework::GradVarName("W")
               << " is set to SelectedRows";
-      block->Var(out_var_name)->SetType(framework::VarDesc::SELECTED_ROWS);
+      block->Var(out_var_name)
+          ->SetType(framework::proto::VarDesc::SELECTED_ROWS);
     } else {
       VLOG(3) << "lookup_table_grad op " << framework::GradVarName("W")
               << " is set to LoDTensor";
-      block->Var(out_var_name)->SetType(framework::VarDesc::LOD_TENSOR);
+      block->Var(out_var_name)->SetType(framework::proto::VarDesc::LOD_TENSOR);
     }
   }
 };

paddle/operators/lrn_op.cc

@@ -140,7 +140,7 @@ class LRNOp : public framework::OperatorWithKernel {
 template <typename T>
 class LRNOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LRNOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
+  LRNOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(Tensor) The input of LRN operator. "

paddle/operators/lstm_op.cc

@@ -102,7 +102,7 @@ class LSTMOp : public framework::OperatorWithKernel {
 
 class LSTMOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LSTMOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
+  LSTMOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Input",
              "(LoDTensor) the first input is a LodTensor, which support "

paddle/operators/lstm_unit_op.cc

@@ -48,8 +48,7 @@ class LstmUnitOp : public framework::OperatorWithKernel {
 
 class LstmUnitOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  LstmUnitOpMaker(framework::OpProto* proto,
-                  framework::OpAttrChecker* op_checker)
+  LstmUnitOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "Lstm unit only applies non-linear activations, please make sure"

paddle/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(framework::OpProto *proto,
-                        framework::OpAttrChecker *op_checker)
+  MarginRankLossOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X1",
              "(2-D tensor with shape [batch_size x 1]) The score for "

paddle/operators/matmul_op.cc

@@ -130,7 +130,7 @@ class MatMulOp : public framework::OperatorWithKernel {
 
 class MatMulOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MatMulOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
+  MatMulOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "The first input of MatMul op");
     AddInput("Y", "The second input of MatMul op");

paddle/operators/max_sequence_len_op.cc

@@ -40,8 +40,7 @@ class MaxSeqenceLenOp : public framework::OperatorBase {
 
 class MaxSeqenceLenOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MaxSeqenceLenOpProtoMaker(framework::OpProto *proto,
-                            framework::OpAttrChecker *op_checker)
+  MaxSeqenceLenOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("RankTable", "The lod_rank_table.");
     AddOutput("Out", "The max sequence length.");

paddle/operators/maxout_op.cc

@@ -20,7 +20,7 @@ using framework::Tensor;
 
 class MaxOutOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MaxOutOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
+  MaxOutOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput(
         "X",

paddle/operators/mean_op.cc

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

paddle/operators/merge_lod_tensor_op.cc

@@ -114,8 +114,7 @@ class MergeLoDTensorOp : public framework::OperatorBase {
 
 class MergeLoDTensorOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MergeLoDTensorOpProtoMaker(framework::OpProto *proto,
-                             framework::OpAttrChecker *op_checker)
+  MergeLoDTensorOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "The input LoDTensor, contains complete lod information to "

paddle/operators/minus_op.cc

@@ -46,7 +46,7 @@ class MinusOp : public framework::OperatorWithKernel {
 
 class MinusOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MinusOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  MinusOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "The left tensor of minus operator.");
     AddInput("Y", "The right tensor of minus operator.");

paddle/operators/modified_huber_loss_op.cc

@@ -39,8 +39,7 @@ class ModifiedHuberLossOp : public framework::OperatorWithKernel {
 
 class ModifiedHuberLossOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ModifiedHuberLossOpMaker(framework::OpProto* proto,
-                           framework::OpAttrChecker* op_checker)
+  ModifiedHuberLossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "The input tensor of modified huber loss op. "

paddle/operators/momentum_op.cc

@@ -54,8 +54,7 @@ class MomentumOp : public framework::OperatorWithKernel {
 
 class MomentumOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MomentumOpMaker(framework::OpProto *proto,
-                  framework::OpAttrChecker *op_checker)
+  MomentumOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Param",
              "(Tensor, default Tensor<float>) "

paddle/operators/mul_op.cc

@@ -71,7 +71,7 @@ class MulOpShapeInference : public framework::InferShapeBase {
 
 class MulOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MulOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
+  MulOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "The first input of mul op");
     AddInput("Y", "The second input of mul op");

paddle/operators/multiplex_op.cc

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

paddle/operators/name_convention.md

@@ -35,8 +35,8 @@ Here we give some examples to show how these rules will be used.
 ```c++
 class AccumulateOpMaker : public framework::OpProtoAndCheckerMaker {
 public:
-  AccumulateOpMaker(framework::OpProto *proto,
-                            framework::OpAttrChecker *op_checker)
+  AccumulateOpMaker(OpProto *proto,
+                    OpAttrChecker *op_checker)
     : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "(Tensor) The input tensor that has to be accumulated to the output tensor.
     If the output size is not the same as input size,

paddle/operators/nccl_op.cc

@@ -43,8 +43,7 @@ class NCCLInitOp : public framework::OperatorBase {
 
 class NCCLInitOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  NCCLInitOpMaker(framework::OpProto *proto,
-                  framework::OpAttrChecker *op_checker)
+  NCCLInitOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddOutput("Communicator",
               "Create Communicator for communicating between gpus");
@@ -52,7 +51,7 @@ class NCCLInitOpMaker : public framework::OpProtoAndCheckerMaker {
     AddAttr<int>("dtype",
                  "(int, default 5 (FP32)) "
                  "Output data type")
-        .SetDefault(framework::DataType::FP32);
+        .SetDefault(framework::proto::DataType::FP32);
     AddComment(R"DOC(
 NCCLInit Operator.
 
@@ -141,8 +140,7 @@ class NCCLBcastOp : public framework::OperatorWithKernel {
 // AllreduceOp
 class NCCLAllReduceOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  NCCLAllReduceOpMaker(framework::OpProto *proto,
-                       framework::OpAttrChecker *op_checker)
+  NCCLAllReduceOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "The input of AllReduce op");
     AddInput("Communicator", "Communicator for communicating between gpus");
@@ -163,8 +161,7 @@ AllReduce the input tensors.
 // ReduceOp
 class NCCLReduceOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  NCCLReduceOpMaker(framework::OpProto *proto,
-                    framework::OpAttrChecker *op_checker)
+  NCCLReduceOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "The input of Reduce op");
     AddInput("Communicator", "Communicator for communicating between gpus");
@@ -190,8 +187,7 @@ Reduce the tensors.
 // BcastOp
 class NCCLBcastOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  NCCLBcastOpMaker(framework::OpProto *proto,
-                   framework::OpAttrChecker *op_checker)
+  NCCLBcastOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "The input of BcastSend op");
     AddInput("Communicator", "Communicator for communicating between gpus");

paddle/operators/nce_op.cc

@@ -73,7 +73,7 @@ class NCEOp : public framework::OperatorWithKernel {
 
 class NCEOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  NCEOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
+  NCEOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Input", "(Tensor) A tensor of shape [batch_size, dim].");
     AddInput(

paddle/operators/pad_op.cc

@@ -48,7 +48,7 @@ class PadOp : public framework::OperatorWithKernel {
 
 class PadOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  PadOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
+  PadOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "The input of pad op. "

paddle/operators/pool_op.cc

@@ -67,8 +67,7 @@ void PoolOpGrad::InferShape(framework::InferShapeContext *ctx) const {
   ctx->SetOutputDim(framework::GradVarName("X"), ctx->GetInputDim("X"));
 }
 
-Pool2dOpMaker::Pool2dOpMaker(framework::OpProto *proto,
-                             framework::OpAttrChecker *op_checker)
+Pool2dOpMaker::Pool2dOpMaker(OpProto *proto, OpAttrChecker *op_checker)
     : OpProtoAndCheckerMaker(proto, op_checker) {
   AddInput(
       "X",
@@ -136,8 +135,7 @@ Example:
 )DOC");
 }
 
-Pool3dOpMaker::Pool3dOpMaker(framework::OpProto *proto,
-                             framework::OpAttrChecker *op_checker)
+Pool3dOpMaker::Pool3dOpMaker(OpProto *proto, OpAttrChecker *op_checker)
     : OpProtoAndCheckerMaker(proto, op_checker) {
   AddInput("X",
            "(Tensor) The input tensor of pooling operator. "

paddle/operators/pool_op.h

@@ -40,14 +40,12 @@ class PoolOpGrad : public framework::OperatorWithKernel {
 
 class Pool2dOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  Pool2dOpMaker(framework::OpProto* proto,
-                framework::OpAttrChecker* op_checker);
+  Pool2dOpMaker(OpProto* proto, OpAttrChecker* op_checker);
 };
 
 class Pool3dOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  Pool3dOpMaker(framework::OpProto* proto,
-                framework::OpAttrChecker* op_checker);
+  Pool3dOpMaker(OpProto* proto, OpAttrChecker* op_checker);
 };
 
 template <typename DeviceContext, typename T>

paddle/operators/pool_with_index_op.cc

@@ -100,8 +100,7 @@ class MaxPoolWithIndexOpGrad : public framework::OperatorWithKernel {
 
 class MaxPool2dWithIndexOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MaxPool2dWithIndexOpMaker(framework::OpProto *proto,
-                            framework::OpAttrChecker *op_checker)
+  MaxPool2dWithIndexOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput(
         "X",
@@ -178,8 +177,7 @@ Example:
 
 class MaxPool3dWithIndexOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  MaxPool3dWithIndexOpMaker(framework::OpProto *proto,
-                            framework::OpAttrChecker *op_checker)
+  MaxPool3dWithIndexOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(Tensor) The input tensor of pooling operator. "

paddle/operators/positive_negative_pair_op.cc

@@ -95,8 +95,7 @@ class PositiveNegativePairOp : public framework::OperatorWithKernel {
 
 class PositiveNegativePairOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  PositiveNegativePairOpMaker(framework::OpProto *proto,
-                              framework::OpAttrChecker *op_checker)
+  PositiveNegativePairOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Score",
              "(Tensor, float) Model Score on an item (with "

paddle/operators/precision_recall_op.cc

@@ -90,8 +90,7 @@ class PrecisionRecallOp : public framework::OperatorWithKernel {
 
 class PrecisionRecallOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  PrecisionRecallOpMaker(framework::OpProto *proto,
-                         framework::OpAttrChecker *op_checker)
+  PrecisionRecallOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("MaxProbs",
              "(Tensor, default Tensor<float>) A 2-D tensor with shape N x 1, "

paddle/operators/prelu_op.cc

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

paddle/operators/proximal_adagrad_op.cc

@@ -59,8 +59,7 @@ class ProximalAdagradOp : public framework::OperatorWithKernel {
 
 class ProximalAdagradOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ProximalAdagradOpMaker(framework::OpProto *proto,
-                         framework::OpAttrChecker *op_checker)
+  ProximalAdagradOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Param",
              "(Tensor, default Tensor<float>) "

paddle/operators/proximal_gd_op.cc

@@ -47,8 +47,7 @@ class ProximalGDOp : public framework::OperatorWithKernel {
 
 class ProximalGDOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ProximalGDOpMaker(framework::OpProto *proto,
-                    framework::OpAttrChecker *op_checker)
+  ProximalGDOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Param",
              "(Tensor, default Tensor<float>) "

paddle/operators/rank_loss_op.cc

@@ -45,8 +45,7 @@ class RankLossOp : public framework::OperatorWithKernel {
 
 class RankLossOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  RankLossOpMaker(framework::OpProto *proto,
-                  framework::OpAttrChecker *op_checker)
+  RankLossOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Label",
              "(2-D Tensor with shape [batch_size x 1]) "

paddle/operators/recurrent_op.cc

@@ -497,8 +497,7 @@ class RecurrentGradOp : public RecurrentBase {
 
 class RecurrentOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  RecurrentOpProtoMaker(framework::OpProto *proto,
-                        framework::OpAttrChecker *op_checker)
+  RecurrentOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput(kInputs, "rnn inputs").AsDuplicable();
     AddInput(kInitialStates, "rnn initial states").AsDuplicable();

paddle/operators/recv_op.cc

@@ -97,7 +97,7 @@ class RecvOp : public framework::OperatorBase {
 
 class RecvOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  RecvOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  RecvOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("RX", "(Tensor) Input tensor to be saved");
     AddComment(R"DOC(

paddle/operators/reduce_op.cc

@@ -83,7 +83,7 @@ class ReduceGradOp : public framework::OperatorWithKernel {
 
 class ReduceOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ReduceOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  ReduceOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(Tensor) The input tensor. Tensors with rank at most 6 are "
@@ -135,8 +135,7 @@ If reduce_all is true, just reduce along all dimensions and output a scalar.
 
 class ReduceSumOpMaker : public ReduceOpMaker {
  public:
-  ReduceSumOpMaker(framework::OpProto *proto,
-                   framework::OpAttrChecker *op_checker)
+  ReduceSumOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : ReduceOpMaker(proto, op_checker) {
     SetComment("ReduceSum", "sum");
     AddComment(comment_);
@@ -145,8 +144,7 @@ class ReduceSumOpMaker : public ReduceOpMaker {
 
 class ReduceMeanOpMaker : public ReduceOpMaker {
  public:
-  ReduceMeanOpMaker(framework::OpProto *proto,
-                    framework::OpAttrChecker *op_checker)
+  ReduceMeanOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : ReduceOpMaker(proto, op_checker) {
     SetComment("ReduceMean", "mean");
     AddComment(comment_);
@@ -155,8 +153,7 @@ class ReduceMeanOpMaker : public ReduceOpMaker {
 
 class ReduceMaxOpMaker : public ReduceOpMaker {
  public:
-  ReduceMaxOpMaker(framework::OpProto *proto,
-                   framework::OpAttrChecker *op_checker)
+  ReduceMaxOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : ReduceOpMaker(proto, op_checker) {
     SetComment("ReduceMax", "max");
     AddComment(comment_);
@@ -165,8 +162,7 @@ class ReduceMaxOpMaker : public ReduceOpMaker {
 
 class ReduceMinOpMaker : public ReduceOpMaker {
  public:
-  ReduceMinOpMaker(framework::OpProto *proto,
-                   framework::OpAttrChecker *op_checker)
+  ReduceMinOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : ReduceOpMaker(proto, op_checker) {
     SetComment("ReduceMin", "min");
     AddComment(comment_);

paddle/operators/reshape_op.cc

@@ -77,8 +77,7 @@ class ReshapeOp : public framework::OperatorWithKernel {
 
 class ReshapeOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ReshapeOpMaker(framework::OpProto *proto,
-                 framework::OpAttrChecker *op_checker)
+  ReshapeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "The input tensor of reshape operator.");
     AddOutput("Out", "The output tensor of reshape operator.");

paddle/operators/rmsprop_op.cc

@@ -63,8 +63,7 @@ class RmspropOp : public framework::OperatorWithKernel {
 
 class RmspropOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  RmspropOpMaker(framework::OpProto *proto,
-                 framework::OpAttrChecker *op_checker)
+  RmspropOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Param",
              "(Tensor, default Tensor<float>) "

paddle/operators/rnn_memory_helper_op.cc

@@ -57,15 +57,14 @@ class RNNMemoryHelperOpShapeInference : public framework::InferShapeBase {
 
 class RNNMemoryHelperOpInfoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  RNNMemoryHelperOpInfoMaker(framework::OpProto *proto,
-                             framework::OpAttrChecker *op_checker)
+  RNNMemoryHelperOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "");
     AddOutput("Out", "");
     AddAttr<int>("dtype",
                  "(int, default 5 (FP32)) "
                  "Output data type")
-        .SetDefault(framework::DataType::FP32);
+        .SetDefault(framework::proto::DataType::FP32);
     AddComment("");
   }
 };
@@ -114,8 +113,7 @@ class RNNMemoryHelperGradOp : public framework::OperatorBase {
 class RNNMemoryHelperGradOpInfoMaker
     : public framework::OpProtoAndCheckerMaker {
  public:
-  RNNMemoryHelperGradOpInfoMaker(framework::OpProto *proto,
-                                 framework::OpAttrChecker *op_checker)
+  RNNMemoryHelperGradOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput(framework::GradVarName("Out"), "");
     AddInput("X", "");
@@ -124,7 +122,7 @@ class RNNMemoryHelperGradOpInfoMaker
     AddAttr<int>("dtype",
                  "(int, default 5 (FP32)) "
                  "Output data type")
-        .SetDefault(framework::DataType::FP32);
+        .SetDefault(framework::proto::DataType::FP32);
     AddComment("");
   }
 };

paddle/operators/roi_pool_op.cc

@@ -99,8 +99,7 @@ class ROIPoolGradOp : public framework::OperatorWithKernel {
 
 class ROIPoolOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ROIPoolOpMaker(framework::OpProto* proto,
-                 framework::OpAttrChecker* op_checker)
+  ROIPoolOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(Tensor), "

paddle/operators/row_conv_op.cc

@@ -76,8 +76,7 @@ class RowConvGradOp : public framework::OperatorWithKernel {
 
 class RowConvOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  RowConvOpMaker(framework::OpProto *proto,
-                 framework::OpAttrChecker *op_checker)
+  RowConvOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(LoDTensor), the input(X) is a LodTensor, which supports "

paddle/operators/save_op.cc

@@ -94,8 +94,7 @@ class SaveOp : public framework::OperatorBase {
 
 class SaveOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SaveOpProtoMaker(framework::OpProto *proto,
-                   framework::OpAttrChecker *op_checker)
+  SaveOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "(Tensor ) Input tensor to be saved");
     AddComment(R"DOC(

paddle/operators/scale_op.cc

@@ -38,7 +38,7 @@ class ScaleOp : public framework::OperatorWithKernel {
 template <typename AttrType>
 class ScaleOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ScaleOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  ScaleOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "(Tensor) Input tensor of scale operator.");
     AddOutput("Out", "(Tensor) Output tensor of scale operator.");

paddle/operators/scatter_op.cc

@@ -78,8 +78,7 @@ class ScatterGradOp : public framework::OperatorWithKernel {
 
 class ScatterOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ScatterOpMaker(framework::OpProto* proto,
-                 framework::OpAttrChecker* op_checker)
+  ScatterOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Ref", "The source input of scatter op");
     AddInput("Index",

paddle/operators/send_op.cc

@@ -59,7 +59,7 @@ class SendOp : public framework::OperatorBase {
 
 class SendOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SendOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  SendOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "(Tensor) Input tensor to be saved");
     AddOutput("Out", "(Tensor) Output fetched from server");

paddle/operators/sequence_concat_op.cc

@@ -43,8 +43,7 @@ class SequenceConcatOp : public framework::OperatorWithKernel {
 
 class SequenceConcatOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SequenceConcatOpMaker(framework::OpProto* proto,
-                        framework::OpAttrChecker* op_checker)
+  SequenceConcatOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(LodTensorArray) Input is a vector of LoDTensor, "

paddle/operators/sequence_conv_op.cc

@@ -100,8 +100,7 @@ class SequenceConvGradOp : public framework::OperatorWithKernel {
 
 class SequenceConvOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SequenceConvOpMaker(framework::OpProto* proto,
-                      framework::OpAttrChecker* op_checker)
+  SequenceConvOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput(
         "X",

paddle/operators/sequence_expand_op.cc

@@ -37,8 +37,7 @@ class SequenceExpandOp : public framework::OperatorWithKernel {
 
 class SequenceExpandOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SequenceExpandOpMaker(framework::OpProto* proto,
-                        framework::OpAttrChecker* op_checker)
+  SequenceExpandOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(Tensor or LoDTensor) The input(X) of this operator can be a "

paddle/operators/sequence_pool_op.cc

@@ -37,8 +37,7 @@ class SequencePoolOp : public framework::OperatorWithKernel {
 
 class SequencePoolOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SequencePoolOpMaker(framework::OpProto* proto,
-                      framework::OpAttrChecker* op_checker)
+  SequencePoolOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "(LoDTensor) The variable-length input of SequencePoolOp");
     AddOutput("Out",

paddle/operators/sequence_slice_op.cc

@@ -79,8 +79,7 @@ class SequenceSliceGradOp : public framework::OperatorWithKernel {
 
 class SequenceSliceOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SequenceSliceOpMaker(framework::OpProto* proto,
-                       framework::OpAttrChecker* op_checker)
+  SequenceSliceOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(LoDTensor), "

paddle/operators/sequence_softmax_op.cc

@@ -33,8 +33,7 @@ class SequenceSoftmaxOp : public framework::OperatorWithKernel {
 
 class SequenceSoftmaxOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SequenceSoftmaxOpMaker(framework::OpProto* proto,
-                         framework::OpAttrChecker* op_checker)
+  SequenceSoftmaxOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(LoDTensor) 1-D or 2-D input LoDTensor with the 2-nd dimension "

paddle/operators/sgd_op.cc

@@ -43,7 +43,7 @@ class SGDOp : public framework::OperatorWithKernel {
 
 class SGDOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SGDOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
+  SGDOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Param", "(Tensor) Input parameter");
     AddInput("LearningRate", "(Tensor) Learning rate of SGD");

paddle/operators/shrink_rnn_memory_op.cc

@@ -54,8 +54,7 @@ class ShrinkRNNMemoryOp : public ArrayOp {
 
 class ShrinkRNNMemoryOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ShrinkRNNMemoryOpProtoMaker(framework::OpProto *proto,
-                              framework::OpAttrChecker *op_checker)
+  ShrinkRNNMemoryOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "(LoDTensor) The RNN step memory to be shrinked.");
     AddInput("RankTable", "(LoDRankTable) The lod_rank_table of dynamic RNN.");

paddle/operators/sigmoid_cross_entropy_with_logits_op.cc

@@ -86,8 +86,8 @@ class SigmoidCrossEntropyWithLogitsGradOp
 class SigmoidCrossEntropyWithLogitsOpMaker
     : public framework::OpProtoAndCheckerMaker {
  public:
-  SigmoidCrossEntropyWithLogitsOpMaker(framework::OpProto* proto,
-                                       framework::OpAttrChecker* op_checker)
+  SigmoidCrossEntropyWithLogitsOpMaker(OpProto* proto,
+                                       OpAttrChecker* op_checker)
       : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(Tensor, default Tensor<float>), a 2-D tensor with shape N x D, "

paddle/operators/sign_op.cc

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

paddle/operators/smooth_l1_loss_op.cc

@@ -47,8 +47,7 @@ class SmoothL1LossOp : public framework::OperatorWithKernel {
 template <typename AttrType>
 class SmoothL1LossOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SmoothL1LossOpMaker(framework::OpProto* proto,
-                      framework::OpAttrChecker* op_checker)
+  SmoothL1LossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "(Tensor, default Tensor<float>) A tensor with rank at least 2. "

paddle/operators/softmax_op.cc

@@ -36,8 +36,7 @@ class SoftmaxOp : public framework::OperatorWithKernel {
 
 class SoftmaxOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SoftmaxOpMaker(framework::OpProto* proto,
-                 framework::OpAttrChecker* op_checker)
+  SoftmaxOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X",
              "The input tensor of softmax. "

paddle/operators/softmax_with_cross_entropy_op.cc

@@ -20,8 +20,7 @@ namespace operators {
 class SoftmaxWithCrossEntropyOpMaker
     : public framework::OpProtoAndCheckerMaker {
  public:
-  SoftmaxWithCrossEntropyOpMaker(framework::OpProto* proto,
-                                 framework::OpAttrChecker* op_checker)
+  SoftmaxWithCrossEntropyOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("Logits",
              "(Tensor, default: Tensor<float>), The unscaled log probabilities "

paddle/operators/split_lod_tensor_op.cc

@@ -118,8 +118,7 @@ class SplitLoDTensorOp : public framework::OperatorBase {
 
 class SplitLoDTensorOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SplitLoDTensorOpProtoMaker(framework::OpProto *proto,
-                             framework::OpAttrChecker *op_checker)
+  SplitLoDTensorOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "The input LoDTensor");
     AddInput("Mask", "A bool column vector which mask the input");

paddle/operators/split_op.cc

@@ -65,7 +65,7 @@ class SplitOp : public framework::OperatorWithKernel {
 
 class SplitOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SplitOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  SplitOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "(Tensor) Input tensor of the split operator.");
     AddOutput("Out", "(Tensor) Output tensors of the split operator.")

paddle/operators/spp_op.cc

@@ -18,7 +18,7 @@ namespace operators {
 
 class SppOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SppOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
+  SppOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput(
         "X",

paddle/operators/squared_l2_distance_op.cc

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

paddle/operators/squared_l2_norm_op.cc

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

paddle/operators/sum_op.cc

@@ -29,7 +29,7 @@ class SumOp : public framework::OperatorWithKernel {
                    "Output(Out) of SumOp should not be null.");
     if (ctx->IsRuntime() &&
         ctx->GetOutputsVarType("Out")[0] ==
-            framework::VarDesc::LOD_TENSOR_ARRAY) {
+            framework::proto::VarDesc::LOD_TENSOR_ARRAY) {
       return;  // skip runtime infershape when is tensor array;
     }
 
@@ -72,8 +72,8 @@ class SumOp : public framework::OperatorWithKernel {
       PADDLE_ENFORCE_NE(dtype, -1,
                         "Sum operator should have at least one tensor");
 
-      return framework::OpKernelType(static_cast<framework::DataType>(dtype),
-                                     ctx.device_context());
+      return framework::OpKernelType(
+          static_cast<framework::proto::DataType>(dtype), ctx.device_context());
     } else if (x_vars[0]->IsType<framework::SelectedRows>()) {
       return framework::OpKernelType(
           framework::ToDataType(
@@ -98,7 +98,7 @@ class SumOp : public framework::OperatorWithKernel {
 
 class SumOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  SumOpMaker(framework::OpProto* proto, framework::OpAttrChecker* op_checker)
+  SumOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "(vector<Tensor>) The input tensors of sum operator.")
         .AsDuplicable();
@@ -118,7 +118,7 @@ class SumOpVarTypeInference : public framework::VarTypeInference {
   void operator()(const framework::OpDescBind& op_desc,
                   framework::BlockDescBind* block) const override {
     auto& inputs = op_desc.Input("X");
-    auto var_type = framework::VarDesc::SELECTED_ROWS;
+    auto var_type = framework::proto::VarDesc::SELECTED_ROWS;
 
     for (auto& name : op_desc.Input("X")) {
       VLOG(10) << name << " "
@@ -128,12 +128,12 @@ class SumOpVarTypeInference : public framework::VarTypeInference {
     bool any_input_is_lod_tensor = std::any_of(
         inputs.begin(), inputs.end(), [block](const std::string& name) {
           return block->FindRecursiveOrCreateVar(name)->GetType() ==
-                 framework::VarDesc::LOD_TENSOR;
+                 framework::proto::VarDesc::LOD_TENSOR;
         });
 
     auto is_tensor_array = [block](const std::string& name) {
       return detail::Ref(block->FindRecursiveOrCreateVar(name)).GetType() ==
-             framework::VarDesc::LOD_TENSOR_ARRAY;
+             framework::proto::VarDesc::LOD_TENSOR_ARRAY;
     };
 
     bool any_input_is_tensor_array =
@@ -152,9 +152,9 @@ class SumOpVarTypeInference : public framework::VarTypeInference {
         PADDLE_ENFORCE(all_inputs_are_tensor_array,
                        "Not all inputs are tensor array:\n%s", os.str());
       }
-      var_type = framework::VarDesc::LOD_TENSOR_ARRAY;
+      var_type = framework::proto::VarDesc::LOD_TENSOR_ARRAY;
     } else if (any_input_is_lod_tensor) {
-      var_type = framework::VarDesc::LOD_TENSOR;
+      var_type = framework::proto::VarDesc::LOD_TENSOR;
     }
 
     auto out_var_name = op_desc.Output("Out").front();

paddle/operators/tensor_array_read_write_op.cc

@@ -51,8 +51,7 @@ class WriteToArrayOp : public ArrayOp {
 
 class WriteToArrayOpProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  WriteToArrayOpProtoMaker(framework::OpProto *proto,
-                           framework::OpAttrChecker *op_checker)
+  WriteToArrayOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "(LoDTensor) the tensor will be written to tensor array");
     AddInput(
@@ -104,7 +103,7 @@ class WriteToArrayInferVarType : public framework::VarTypeInference {
     VLOG(10) << "Set Variable " << out_name << " as LOD_TENSOR_ARRAY";
     auto &out = detail::Ref(block->FindRecursiveOrCreateVar(out_name),
                             "Cannot found %s", out_name);
-    out.SetType(framework::VarDesc::LOD_TENSOR_ARRAY);
+    out.SetType(framework::proto::VarDesc::LOD_TENSOR_ARRAY);
     auto *x = block->FindVarRecursive(x_name);
     if (x != nullptr) {
       out.SetDataType(x->GetDataType());
@@ -140,8 +139,7 @@ class ReadFromArrayOp : public ArrayOp {
 
 class ReadFromArrayProtoMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  ReadFromArrayProtoMaker(framework::OpProto *proto,
-                          framework::OpAttrChecker *op_checker)
+  ReadFromArrayProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "(TensorArray) the array will be read from.");
     AddInput("I",

paddle/operators/top_k_op.cc

@@ -46,7 +46,7 @@ class TopkOp : public framework::OperatorWithKernel {
 
 class TopkOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  TopkOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  TopkOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput("X", "(Tensor) The input of Topk op");
     AddOutput("Out", "(Tensor) The output tensor of Topk op");

paddle/operators/transpose_op.cc

@@ -55,8 +55,7 @@ class TransposeOp : public framework::OperatorWithKernel {
 
 class TransposeOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  TransposeOpMaker(framework::OpProto* proto,
-                   framework::OpAttrChecker* op_checker)
+  TransposeOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput(
         "X",

paddle/operators/uniform_random_op.cc

@@ -66,15 +66,14 @@ class UniformRandomOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetKernelType(
       const framework::ExecutionContext& ctx) const override {
     return framework::OpKernelType(
-        static_cast<framework::DataType>(ctx.Attr<int>("dtype")),
+        static_cast<framework::proto::DataType>(ctx.Attr<int>("dtype")),
         ctx.GetPlace());
   }
 };
 
 class UniformRandomOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  UniformRandomOpMaker(framework::OpProto* proto,
-                       framework::OpAttrChecker* op_checker)
+  UniformRandomOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : framework::OpProtoAndCheckerMaker(proto, op_checker) {
     AddOutput("Out", "(Tensor) The output tensor of uniform random op");
     AddComment(R"DOC(
@@ -100,7 +99,7 @@ uniform distribution.
                  "0 means use a seed generated by the system.")
         .SetDefault(0);
     AddAttr<int>("dtype", "(int, default 5(FP32)) Output tensor data type")
-        .SetDefault(framework::DataType::FP32);
+        .SetDefault(framework::proto::DataType::FP32);
   }
 };
 }  // namespace operators

paddle/operators/unpool_op.cc

@@ -18,8 +18,7 @@ namespace operators {
 
 class Unpool2dOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  Unpool2dOpMaker(framework::OpProto* proto,
-                  framework::OpAttrChecker* op_checker)
+  Unpool2dOpMaker(OpProto* proto, OpAttrChecker* op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput(
         "X",

paddle/operators/while_op.cc

@@ -64,7 +64,7 @@ class WhileOp : public framework::OperatorBase {
 
 class WhileOpMaker : public framework::OpProtoAndCheckerMaker {
  public:
-  WhileOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker)
+  WhileOpMaker(OpProto *proto, OpAttrChecker *op_checker)
       : OpProtoAndCheckerMaker(proto, op_checker) {
     AddInput(kParameters,
              "A set of variables, which are required by operators inside the "
@@ -321,10 +321,10 @@ class WhileGradOpShapeInference : public framework::InferShapeBase {
         continue;
       }
       auto dims = ctx->GetInputsElementDim(kParameters, i);
-      if (var_types[i] == framework::VarDesc::LOD_TENSOR) {
+      if (var_types[i] == framework::proto::VarDesc::LOD_TENSOR) {
         names_to_set.push_back(pg_names[i]);
         dims_to_set.push_back(dims);
-      } else if (var_types[i] == framework::VarDesc::LOD_TENSOR_ARRAY) {
+      } else if (var_types[i] == framework::proto::VarDesc::LOD_TENSOR_ARRAY) {
         // not sure how to set the dim of LOD_TENSOR_ARRAY
         names_to_set.push_back(pg_names[i]);
         dims_to_set.push_back(dims);

paddle/pybind/print_operators_doc.cc

@@ -31,31 +31,32 @@ std::string Escape(const std::string& s) {
   return r;
 }
 
-std::string AttrType(paddle::framework::AttrType at) {
+std::string AttrType(paddle::framework::proto::AttrType at) {
   switch (at) {
-    case paddle::framework::INT:
+    case paddle::framework::proto::INT:
       return "int";
-    case paddle::framework::FLOAT:
+    case paddle::framework::proto::FLOAT:
       return "float";
-    case paddle::framework::STRING:
+    case paddle::framework::proto::STRING:
       return "string";
-    case paddle::framework::BOOLEAN:
+    case paddle::framework::proto::BOOLEAN:
       return "bool";
-    case paddle::framework::INTS:
+    case paddle::framework::proto::INTS:
       return "int array";
-    case paddle::framework::FLOATS:
+    case paddle::framework::proto::FLOATS:
       return "float array";
-    case paddle::framework::STRINGS:
+    case paddle::framework::proto::STRINGS:
       return "string array";
-    case paddle::framework::BOOLEANS:
+    case paddle::framework::proto::BOOLEANS:
       return "bool array";
-    case paddle::framework::BLOCK:
+    case paddle::framework::proto::BLOCK:
       return "block id";
   }
   return "UNKNOWN";  // not possible
 }
 
-void PrintVar(const paddle::framework::OpProto::Var& v, std::stringstream& ss) {
+void PrintVar(const paddle::framework::proto::OpProto::Var& v,
+              std::stringstream& ss) {
   ss << " { "
      << "\n"
      << "   \"name\" : \"" << Escape(v.name()) << "\",\n"
@@ -65,7 +66,7 @@ void PrintVar(const paddle::framework::OpProto::Var& v, std::stringstream& ss) {
      << " },";
 }
 
-void PrintAttr(const paddle::framework::OpProto::Attr& a,
+void PrintAttr(const paddle::framework::proto::OpProto::Attr& a,
                std::stringstream& ss) {
   ss << " { "
      << "\n"
@@ -81,7 +82,7 @@ void PrintOpProto(const std::string& type,
                   std::stringstream& ss) {
   std::cerr << "Processing " << type << "\n";
 
-  const paddle::framework::OpProto* p = opinfo.proto_;
+  const paddle::framework::proto::OpProto* p = opinfo.proto_;
   if (p == nullptr) {
     return;  // It is possible that an operator doesn't have OpProto.
   }

paddle/pybind/protobuf.cc

@@ -144,7 +144,7 @@ void BindProgramDesc(py::module &m) {
       .def("serialize_to_string", SerializeMessage<ProgramDescBind>)
       .def("parse_from_string",
            [](ProgramDescBind &program_desc, const std::string &data) {
-             ProgramDesc *desc = program_desc.Proto();
+             proto::ProgramDesc *desc = program_desc.Proto();
              PADDLE_ENFORCE(desc->ParseFromString(data),
                             "Fail to parse ProgramDesc from string. This could "
                             "be a bug of Paddle.");
@@ -184,14 +184,14 @@ void BindBlockDesc(py::module &m) {
 }
 
 void BindVarDsec(py::module &m) {
-  py::enum_<DataType>(m, "DataType", "")
-      .value("BOOL", DataType::BOOL)
-      .value("INT16", DataType::INT16)
-      .value("INT32", DataType::INT32)
-      .value("INT64", DataType::INT64)
-      .value("FP16", DataType::FP16)
-      .value("FP32", DataType::FP32)
-      .value("FP64", DataType::FP64);
+  py::enum_<proto::DataType>(m, "DataType", "")
+      .value("BOOL", proto::DataType::BOOL)
+      .value("INT16", proto::DataType::INT16)
+      .value("INT32", proto::DataType::INT32)
+      .value("INT64", proto::DataType::INT64)
+      .value("FP16", proto::DataType::FP16)
+      .value("FP32", proto::DataType::FP32)
+      .value("FP64", proto::DataType::FP64);
 
   py::class_<VarDescBind> var_desc(m, "VarDesc", "");
   var_desc
@@ -213,27 +213,27 @@ void BindVarDsec(py::module &m) {
       .def("persistable", &VarDescBind::Persistable)
       .def("set_persistable", &VarDescBind::SetPersistable);
 
-  py::enum_<VarDesc::VarType>(var_desc, "VarType", "")
-      .value("LOD_TENSOR", VarDesc::LOD_TENSOR)
-      .value("SELECTED_ROWS", VarDesc::SELECTED_ROWS)
-      .value("FEED_MINIBATCH", VarDesc::FEED_MINIBATCH)
-      .value("FETCH_LIST", VarDesc::FETCH_LIST)
-      .value("STEP_SCOPES", VarDesc::STEP_SCOPES)
-      .value("LOD_RANK_TABLE", VarDesc::LOD_RANK_TABLE)
-      .value("LOD_TENSOR_ARRAY", VarDesc::LOD_TENSOR_ARRAY);
+  py::enum_<proto::VarDesc::VarType>(var_desc, "VarType", "")
+      .value("LOD_TENSOR", proto::VarDesc::LOD_TENSOR)
+      .value("SELECTED_ROWS", proto::VarDesc::SELECTED_ROWS)
+      .value("FEED_MINIBATCH", proto::VarDesc::FEED_MINIBATCH)
+      .value("FETCH_LIST", proto::VarDesc::FETCH_LIST)
+      .value("STEP_SCOPES", proto::VarDesc::STEP_SCOPES)
+      .value("LOD_RANK_TABLE", proto::VarDesc::LOD_RANK_TABLE)
+      .value("LOD_TENSOR_ARRAY", proto::VarDesc::LOD_TENSOR_ARRAY);
 }
 
 void BindOpDesc(py::module &m) {
-  py::enum_<AttrType>(m, "AttrType", "")
-      .value("INT", AttrType::INT)
-      .value("INTS", AttrType::INTS)
-      .value("FLOAT", AttrType::FLOAT)
-      .value("FLOATS", AttrType::FLOATS)
-      .value("STRING", AttrType::STRING)
-      .value("STRINGS", AttrType::STRINGS)
-      .value("BOOL", AttrType::BOOLEAN)
-      .value("BOOLS", AttrType::BOOLEANS)
-      .value("BLOCK", AttrType::BLOCK);
+  py::enum_<proto::AttrType>(m, "AttrType", "")
+      .value("INT", proto::AttrType::INT)
+      .value("INTS", proto::AttrType::INTS)
+      .value("FLOAT", proto::AttrType::FLOAT)
+      .value("FLOATS", proto::AttrType::FLOATS)
+      .value("STRING", proto::AttrType::STRING)
+      .value("STRINGS", proto::AttrType::STRINGS)
+      .value("BOOL", proto::AttrType::BOOLEAN)
+      .value("BOOLS", proto::AttrType::BOOLEANS)
+      .value("BLOCK", proto::AttrType::BLOCK);
 
   py::class_<OpDescBind> op_desc(m, "OpDesc", "");
   op_desc.def("type", &OpDescBind::Type)

paddle/pybind/pybind.cc

@@ -288,12 +288,12 @@ All parameter, weight, gradient are variables in Paddle.
     for (const auto &t : targets) {
       prog_with_targets.MutableBlock(t[0])->Op(t[1])->MarkAsTarget();
     }
-    ProgramDesc pruned_desc;
+    proto::ProgramDesc pruned_desc;
     Prune(*prog_with_targets.Proto(), &pruned_desc);
     return new ProgramDescBind(pruned_desc);
   });
   m.def("inference_optimize", [](ProgramDescBind &origin) {
-    ProgramDesc pruned_desc;
+    proto::ProgramDesc pruned_desc;
     InferenceOptimize(*(origin.Proto()), &pruned_desc);
     return new ProgramDescBind(pruned_desc);
   });
@@ -345,7 +345,7 @@ All parameter, weight, gradient are variables in Paddle.
   py::class_<OperatorBase>(m, "Operator")
       .def_static("create",
                   [](py::bytes protobin) {
-                    OpDesc desc;
+                    proto::OpDesc desc;
                     PADDLE_ENFORCE(desc.ParsePartialFromString(protobin),
                                    "Cannot parse user input to OpDesc");
                     PADDLE_ENFORCE(desc.IsInitialized(),
@@ -398,7 +398,7 @@ All parameter, weight, gradient are variables in Paddle.
   py::class_<operators::CondOp, OperatorBase>(m, "CondOp")
       .def_static("create",
                   [](py::bytes protobin) -> operators::CondOp * {
-                    OpDesc desc;
+                    proto::OpDesc desc;
                     PADDLE_ENFORCE(desc.ParsePartialFromString(protobin),
                                    "Cannot parse user input to OpDesc");
                     PADDLE_ENFORCE(desc.IsInitialized(),