Merge pull request #14858 from reyoung/feature/tensor_type

Feature/tensor type

paddle/fluid/framework/data_layout_transform.cc

@@ -85,7 +85,7 @@ void TransDataLayout(const OpKernelType& kernel_type_for_var,
   out->mutable_data(expected_kernel_type.place_, in.type());
 
   framework::VisitDataType(
-      framework::ToDataType(in.type()),
+      in.type(),
       CastDataLayout(pool.Get(expected_kernel_type.place_), axis, in, out));
 
   out->set_layout(expected_kernel_type.data_layout_);
@@ -101,7 +101,7 @@ void* GetDataFromTensor(const Tensor& tensor, mkldnn::memory::data_type type) {
     case mkldnn::memory::data_type::f32:
       return platform::to_void_cast(tensor.data<float>());
     case mkldnn::memory::data_type::s8:
-      return platform::to_void_cast(tensor.data<char>());
+      return platform::to_void_cast(tensor.data<int8_t>());
     case mkldnn::memory::data_type::u8:
       return platform::to_void_cast(tensor.data<unsigned char>());
     case mkldnn::memory::data_type::s16:
@@ -144,7 +144,7 @@ void TransDataLayoutFromMKLDNN(const OpKernelType& kernel_type_for_var,
 
   memory::data_type in_type = ToMKLDNNDataType(in.type());
   PADDLE_ENFORCE(in_type != memory::data_type::data_undef,
-                 "Input tensor type is not supported: ", in.type().name());
+                 "Input tensor type is not supported: %s", in.type());
   memory::data_type out_type = in_type;
 
   auto in_format = platform::MKLDNNFormatForSize(in_tz.size(), in.format());

paddle/fluid/framework/data_layout_transform.h

@@ -50,14 +50,14 @@ inline DataLayout ToPaddleLayout(const MKLDNNFormat& format) {
   }
 }
 
-inline MKLDNNDataType ToMKLDNNDataType(const std::type_index type) {
-  static const std::map<std::type_index, MKLDNNDataType> dict{
-      {std::type_index(typeid(float)), MKLDNNDataType::f32},  // NOLINT
-      {std::type_index(typeid(char)), MKLDNNDataType::s8},    // NOLINT
-      {std::type_index(typeid(unsigned char)), MKLDNNDataType::u8},
-      {std::type_index(typeid(int16_t)), MKLDNNDataType::s16},
-      {std::type_index(typeid(int32_t)), MKLDNNDataType::s32}};
-  auto iter = dict.find(type);
+inline MKLDNNDataType ToMKLDNNDataType(proto::VarType::Type type) {
+  static std::unordered_map<int, MKLDNNDataType> dict{
+      {DataTypeTrait<float>::DataType, MKLDNNDataType::f32},
+      {DataTypeTrait<int8_t>::DataType, MKLDNNDataType::s8},
+      {DataTypeTrait<uint8_t>::DataType, MKLDNNDataType::u8},
+      {DataTypeTrait<int16_t>::DataType, MKLDNNDataType::s16},
+      {DataTypeTrait<int32_t>::DataType, MKLDNNDataType::s32}};
+  auto iter = dict.find(static_cast<int>(type));
   if (iter != dict.end()) return iter->second;
   return MKLDNNDataType::data_undef;
 }

paddle/fluid/framework/data_type.cc

@@ -26,7 +26,7 @@ struct DataTypeMap {
   std::unordered_map<std::type_index, proto::VarType::Type> cpp_to_proto_;
   std::unordered_map<int, std::type_index> proto_to_cpp_;
   std::unordered_map<int, std::string> proto_to_str_;
-  std::unordered_map<std::type_index, size_t> cpp_to_size_;
+  std::unordered_map<int, size_t> proto_to_size_;
 };
 
 static DataTypeMap* InitDataTypeMap();
@@ -45,7 +45,7 @@ static inline void RegisterType(DataTypeMap* map,
   map->proto_to_cpp_.emplace(static_cast<int>(proto_type), typeid(T));
   map->cpp_to_proto_.emplace(typeid(T), proto_type);
   map->proto_to_str_.emplace(static_cast<int>(proto_type), name);
-  map->cpp_to_size_.emplace(typeid(T), sizeof(T));
+  map->proto_to_size_.emplace(static_cast<int>(proto_type), sizeof(T));
 }
 
 static DataTypeMap* InitDataTypeMap() {
@@ -54,17 +54,7 @@ static DataTypeMap* InitDataTypeMap() {
 #define RegType(cc_type, proto_type) \
   RegisterType<cc_type>(retv, proto_type, #cc_type)
 
-  // NOTE: Add your customize type here.
-  RegType(float16, proto::VarType::FP16);
-  RegType(float, proto::VarType::FP32);
-  RegType(double, proto::VarType::FP64);
-  RegType(int, proto::VarType::INT32);
-  RegType(int64_t, proto::VarType::INT64);
-  RegType(bool, proto::VarType::BOOL);
-  RegType(size_t, proto::VarType::SIZE_T);
-  RegType(int16_t, proto::VarType::INT16);
-  RegType(uint8_t, proto::VarType::UINT8);
-  RegType(int8_t, proto::VarType::INT8);
+  _ForEachDataType_(RegType);
 
 #undef RegType
   return retv;
@@ -96,12 +86,12 @@ std::string DataTypeToString(const proto::VarType::Type type) {
                static_cast<int>(type));
 }
 
-size_t SizeOfType(std::type_index type) {
-  auto it = gDataTypeMap().cpp_to_size_.find(type);
-  if (it != gDataTypeMap().cpp_to_size_.end()) {
+size_t SizeOfType(proto::VarType::Type type) {
+  auto it = gDataTypeMap().proto_to_size_.find(static_cast<int>(type));
+  if (it != gDataTypeMap().proto_to_size_.end()) {
     return it->second;
   }
-  PADDLE_THROW("Not support %s as tensor type", type.name());
+  PADDLE_THROW("Not support %s as tensor type", DataTypeToString(type));
 }
 
 }  // namespace framework

paddle/fluid/framework/data_type.h

@@ -22,46 +22,59 @@ limitations under the License. */
 namespace paddle {
 namespace framework {
 
+template <typename T>
+struct DataTypeTrait {};
+
+// Stub handle for void
+template <>
+struct DataTypeTrait<void> {
+  constexpr static auto DataType = proto::VarType::RAW;
+};
+
+#define _ForEachDataTypeHelper_(callback, cpp_type, proto_type) \
+  callback(cpp_type, ::paddle::framework::proto::VarType::proto_type);
+
+#define _ForEachDataType_(callback)                                     \
+  _ForEachDataTypeHelper_(callback, float, FP32);                       \
+  _ForEachDataTypeHelper_(callback, ::paddle::platform::float16, FP16); \
+  _ForEachDataTypeHelper_(callback, double, FP64);                      \
+  _ForEachDataTypeHelper_(callback, int, INT32);                        \
+  _ForEachDataTypeHelper_(callback, int64_t, INT64);                    \
+  _ForEachDataTypeHelper_(callback, bool, BOOL);                        \
+  _ForEachDataTypeHelper_(callback, uint8_t, UINT8);                    \
+  _ForEachDataTypeHelper_(callback, int16_t, INT16);                    \
+  _ForEachDataTypeHelper_(callback, int8_t, INT8)
+
+#define DefineDataTypeTrait(cpp_type, proto_type) \
+  template <>                                     \
+  struct DataTypeTrait<cpp_type> {                \
+    constexpr static auto DataType = proto_type;  \
+  }
+
+_ForEachDataType_(DefineDataTypeTrait);
+
+#undef DefineDataTypeTrait
+
 extern proto::VarType::Type ToDataType(std::type_index type);
 extern std::type_index ToTypeIndex(proto::VarType::Type type);
 
 template <typename Visitor>
 inline void VisitDataType(proto::VarType::Type type, Visitor visitor) {
-  switch (type) {
-    case proto::VarType::FP16:
-      visitor.template apply<platform::float16>();
-      break;
-    case proto::VarType::FP32:
-      visitor.template apply<float>();
-      break;
-    case proto::VarType::FP64:
-      visitor.template apply<double>();
-      break;
-    case proto::VarType::INT32:
-      visitor.template apply<int>();
-      break;
-    case proto::VarType::INT64:
-      visitor.template apply<int64_t>();
-      break;
-    case proto::VarType::BOOL:
-      visitor.template apply<bool>();
-      break;
-    case proto::VarType::UINT8:
-      visitor.template apply<uint8_t>();
-      break;
-    case proto::VarType::INT16:
-      visitor.template apply<int16_t>();
-      break;
-    case proto::VarType::INT8:
-      visitor.template apply<int8_t>();
-      break;
-    default:
-      PADDLE_THROW("Not supported %d", type);
-  }
+#define VisitDataTypeCallback(cpp_type, proto_type) \
+  do {                                              \
+    if (type == proto_type) {                       \
+      visitor.template apply<cpp_type>();           \
+      return;                                       \
+    }                                               \
+  } while (0)
+
+  _ForEachDataType_(VisitDataTypeCallback);
+#undef VisitDataTypeCallback
+  PADDLE_THROW("Not supported %d", type);
 }
 
 extern std::string DataTypeToString(const proto::VarType::Type type);
-extern size_t SizeOfType(std::type_index type);
+extern size_t SizeOfType(proto::VarType::Type type);
 inline std::ostream& operator<<(std::ostream& out,
                                 const proto::VarType::Type& type) {
   out << DataTypeToString(type);

paddle/fluid/framework/data_type_test.cc

@@ -26,15 +26,15 @@ TEST(DataType, float16) {
 
   Tensor tensor;
   CPUPlace cpu;
-  tensor.mutable_data(cpu, f::ToTypeIndex(dtype));
+  tensor.mutable_data(cpu, dtype);
 
   // test fp16 tensor
-  EXPECT_EQ(tensor.type(), std::type_index(typeid(float16)));
+  EXPECT_EQ(tensor.type(), f::ToDataType(typeid(float16)));
 
   // test fp16 size
-  EXPECT_EQ(f::SizeOfType(f::ToTypeIndex(dtype)), 2u);
+  EXPECT_EQ(f::SizeOfType(dtype), 2u);
 
   // test debug info
-  std::string type = "float16";
+  std::string type = "::paddle::platform::float16";
   EXPECT_STREQ(f::DataTypeToString(dtype).c_str(), type.c_str());
 }

paddle/fluid/framework/details/all_reduce_op_handle.cc

@@ -127,7 +127,7 @@ void AllReduceOpHandle::RunImpl() {
 
       // Reduce All Tensor to trg in CPU
       ReduceLoDTensor func(lod_tensors, &trg);
-      VisitDataType(ToDataType(lod_tensors[0]->type()), func);
+      VisitDataType(lod_tensors[0]->type(), func);
 
       for (size_t i = 1; i < local_scopes_.size(); ++i) {
         auto &scope =

paddle/fluid/framework/details/fuse_vars_op_handle.h

@@ -33,7 +33,7 @@ struct FuseVarsOpHandle : public OpHandleBase {
   FuseVarsOpHandle(ir::Node *node, Scope *local_scope,
                    const platform::Place &place,
                    const std::unordered_map<std::string, int64_t> &inputs_numel,
-                   const std::type_index &var_type)
+                   const proto::VarType::Type var_type)
       : OpHandleBase(node),
         local_scope_(local_scope),
         place_(place),
@@ -57,7 +57,7 @@ struct FuseVarsOpHandle : public OpHandleBase {
   Scope *local_scope_;
   const platform::Place place_;
   const std::unordered_map<std::string, int64_t> inputs_numel_;
-  const std::type_index type_;
+  const proto::VarType::Type type_;
   int64_t total_numel_;
 };
 }  // namespace details

paddle/fluid/framework/details/reduce_op_handle.cc

@@ -218,18 +218,18 @@ void ReduceOpHandle::RunImpl() {
       }
 
 #if defined PADDLE_WITH_CUDA && defined PADDLE_WITH_DISTRIBUTE
-      if (framework::IsType<const float>(in_selected_rows[0]->value().type())) {
+      if (in_selected_rows[0]->value().type() ==
+          framework::proto::VarType::FP32) {
         GatherSelectedRows<platform::CUDADeviceContext, float>(
             in_selected_rows, in_places, dev_ctxes_, out_var_handle, t_out_p,
             out_var->GetMutable<framework::SelectedRows>());
-      } else if (framework::IsType<const double>(
-                     in_selected_rows[0]->value().type())) {
+      } else if (in_selected_rows[0]->value().type() ==
+                 framework::proto::VarType::FP64) {
         GatherSelectedRows<platform::CUDADeviceContext, double>(
             in_selected_rows, in_places, dev_ctxes_, out_var_handle, t_out_p,
             out_var->GetMutable<framework::SelectedRows>());
       } else {
-        PADDLE_ENFORCE(false,
-                       "only support double or float when gahter SelectedRows");
+        PADDLE_THROW("only support double or float when gather SelectedRows");
       }
 #endif
     });
@@ -246,7 +246,7 @@ void ReduceOpHandle::RunImpl() {
         if (!FLAGS_cpu_deterministic) {
           ReduceLoDTensor func(lod_tensors,
                                out_var->GetMutable<framework::LoDTensor>());
-          VisitDataType(ToDataType(lod_tensors[0]->type()), func);
+          VisitDataType(lod_tensors[0]->type(), func);
         } else {
           // We sum lod_tensors to reduce_sum_trg which is in local_scopes_0
           // here, but it doesn't mean reduce_sum_trg must be in local_scopes_0.
@@ -256,7 +256,7 @@ void ReduceOpHandle::RunImpl() {
                                       ->FindVar(out_var_handle->name_)
                                       ->GetMutable<framework::LoDTensor>();
           ReduceLoDTensor func(lod_tensors, &reduce_sum_trg);
-          VisitDataType(ToDataType(lod_tensors[0]->type()), func);
+          VisitDataType(lod_tensors[0]->type(), func);
 
           auto trg = out_var->GetMutable<framework::LoDTensor>();
           if (reduce_sum_trg.data<void>() != trg->data<void>()) {

paddle/fluid/framework/dlpack_tensor.cc

@@ -13,7 +13,7 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/dlpack_tensor.h"
-
+#include "paddle/fluid/framework/data_type.h"
 namespace paddle {
 namespace framework {
 
@@ -36,26 +36,23 @@ static ::DLDataType GetDLDataTypeCode() {
   return dtype;
 }
 
-static DLDataType GetDLDataTypeFromTypeIndex(const std::type_index &type) {
-#define REG_DL_DATA_TYPE(type) \
-  { std::type_index(typeid(type)), GetDLDataTypeCode<type>() }
-  static const std::unordered_map<std::type_index, ::DLDataType>
-      type_to_dtype_map({
-          REG_DL_DATA_TYPE(platform::float16),  // NOLINT
-          REG_DL_DATA_TYPE(float),              // NOLINT
-          REG_DL_DATA_TYPE(double),             // NOLINT
-          REG_DL_DATA_TYPE(int),                // NOLINT
-          REG_DL_DATA_TYPE(int64_t),            // NOLINT
-          REG_DL_DATA_TYPE(bool),               // NOLINT
-          REG_DL_DATA_TYPE(size_t),             // NOLINT
-          REG_DL_DATA_TYPE(int16_t),            // NOLINT
-          REG_DL_DATA_TYPE(uint8_t),            // NOLINT
-          REG_DL_DATA_TYPE(int8_t)              // NOLINT
-      });
+static std::unordered_map<int, ::DLDataType> CreateDLDataTypeMap() {
+  static std::unordered_map<int, ::DLDataType> result;
+
+#define REG_DL_DATA_TYPE(cpp_type, proto_type) \
+  result[static_cast<int>(proto_type)] = GetDLDataTypeCode<cpp_type>()
+
+  _ForEachDataType_(REG_DL_DATA_TYPE);
+#undef REG_DL_DATA_TYPE
+  return result;
+}
+
+static DLDataType GetDLDataTypeFromTypeIndex(proto::VarType::Type type) {
+  static auto type_to_dtype_map = CreateDLDataTypeMap();
   static auto type_to_dtype_map_end_it = type_to_dtype_map.end();
-  auto it = type_to_dtype_map.find(type);
-  PADDLE_ENFORCE(it != type_to_dtype_map_end_it, "Unsupported data type %s",
-                 type.name());
+  auto it = type_to_dtype_map.find(static_cast<int>(type));
+  PADDLE_ENFORCE(it != type_to_dtype_map_end_it, "Unsupported data type %d",
+                 type);
   return it->second;
 #undef REG_DL_DATA_TYPE
 }

paddle/fluid/framework/dlpack_tensor_test.cc

@@ -91,23 +91,11 @@ void TestMainLoop() {
     }
   }
 }
+TEST(dlpack, test_all) {
+#define TestCallback(cpp_type, proto_type) TestMainLoop<cpp_type>()
 
-#define PADDLE_DLPACK_TEST(type) \
-  TEST(dlpack, test_##type) { TestMainLoop<type>(); }
-
-using float16 = platform::float16;
-PADDLE_DLPACK_TEST(float16);
-PADDLE_DLPACK_TEST(float);
-PADDLE_DLPACK_TEST(double);
-PADDLE_DLPACK_TEST(int);
-PADDLE_DLPACK_TEST(int64_t);
-PADDLE_DLPACK_TEST(bool);
-PADDLE_DLPACK_TEST(size_t);
-PADDLE_DLPACK_TEST(int16_t);
-PADDLE_DLPACK_TEST(uint8_t);
-PADDLE_DLPACK_TEST(int8_t);
-
-#undef PADDLE_DLPACK_TEST
+  _ForEachDataType_(TestCallback);
+}
 
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/framework/executor_thread_worker.cc

@@ -139,39 +139,19 @@ void print_lod_tensor(std::string var_name, const LoDTensor& lod_tensor) {
   std::cout << sstream.str() << std::endl;
 }
 
-void print_fetch_var(Scope* scope, std::string var_name) {
-  const LoDTensor& tensor = scope->FindVar(var_name)->Get<LoDTensor>();
-
-  if (std::type_index(tensor.type()) ==
-      std::type_index(typeid(platform::float16))) {
-    print_lod_tensor<platform::float16>(var_name, tensor);
-  } else if (std::type_index(tensor.type()) == std::type_index(typeid(float))) {
-    print_lod_tensor<float>(var_name, tensor);
-  } else if (std::type_index(tensor.type()) ==
-             std::type_index(typeid(double))) {
-    print_lod_tensor<double>(var_name, tensor);
-  } else if (std::type_index(tensor.type()) == std::type_index(typeid(int))) {
-    print_lod_tensor<int>(var_name, tensor);
-  } else if (std::type_index(tensor.type()) ==
-             std::type_index(typeid(int64_t))) {
-    print_lod_tensor<int64_t>(var_name, tensor);
-  } else if (std::type_index(tensor.type()) == std::type_index(typeid(bool))) {
-    print_lod_tensor<bool>(var_name, tensor);
-  } else if (std::type_index(tensor.type()) ==
-             std::type_index(typeid(uint8_t))) {
-    print_lod_tensor<uint8_t>(var_name, tensor);
-  } else if (std::type_index(tensor.type()) ==
-             std::type_index(typeid(int16_t))) {
-    print_lod_tensor<int16_t>(var_name, tensor);
-  } else if (std::type_index(tensor.type()) ==
-             std::type_index(typeid(int8_t))) {
-    print_lod_tensor<int8_t>(var_name, tensor);
-  } else {
-    VLOG(1) << "print_fetch_var: unrecognized data type:"
-            << tensor.type().name();
-  }
-
-  return;
+static void print_fetch_var(Scope* scope, const std::string& var_name) {
+  auto& tensor = scope->FindVar(var_name)->Get<LoDTensor>();
+
+#define PrintLoDTensorCallback(cpp_type, proto_type) \
+  do {                                               \
+    if (tensor.type() == proto_type) {               \
+      print_lod_tensor<cpp_type>(var_name, tensor);  \
+      return;                                        \
+    }                                                \
+  } while (0)
+
+  _ForEachDataType_(PrintLoDTensorCallback);
+  VLOG(1) << "print_fetch_var: unrecognized data type:" << tensor.type();
 }
 
 void ExecutorThreadWorker::TrainFiles() {

paddle/fluid/framework/lod_tensor.cc

@@ -70,9 +70,9 @@ std::ostream &operator<<(std::ostream &os, const LoDTensor &t) {
   // only print first ten elements
   int64_t size = t.numel() < 10 ? t.numel() : 10;
   for (int64_t i = 0; i < size; ++i) {
-    if (IsType<float>(t.type())) {
+    if (t.type() == proto::VarType::FP32) {
       os << t.data<float>()[i] << " ";
-    } else if (IsType<int64_t>(t.type())) {
+    } else if (t.type() == proto::VarType::INT64) {
       os << t.data<int64_t>()[i] << " ";
     } else {
       PADDLE_THROW("LoDTensor data type not in [float, int64_t]");
@@ -387,7 +387,7 @@ void LoDTensor::MergeLoDTensor(
   PADDLE_ENFORCE(!lod_tensors.empty());
 
   framework::DDim new_dim = lod_tensors[0]->dims();
-  std::type_index new_type = lod_tensors[0]->type();
+  auto new_type = lod_tensors[0]->type();
   framework::DataLayout new_layout = lod_tensors[0]->layout();
   LoD new_lod = lod_tensors[0]->lod();
   for (size_t i = 1; i < lod_tensors.size(); ++i) {

paddle/fluid/framework/ngraph_operator.cc

@@ -471,27 +471,23 @@ void NgraphEngine::Run(const Scope& scope, const platform::Place& place) const {
       auto* tensor_pd = GetLoDTensorOrSelectedRowsValueFromVar(*var);
       PADDLE_ENFORCE(sp == Ddim2Shape(tensor_pd->dims()),
                      "Ensure ngraph tensor layout align with paddle tensor");
-      if (tensor_pd->type().hash_code() ==
-          typeid(float).hash_code()) {  // NOLINT
+      if (tensor_pd->type() == proto::VarType::FP32) {
         const float* arr = tensor_pd->data<float>();
         ti = backend_->create_tensor(ngraph::element::f32, sp,
                                      const_cast<float*>(arr));
-      } else if (tensor_pd->type().hash_code() ==
-                 typeid(int).hash_code()) {  // NOLINT
+      } else if (tensor_pd->type() == proto::VarType::INT32) {
         const int* arr = tensor_pd->data<int>();
         ti = backend_->create_tensor(ngraph::element::i32, sp,
                                      const_cast<int*>(arr));
-      } else if (tensor_pd->type().hash_code() == typeid(int64_t).hash_code()) {
+      } else if (tensor_pd->type() == proto::VarType::INT64) {
         const int64_t* arr = tensor_pd->data<int64_t>();
         ti = backend_->create_tensor(ngraph::element::i64, sp,
                                      const_cast<int64_t*>(arr));
-      } else if (tensor_pd->type().hash_code() ==
-                 typeid(double).hash_code()) {  // NOLINT
+      } else if (tensor_pd->type() == proto::VarType::FP64) {
         const double* arr = tensor_pd->data<double>();
         ti = backend_->create_tensor(ngraph::element::f64, sp,
                                      const_cast<double*>(arr));
-      } else if (tensor_pd->type().hash_code() ==
-                 typeid(bool).hash_code()) {  // NOLINT
+      } else if (tensor_pd->type() == proto::VarType::BOOL) {
         const bool* arr = tensor_pd->data<bool>();
         ti = backend_->create_tensor(ngraph::element::boolean, sp,
                                      const_cast<bool*>(arr));

paddle/fluid/framework/op_kernel_type_test.cc

@@ -34,7 +34,8 @@ TEST(OpKernelType, ToString) {
   OpKernelType op_kernel_type2(DataType::FP16, CUDAPlace(0), DataLayout::kNCHW,
                                LibraryType::kCUDNN);
   ASSERT_EQ(paddle::framework::KernelTypeToString(op_kernel_type2),
-            "data_type[float16]:data_layout[NCHW]:place[CUDAPlace(0)]:library_"
+            "data_type[::paddle::platform::float16]:data_layout[NCHW]:place["
+            "CUDAPlace(0)]:library_"
             "type[CUDNN]");
 }
 

paddle/fluid/framework/operator.cc

@@ -43,10 +43,9 @@ std::vector<std::tuple<platform::Place, LibraryType>> kKernelPriority = {
 
 proto::VarType::Type GetDataTypeOfVar(const Variable* var) {
   if (var->IsType<framework::LoDTensor>()) {
-    return framework::ToDataType(var->Get<framework::LoDTensor>().type());
+    return var->Get<framework::LoDTensor>().type();
   } else if (var->IsType<framework::SelectedRows>()) {
-    return framework::ToDataType(
-        var->Get<framework::SelectedRows>().value().type());
+    return var->Get<framework::SelectedRows>().value().type();
   } else {
     PADDLE_THROW("Var should be LoDTensor or SelectedRows");
   }
@@ -93,13 +92,13 @@ static std::string GetDtype(const Scope& scope, const std::string& name) {
     if (UNLIKELY(!tensor.IsInitialized())) {
       return "";
     }
-    return DataTypeToString(ToDataType(tensor.type()));
+    return DataTypeToString(tensor.type());
   } else if (var->IsType<SelectedRows>()) {
     auto tensor = var->Get<SelectedRows>().value();
     if (UNLIKELY(!tensor.IsInitialized())) {
       return "uninited";
     } else {
-      return DataTypeToString(ToDataType(tensor.type()));
+      return DataTypeToString(tensor.type());
     }
   } else {
     return "";
@@ -686,7 +685,8 @@ static void CheckTensorNANOrInf(const std::string& name,
   if (tensor.memory_size() == 0) {
     return;
   }
-  if (!IsType<float>(tensor.type()) && !IsType<double>(tensor.type())) {
+  if (tensor.type() != proto::VarType::FP32 &&
+      tensor.type() != proto::VarType::FP64) {
     return;
   }
   PADDLE_ENFORCE(!framework::TensorContainsInf(tensor),
@@ -881,7 +881,7 @@ proto::VarType::Type OperatorWithKernel::IndicateDataType(
         if (t != nullptr) {
           PADDLE_ENFORCE(t->IsInitialized(), "Input %s is not initialized: %s",
                          ipt_name, DebugString());
-          int tmp = static_cast<int>(ToDataType(t->type()));
+          int tmp = static_cast<int>(t->type());
           PADDLE_ENFORCE(
               tmp == data_type || data_type == -1,
               "DataType of Paddle Op %s must be the same. Get %s(%d) != %s(%d)",

paddle/fluid/framework/selected_rows.cc

@@ -218,11 +218,11 @@ void SelectedRows::Get(const framework::Tensor& ids, framework::Tensor* value,
       if (index < 0) {
         VLOG(5) << "id " << id << " not in the table, return 0";
         framework::VisitDataType(
-            framework::ToDataType(value_->type()),
+            value_->type(),
             TensorFillVisitor(value, i * value_width, value_width, 0.0));
       } else {
         framework::VisitDataType(
-            framework::ToDataType(value_->type()),
+            value_->type(),
             TensorCopyVisitor(value, i * value_width, *value_.get(),
                               index * value_width, value_width));
       }

paddle/fluid/framework/tensor.cc

@@ -16,7 +16,7 @@ limitations under the License. */
 
 namespace paddle {
 namespace framework {
-extern size_t SizeOfType(std::type_index type);
+extern size_t SizeOfType(proto::VarType::Type type);
 void Tensor::check_memory_size() const {
   PADDLE_ENFORCE_NOT_NULL(
       holder_, "Tensor holds no memory. Call Tensor::mutable_data first.");
@@ -31,7 +31,7 @@ size_t Tensor::memory_size() const {
   return holder_ == nullptr ? 0UL : holder_->size() - offset_;
 }
 
-void* Tensor::mutable_data(platform::Place place, std::type_index type,
+void* Tensor::mutable_data(platform::Place place, proto::VarType::Type type,
                            memory::Allocator::Attr attr,
                            size_t requested_size) {
   type_ = type;

paddle/fluid/framework/tensor.h

@@ -19,9 +19,9 @@ limitations under the License. */
 #include <memory>
 #include <typeindex>
 #include <vector>
-
 #include "paddle/fluid/framework/data_layout.h"
 #include "paddle/fluid/framework/ddim.h"
+#include "paddle/fluid/framework/framework.pb.h"
 #include "paddle/fluid/memory/memory.h"
 #include "paddle/fluid/platform/device_context.h"
 #include "paddle/fluid/platform/enforce.h"
@@ -67,7 +67,7 @@ class Tensor {
   friend struct EigenVector;
 
  public:
-  Tensor() : type_(typeid(float)), offset_(0) {}
+  Tensor() : type_(proto::VarType::FP32), offset_(0) {}
 
   /*! Return a pointer to mutable memory block. */
   template <typename T>
@@ -88,7 +88,7 @@ class Tensor {
                   memory::Allocator::Attr attr = memory::Allocator::kDefault,
                   size_t requested_size = 0);
 
-  void* mutable_data(platform::Place place, std::type_index type,
+  void* mutable_data(platform::Place place, proto::VarType::Type type,
                      memory::Allocator::Attr attr = memory::Allocator::kDefault,
                      size_t requested_size = 0);
 
@@ -138,7 +138,7 @@ class Tensor {
     return holder_->place();
   }
 
-  std::type_index type() const {
+  proto::VarType::Type type() const {
     PADDLE_ENFORCE_NOT_NULL(
         holder_, "Tensor not initialized yet when Tensor::type() is called.");
     return type_;
@@ -165,7 +165,7 @@ class Tensor {
  private:
   /*! holds the memory block if allocated. */
   std::shared_ptr<memory::Allocation> holder_;
-  std::type_index type_;
+  proto::VarType::Type type_;
   /**
    * @brief points to elements dimensions.
    *

paddle/fluid/framework/tensor_impl.h

@@ -24,9 +24,8 @@ template <typename T>
 inline const T* Tensor::data() const {
   check_memory_size();
   bool valid =
-      std::is_same<T, void>::value || type_ == std::type_index(typeid(T));
-  PADDLE_ENFORCE(valid, "Tensor holds the wrong type, it holds %s",
-                 type_.name());
+      std::is_same<T, void>::value || type_ == DataTypeTrait<T>::DataType;
+  PADDLE_ENFORCE(valid, "Tensor holds the wrong type, it holds %d", type_);
 
   return reinterpret_cast<const T*>(
       reinterpret_cast<uintptr_t>(holder_->ptr()) + offset_);
@@ -38,9 +37,8 @@ template <typename T>
 inline T* Tensor::data() {
   check_memory_size();
   bool valid =
-      std::is_same<T, void>::value || type_ == std::type_index(typeid(T));
-  PADDLE_ENFORCE(valid, "Tensor holds the wrong type, it holds %s",
-                 type_.name());
+      std::is_same<T, void>::value || type_ == DataTypeTrait<T>::DataType;
+  PADDLE_ENFORCE(valid, "Tensor holds the wrong type, it holds %s", type_);
   return reinterpret_cast<T*>(reinterpret_cast<uintptr_t>(holder_->ptr()) +
                               offset_);
 }
@@ -60,7 +58,7 @@ inline T* Tensor::mutable_data(platform::Place place,
                                size_t requested_size) {
   static_assert(std::is_pod<T>::value, "T must be POD");
   return reinterpret_cast<T*>(
-      mutable_data(place, typeid(T), attr, requested_size));
+      mutable_data(place, DataTypeTrait<T>::DataType, attr, requested_size));
 }
 
 inline Tensor ReshapeToMatrix(const Tensor& src, int num_col_dims) {

paddle/fluid/framework/tensor_util.cc

@@ -186,8 +186,8 @@ struct AnyDTypeVisitor {
 template <typename Predicate, typename DevCtx>
 inline void AnyImpl(Predicate predicate, const framework::Tensor& tensor,
                     const DevCtx& ctx, framework::Tensor* out) {
-  VisitDataType(ToDataType(tensor.type()), AnyDTypeVisitor<Predicate, DevCtx>(
-                                               predicate, tensor, ctx, out));
+  VisitDataType(tensor.type(), AnyDTypeVisitor<Predicate, DevCtx>(
+                                   predicate, tensor, ctx, out));
 }
 
 template <typename Predicate>
@@ -379,7 +379,7 @@ void TensorToStream(std::ostream& os, const Tensor& tensor,
      // int32_t  size
      // void*    protobuf message
     proto::VarType::TensorDesc desc;
-    desc.set_data_type(framework::ToDataType(tensor.type()));
+    desc.set_data_type(tensor.type());
     auto dims = framework::vectorize(tensor.dims());
     auto* pb_dims = desc.mutable_dims();
     pb_dims->Resize(static_cast<int>(dims.size()), 0);
@@ -461,9 +461,7 @@ void TensorFromStream(std::istream& is, Tensor* tensor,
     tensor->Resize(framework::make_ddim(dims));
     void* buf;
     auto ctx = platform::CPUDeviceContext();
-    size_t size =
-        tensor->numel() *
-        framework::SizeOfType(framework::ToTypeIndex(desc.data_type()));
+    size_t size = tensor->numel() * framework::SizeOfType(desc.data_type());
     if (platform::is_gpu_place(dev_ctx.GetPlace())) {
 #ifdef PADDLE_WITH_CUDA
       Tensor cpu_tensor;

paddle/fluid/inference/api/analysis_predictor.cc

@@ -289,10 +289,10 @@ bool AnalysisPredictor::GetFetch(std::vector<PaddleTensor> *outputs,
     auto type = fetch.type();
     auto output = &(outputs->at(i));
     output->name = fetchs_[idx]->Input("X")[0];
-    if (type == typeid(float)) {
+    if (type == framework::proto::VarType::FP32) {
       GetFetchOne<float>(fetch, output);
       output->dtype = PaddleDType::FLOAT32;
-    } else if (type == typeid(int64_t)) {
+    } else if (type == framework::proto::VarType::INT64) {
       GetFetchOne<int64_t>(fetch, output);
       output->dtype = PaddleDType::INT64;
     } else {

paddle/fluid/inference/api/api_impl.cc

@@ -266,10 +266,10 @@ bool NativePaddlePredictor::GetFetch(std::vector<PaddleTensor> *outputs,
     auto type = fetch.type();
     auto output = &(outputs->at(i));
     output->name = fetchs_[idx]->Input("X")[0];
-    if (type == typeid(float)) {
+    if (type == framework::DataTypeTrait<float>::DataType) {
       GetFetchOne<float>(fetch, output);
       output->dtype = PaddleDType::FLOAT32;
-    } else if (type == typeid(int64_t)) {
+    } else if (type == framework::DataTypeTrait<int64_t>::DataType) {
       GetFetchOne<int64_t>(fetch, output);
       output->dtype = PaddleDType::INT64;
     } else {

paddle/fluid/inference/api/api_impl_tester.cc

@@ -36,10 +36,10 @@ namespace paddle {
 PaddleTensor LodTensorToPaddleTensor(framework::LoDTensor* t) {
   PaddleTensor pt;
 
-  if (t->type() == typeid(int64_t)) {
+  if (t->type() == framework::proto::VarType::INT64) {
     pt.data.Reset(t->data<void>(), t->numel() * sizeof(int64_t));
     pt.dtype = PaddleDType::INT64;
-  } else if (t->type() == typeid(float)) {
+  } else if (t->type() == framework::proto::VarType::FP32) {
     pt.data.Reset(t->data<void>(), t->numel() * sizeof(float));
     pt.dtype = PaddleDType::FLOAT32;
   } else {

paddle/fluid/inference/tests/api/tester_helper.h

@@ -373,7 +373,7 @@ static bool CompareTensorData(const framework::LoDTensor &a,
   }
 
   for (size_t i = 0; i < a_size; i++) {
-    if (a.type() == typeid(float)) {
+    if (a.type() == framework::proto::VarType::FP32) {
       const auto *a_data = a.data<float>();
       const auto *b_data = b.data<float>();
       if (std::abs(a_data[i] - b_data[i]) > 1e-3) {
@@ -382,7 +382,7 @@ static bool CompareTensorData(const framework::LoDTensor &a,
             b_data[i]);
         return false;
       }
-    } else if (a.type() == typeid(int64_t)) {
+    } else if (a.type() == framework::proto::VarType::INT64) {
       const auto *a_data = a.data<int64_t>();
       const auto *b_data = b.data<int64_t>();
       if (std::abs(a_data[i] - b_data[i]) > 1e-3) {

paddle/fluid/operators/affine_grid_op.cc

@@ -78,7 +78,7 @@ class AffineGridOp : public framework::OperatorWithKernel {
       library = framework::LibraryType::kCUDNN;
     }
 #endif
-    auto data_type = framework::ToDataType(ctx.Input<Tensor>("Theta")->type());
+    auto data_type = ctx.Input<Tensor>("Theta")->type();
     return framework::OpKernelType(data_type, ctx.GetPlace(),
                                    framework::DataLayout::kAnyLayout, library);
   }
@@ -188,9 +188,9 @@ class AffineGridOpGrad : public framework::OperatorWithKernel {
       library_ = framework::LibraryType::kCUDNN;
     }
 #endif
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("Theta")->type()),
-        ctx.GetPlace(), framework::DataLayout::kAnyLayout, library_);
+    return framework::OpKernelType(ctx.Input<Tensor>("Theta")->type(),
+                                   ctx.GetPlace(),
+                                   framework::DataLayout::kAnyLayout, library_);
   }
 };
 

paddle/fluid/operators/arg_max_op.cc

@@ -28,6 +28,5 @@ REGISTER_OP_CPU_KERNEL(
                                     int32_t>,
     paddle::operators::ArgMaxKernel<paddle::platform::CPUDeviceContext,
                                     int16_t>,
-    paddle::operators::ArgMaxKernel<paddle::platform::CPUDeviceContext, size_t>,
     paddle::operators::ArgMaxKernel<paddle::platform::CPUDeviceContext,
                                     uint8_t>);

paddle/fluid/operators/arg_max_op.cu

@@ -25,7 +25,5 @@ REGISTER_OP_CUDA_KERNEL(
                                     int32_t>,
     paddle::operators::ArgMaxKernel<paddle::platform::CUDADeviceContext,
                                     int16_t>,
-    paddle::operators::ArgMaxKernel<paddle::platform::CUDADeviceContext,
-                                    size_t>,
     paddle::operators::ArgMaxKernel<paddle::platform::CUDADeviceContext,
                                     uint8_t>);

paddle/fluid/operators/arg_min_op.cc

@@ -28,6 +28,5 @@ REGISTER_OP_CPU_KERNEL(
                                     int32_t>,
     paddle::operators::ArgMinKernel<paddle::platform::CPUDeviceContext,
                                     int16_t>,
-    paddle::operators::ArgMinKernel<paddle::platform::CPUDeviceContext, size_t>,
     paddle::operators::ArgMinKernel<paddle::platform::CPUDeviceContext,
                                     uint8_t>);

paddle/fluid/operators/arg_min_op.cu

@@ -25,7 +25,5 @@ REGISTER_OP_CUDA_KERNEL(
                                     int32_t>,
     paddle::operators::ArgMinKernel<paddle::platform::CUDADeviceContext,
                                     int16_t>,
-    paddle::operators::ArgMinKernel<paddle::platform::CUDADeviceContext,
-                                    size_t>,
     paddle::operators::ArgMinKernel<paddle::platform::CUDADeviceContext,
                                     uint8_t>);

paddle/fluid/operators/array_to_lod_tensor_op.cc

@@ -58,7 +58,7 @@ struct ArrayToLoDFunctor : public boost::static_visitor<void> {
     ArrayToLoDFunctorImpl<DeviceContext> functor;
     functor.dev_ctx_ = dev_ctx;
     functor.prev_functor_ = this;
-    framework::VisitDataType(framework::ToDataType(out->type()), functor);
+    framework::VisitDataType(out->type(), functor);
   }
 };
 
@@ -91,7 +91,7 @@ class ArrayToLoDTensorOp : public framework::OperatorBase {
     PADDLE_ENFORCE(!x.empty(), "There's no element in the input array.");
     int rank = x[0].dims().size();
     platform::Place place = x[0].place();
-    std::type_index data_type = x[0].type();
+    auto data_type = x[0].type();
     int64_t batch_size = x[0].dims()[0];
     framework::DDim ins_dims = rank > 1
                                    ? framework::slice_ddim(x[0].dims(), 1, rank)

paddle/fluid/operators/attention_lstm_op.cc

@@ -121,9 +121,8 @@ void AttentionLSTMOp::InferShape(framework::InferShapeContext* ctx) const {
 
 framework::OpKernelType AttentionLSTMOp::GetExpectedKernelType(
     const framework::ExecutionContext& ctx) const {
-  return framework::OpKernelType(
-      framework::ToDataType(ctx.Input<framework::LoDTensor>("X")->type()),
-      ctx.device_context());
+  return framework::OpKernelType(ctx.Input<framework::LoDTensor>("X")->type(),
+                                 ctx.device_context());
 }
 
 void AttentionLSTMOpMaker::Make() {

paddle/fluid/operators/average_accumulates_op.cc

@@ -103,9 +103,8 @@ class AverageAccumulatesOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("param")->type()),
-        ctx.GetPlace());
+    return framework::OpKernelType(ctx.Input<Tensor>("param")->type(),
+                                   ctx.GetPlace());
   }
 };
 

paddle/fluid/operators/batch_norm_op.cc

@@ -72,8 +72,7 @@ class BatchNormOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
-    auto input_data_type =
-        framework::ToDataType(ctx.Input<Tensor>("X")->type());
+    auto input_data_type = ctx.Input<Tensor>("X")->type();
     // By default, the type of the scale, bias, mean,
     // and var tensors should both be float. (For float or float16 input tensor)
     // or double (For double input tensor).
@@ -81,17 +80,13 @@ class BatchNormOp : public framework::OperatorWithKernel {
     if (input_data_type == framework::proto::VarType::FP64) {
       bn_param_type = framework::proto::VarType::FP64;
     }
-    PADDLE_ENFORCE_EQ(bn_param_type,
-                      framework::ToDataType(ctx.Input<Tensor>("Scale")->type()),
+    PADDLE_ENFORCE_EQ(bn_param_type, ctx.Input<Tensor>("Scale")->type(),
                       "Scale input should be of float type");
-    PADDLE_ENFORCE_EQ(bn_param_type,
-                      framework::ToDataType(ctx.Input<Tensor>("Bias")->type()),
+    PADDLE_ENFORCE_EQ(bn_param_type, ctx.Input<Tensor>("Bias")->type(),
                       "Bias input should be of float type");
-    PADDLE_ENFORCE_EQ(bn_param_type,
-                      framework::ToDataType(ctx.Input<Tensor>("Mean")->type()),
+    PADDLE_ENFORCE_EQ(bn_param_type, ctx.Input<Tensor>("Mean")->type(),
                       "Mean input should be of float type");
-    PADDLE_ENFORCE_EQ(bn_param_type, framework::ToDataType(
-                                         ctx.Input<Tensor>("Variance")->type()),
+    PADDLE_ENFORCE_EQ(bn_param_type, ctx.Input<Tensor>("Variance")->type(),
                       "Variance input should be of float type");
 
     // TODO(pzelazko-intel): enable MKLDNN layout when it's ready
@@ -413,9 +408,8 @@ class BatchNormGradOp : public framework::OperatorWithKernel {
     }
 #endif
 
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("X")->type()), ctx.GetPlace(),
-        layout, library);
+    return framework::OpKernelType(ctx.Input<Tensor>("X")->type(),
+                                   ctx.GetPlace(), layout, library);
   }
 };
 

paddle/fluid/operators/beam_search_decode_op.cc

@@ -145,7 +145,7 @@ class BeamSearchDecodeOp : public framework::OperatorBase {
     LoDTensor* sentenceScores = ctx.Output<LoDTensor>("SentenceScores");
 
     framework::VisitDataType(
-        framework::ToDataType(scores->at(0).type()),
+        scores->at(0).type(),
         BeamSearchDecodeFunctor(*ids, *scores, sentenceIds, sentenceScores,
                                 beam_size, end_id));
   }

paddle/fluid/operators/beam_search_op.cc

@@ -282,8 +282,7 @@ class BeamSearchOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
     framework::OpKernelType kt = framework::OpKernelType(
-        framework::ToDataType(
-            ctx.Input<framework::LoDTensor>("pre_ids")->type()),
+        ctx.Input<framework::LoDTensor>("pre_ids")->type(),
         platform::CPUPlace());
     return kt;
   }

paddle/fluid/operators/bpr_loss_op.cc

@@ -47,9 +47,8 @@ class BprLossOp : public framework::OperatorWithKernel {
   // is determined by its input "X".
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("X")->type()),
-        platform::CPUPlace());
+    return framework::OpKernelType(ctx.Input<Tensor>("X")->type(),
+                                   platform::CPUPlace());
   }
 };
 
@@ -94,9 +93,8 @@ class BprLossGradientOp : public framework::OperatorWithKernel {
   // is determined by its input "X".
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("X")->type()),
-        platform::CPUPlace());
+    return framework::OpKernelType(ctx.Input<Tensor>("X")->type(),
+                                   platform::CPUPlace());
   }
 };
 

paddle/fluid/operators/controlflow/conditional_block_op.cc

@@ -48,13 +48,12 @@ class ConditionalOp : public framework::OperatorBase {
     if (!(ips.size() == 1UL && ips[0]->IsInitialized())) {
       PADDLE_THROW("should have one initialized input as condition");
     }
-    if (!(framework::IsType<bool>(ips[0]->type()) &&  // NOLINT
-          ips[0]->numel() == 1)) {
-      PADDLE_THROW(
-          "condition input's data type should be bool, "
-          "numel should be 1, actual numel is %d",
-          ips[0]->numel());
-    }
+
+    PADDLE_ENFORCE(ips[0]->type() == framework::proto::VarType::BOOL &&
+                       ips[0]->numel() == 1,
+                   "condition input's data type should be bool, "
+                   "numel should be 1, actual numel is %d",
+                   ips[0]->numel());
     bool res = false;
     if (platform::is_gpu_place(ips[0]->place())) {
 #ifdef PADDLE_WITH_CUDA

paddle/fluid/operators/controlflow/while_op.cc

@@ -261,7 +261,7 @@ class WhileGradOp : public framework::OperatorBase {
           if (var->IsType<LoDTensor>()) {
             auto &inside_tensor = var->Get<framework::LoDTensor>();
             framework::AttributeMap attrs;
-            attrs["dtype"] = framework::ToDataType(inside_tensor.type());
+            attrs["dtype"] = inside_tensor.type();
             attrs["shape"] = framework::vectorize2int(inside_tensor.dims());
             attrs["value"] = 0.0f;
 

paddle/fluid/operators/conv_op.cc

@@ -97,10 +97,8 @@ framework::OpKernelType ConvOp::GetExpectedKernelType(
   }
 #endif
 
-  auto input_data_type =
-      framework::ToDataType(ctx.Input<Tensor>("Input")->type());
-  auto filter_data_type =
-      framework::ToDataType(ctx.Input<Tensor>("Filter")->type());
+  auto input_data_type = ctx.Input<Tensor>("Input")->type();
+  auto filter_data_type = ctx.Input<Tensor>("Filter")->type();
   PADDLE_ENFORCE_EQ(input_data_type, filter_data_type,
                     "input and filter data type should be consistent");
 
@@ -384,9 +382,9 @@ framework::OpKernelType ConvOpGrad::GetExpectedKernelType(
   }
 #endif
 
-  return framework::OpKernelType(
-      framework::ToDataType(ctx.Input<Tensor>("Input")->type()), ctx.GetPlace(),
-      layout_, library_, customized_type_value);
+  return framework::OpKernelType(ctx.Input<Tensor>("Input")->type(),
+                                 ctx.GetPlace(), layout_, library_,
+                                 customized_type_value);
 }
 
 }  // namespace operators

paddle/fluid/operators/conv_transpose_op.cc

@@ -104,9 +104,8 @@ framework::OpKernelType ConvTransposeOp::GetExpectedKernelType(
   }
 #endif
 
-  return framework::OpKernelType(
-      framework::ToDataType(ctx.Input<Tensor>("Input")->type()), ctx.GetPlace(),
-      layout_, library_);
+  return framework::OpKernelType(ctx.Input<Tensor>("Input")->type(),
+                                 ctx.GetPlace(), layout_, library_);
 }
 
 void Conv2DTransposeOpMaker::Make() {
@@ -335,9 +334,8 @@ framework::OpKernelType ConvTransposeOpGrad::GetExpectedKernelType(
 
   std::string data_format = ctx.Attr<std::string>("data_format");
   framework::DataLayout layout_ = framework::StringToDataLayout(data_format);
-  return framework::OpKernelType(
-      framework::ToDataType(ctx.Input<Tensor>("Input")->type()), ctx.GetPlace(),
-      layout_, library_);
+  return framework::OpKernelType(ctx.Input<Tensor>("Input")->type(),
+                                 ctx.GetPlace(), layout_, library_);
 }
 
 }  // namespace operators

paddle/fluid/operators/crf_decoding_op.cc

@@ -118,9 +118,8 @@ class CRFDecodingOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<LoDTensor>("Emission")->type()),
-        platform::CPUPlace());
+    return framework::OpKernelType(ctx.Input<LoDTensor>("Emission")->type(),
+                                   platform::CPUPlace());
   }
 };
 }  // namespace operators

paddle/fluid/operators/crop_op.cc

@@ -51,9 +51,8 @@ class CropOp : public framework::OperatorWithKernel {
 
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::LoDTensor>("X")->type()),
-        ctx.device_context());
+    return framework::OpKernelType(ctx.Input<framework::LoDTensor>("X")->type(),
+                                   ctx.device_context());
   }
 };
 
@@ -174,9 +173,7 @@ class CropOpGrad : public framework::OperatorWithKernel {
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
     return framework::OpKernelType(
-        framework::ToDataType(
-            ctx.Input<framework::LoDTensor>(framework::GradVarName("Out"))
-                ->type()),
+        ctx.Input<framework::LoDTensor>(framework::GradVarName("Out"))->type(),
         ctx.device_context());
   }
 };

paddle/fluid/operators/cross_entropy_op.cc

@@ -57,9 +57,8 @@ class CrossEntropyOp : public framework::OperatorWithKernel {
   // is determined by its input "X".
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("X")->type()),
-        ctx.device_context());
+    return framework::OpKernelType(ctx.Input<Tensor>("X")->type(),
+                                   ctx.device_context());
   }
 };
 
@@ -111,9 +110,8 @@ class CrossEntropyGradientOp : public framework::OperatorWithKernel {
   // is determined by its input "X".
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("X")->type()),
-        ctx.device_context());
+    return framework::OpKernelType(ctx.Input<Tensor>("X")->type(),
+                                   ctx.device_context());
   }
 };
 

paddle/fluid/operators/ctc_align_op.cc

@@ -36,9 +36,8 @@ class CTCAlignOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("Input")->type()),
-        ctx.device_context());
+    return framework::OpKernelType(ctx.Input<Tensor>("Input")->type(),
+                                   ctx.device_context());
   }
 };
 

paddle/fluid/operators/detection/anchor_generator_op.cc

@@ -53,8 +53,7 @@ class AnchorGeneratorOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
     return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::Tensor>("Input")->type()),
-        ctx.device_context());
+        ctx.Input<framework::Tensor>("Input")->type(), ctx.device_context());
   }
 };
 

paddle/fluid/operators/detection/bipartite_match_op.cc

@@ -45,9 +45,8 @@ class BipartiteMatchOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<LoDTensor>("DistMat")->type()),
-        platform::CPUPlace());
+    return framework::OpKernelType(ctx.Input<LoDTensor>("DistMat")->type(),
+                                   platform::CPUPlace());
   }
 };
 

paddle/fluid/operators/detection/density_prior_box_op.cc

@@ -66,8 +66,7 @@ class DensityPriorBoxOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
     return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::Tensor>("Input")->type()),
-        ctx.GetPlace());
+        ctx.Input<framework::Tensor>("Input")->type(), ctx.GetPlace());
   }
 };
 

paddle/fluid/operators/detection/generate_proposals_op.cc

@@ -66,9 +66,8 @@ class GenerateProposalsOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("Anchors")->type()),
-        ctx.device_context());
+    return framework::OpKernelType(ctx.Input<Tensor>("Anchors")->type(),
+                                   ctx.device_context());
   }
 };
 

paddle/fluid/operators/detection/mine_hard_examples_op.cc

@@ -249,8 +249,7 @@ class MineHardExamplesOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
     return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::Tensor>("ClsLoss")->type()),
-        platform::CPUPlace());
+        ctx.Input<framework::Tensor>("ClsLoss")->type(), platform::CPUPlace());
   }
 };
 

paddle/fluid/operators/detection/multiclass_nms_op.cc

@@ -65,8 +65,7 @@ class MultiClassNMSOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
     return framework::OpKernelType(
-        framework::ToDataType(
-            ctx.Input<framework::LoDTensor>("Scores")->type()),
+        ctx.Input<framework::LoDTensor>("Scores")->type(),
         platform::CPUPlace());
   }
 };

paddle/fluid/operators/detection/prior_box_op.cc

@@ -72,8 +72,7 @@ class PriorBoxOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
     return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::Tensor>("Input")->type()),
-        ctx.device_context());
+        ctx.Input<framework::Tensor>("Input")->type(), ctx.device_context());
   }
 };
 

paddle/fluid/operators/detection/roi_perspective_transform_op.cc

@@ -498,9 +498,8 @@ class ROIPerspectiveTransformOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::Tensor>("X")->type()),
-        ctx.device_context());
+    return framework::OpKernelType(ctx.Input<framework::Tensor>("X")->type(),
+                                   ctx.device_context());
   }
 };
 
@@ -519,9 +518,8 @@ class ROIPerspectiveTransformGradOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::Tensor>("X")->type()),
-        ctx.device_context());
+    return framework::OpKernelType(ctx.Input<framework::Tensor>("X")->type(),
+                                   ctx.device_context());
   }
 };
 

paddle/fluid/operators/detection/rpn_target_assign_op.cc

@@ -78,8 +78,7 @@ class RpnTargetAssignOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
     return framework::OpKernelType(
-        framework::ToDataType(
-            ctx.Input<framework::LoDTensor>("Anchor")->type()),
+        ctx.Input<framework::LoDTensor>("Anchor")->type(),
         platform::CPUPlace());
   }
 };

paddle/fluid/operators/detection/target_assign_op.cc

@@ -57,9 +57,8 @@ class TargetAssignOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::LoDTensor>("X")->type()),
-        ctx.device_context());
+    return framework::OpKernelType(ctx.Input<framework::LoDTensor>("X")->type(),
+                                   ctx.device_context());
   }
 };
 

paddle/fluid/operators/detection_map_op.cc

@@ -71,8 +71,7 @@ class DetectionMAPOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
     return framework::OpKernelType(
-        framework::ToDataType(
-            ctx.Input<framework::Tensor>("DetectRes")->type()),
+        ctx.Input<framework::Tensor>("DetectRes")->type(),
         platform::CPUPlace());
   }
 };

paddle/fluid/operators/distributed/grpc_serde.cc

@@ -115,8 +115,7 @@ void SerializeToByteBuffer(const std::string& name, framework::Variable* var,
   if (var->IsType<framework::SelectedRows>()) {
     auto* slr = var->GetMutable<framework::SelectedRows>();
     ProtoEncodeHelper e2(static_cast<char*>(buf), 128);
-    size_t rows_memory_size =
-        slr->rows().size() * framework::SizeOfType(typeid(int64_t));
+    size_t rows_memory_size = slr->rows().size() * sizeof(int64_t);
     e2.WriteVarlengthBeginning(VarMsg::kRowsFieldNumber, rows_memory_size);
     slices[2] = ::grpc::Slice(e2.size());
     memcpy(const_cast<uint8_t*>(slices[2].begin()), e2.data(), e2.size());

paddle/fluid/operators/distributed/sendrecvop_utils.cc

@@ -61,8 +61,7 @@ TensorPayload GetTensorPayload(framework::Variable* var,
   auto tensor = var->Get<framework::LoDTensor>();
   // FIXME(wuyi): data types in send_recv.proto is copied from
   // framework.proto
-  request->set_data_type(
-      static_cast<VarMsg::Type>(framework::ToDataType(tensor.type())));
+  request->set_data_type(static_cast<VarMsg::Type>(tensor.type()));
   for (auto& dim : framework::vectorize(tensor.dims())) {
     request->add_dims(dim);
   }
@@ -83,8 +82,7 @@ TensorPayload GetSelectedRowsPayload(framework::Variable* var,
                                      const platform::DeviceContext& ctx,
                                      VarMsg* request) {
   auto* slr = var->GetMutable<framework::SelectedRows>();
-  request->set_data_type(
-      static_cast<VarMsg::Type>(framework::ToDataType(slr->value().type())));
+  request->set_data_type(static_cast<VarMsg::Type>(slr->value().type()));
   request->set_lod_level(0);
   request->set_slr_height(slr->height());
 

paddle/fluid/operators/distributed/sendrecvop_utils.h

@@ -65,18 +65,19 @@ TensorPayload GetSelectedRowsPayload(framework::Variable* var,
                                      const platform::DeviceContext& ctx,
                                      VarMsg* request);
 
-inline std::type_index ToTypeIndex(sendrecv::VariableMessage::Type type) {
+inline framework::proto::VarType::Type ToVarType(
+    sendrecv::VariableMessage::Type type) {
   switch (type) {
     case sendrecv::VariableMessage::FP32:
-      return typeid(float);  // NOLINT
+      return framework::proto::VarType::FP32;  // NOLINT
     case sendrecv::VariableMessage::FP64:
-      return typeid(double);  // NOLINT
+      return framework::proto::VarType::FP64;  // NOLINT
     case sendrecv::VariableMessage::INT32:
-      return typeid(int);  // NOLINT
+      return framework::proto::VarType::INT32;  // NOLINT
     case sendrecv::VariableMessage::INT64:
-      return typeid(int64_t);  // NOLINT
+      return framework::proto::VarType::INT64;  // NOLINT
     case sendrecv::VariableMessage::BOOL:
-      return typeid(bool);  // NOLINT
+      return framework::proto::VarType::BOOL;  // NOLINT
     default:
       PADDLE_THROW("Not support type %d", type);
   }

paddle/fluid/operators/distributed/variable_response.cc

@@ -114,7 +114,7 @@ bool VariableResponse::CopyLodTensorData(
   tensor->set_lod(lod);
 
   void* tensor_data =
-      tensor->mutable_data(ctx.GetPlace(), ToTypeIndex(meta_.data_type()));
+      tensor->mutable_data(ctx.GetPlace(), ToVarType(meta_.data_type()));
 
   VLOG(6) << "Tensor.memory_size = " << tensor->memory_size()
           << ", Buffer Size = " << length;
@@ -139,13 +139,13 @@ bool VariableResponse::CopySelectRowsTensorData(
   slr->set_height(meta_.slr_height());
   auto* tensor = slr->mutable_value();
   tensor->Resize(dims);
-  PADDLE_ENFORCE_EQ(static_cast<size_t>(tensor->numel()),
-                    length / framework::SizeOfType(
-                                 paddle::operators::distributed::ToTypeIndex(
-                                     meta_.data_type())));
+  PADDLE_ENFORCE_EQ(
+      static_cast<size_t>(tensor->numel()),
+      length / framework::SizeOfType(paddle::operators::distributed::ToVarType(
+                   meta_.data_type())));
   void* tensor_data = tensor->mutable_data(
       ctx.GetPlace(),
-      paddle::operators::distributed::ToTypeIndex(meta_.data_type()));
+      paddle::operators::distributed::ToVarType(meta_.data_type()));
 
   if (!ReadRaw(input, ctx, tensor->place(), tensor_data, length)) {
     return false;
@@ -159,8 +159,7 @@ bool VariableResponse::CopySelectRowsData(
     const platform::DeviceContext& ctx, int length) {
   auto* slr = GetVar()->GetMutable<framework::SelectedRows>();
   slr->mutable_rows()->clear();
-  slr->mutable_rows()->resize(length /
-                              framework::SizeOfType(typeid(int64_t)));  // int64
+  slr->mutable_rows()->resize(length / sizeof(int64_t));  // int64
   int64_t* rows_data = slr->mutable_rows()->data();
 
   // copy rows CPU data, GPU data will be copied lazily.

paddle/fluid/operators/distributed_ops/merge_ids_op.cc

@@ -108,9 +108,7 @@ class MergeIdsOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
     return framework::OpKernelType(
-        framework::ToDataType(
-            ctx.MultiInput<framework::Tensor>("X").front()->type()),
-        ctx.GetPlace());
+        ctx.MultiInput<framework::Tensor>("X").front()->type(), ctx.GetPlace());
   }
 };
 

paddle/fluid/operators/distributed_ops/ref_by_trainer_id_op.cc

@@ -42,9 +42,7 @@ class RefByTrainerIdOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
     return framework::OpKernelType(
-        framework::ToDataType(
-            ctx.MultiInput<framework::Tensor>("X")[0]->type()),
-        ctx.GetPlace());
+        ctx.MultiInput<framework::Tensor>("X")[0]->type(), ctx.GetPlace());
   }
 };
 

paddle/fluid/operators/elementwise/elementwise_op.h

@@ -197,8 +197,8 @@ class ElementwiseOpGrad : public framework::OperatorWithKernel {
 
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
-    auto input_data_type = framework::ToDataType(
-        ctx.Input<Tensor>(framework::GradVarName("Out"))->type());
+    auto input_data_type =
+        ctx.Input<Tensor>(framework::GradVarName("Out"))->type();
 
 #ifdef PADDLE_WITH_MKLDNN
     if (platform::CanMKLDNNBeUsed(ctx)) {

paddle/fluid/operators/fake_quantize_op.cc

@@ -115,9 +115,8 @@ class FakeQuantizeAbsMaxOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::LoDTensor>("X")->type()),
-        ctx.device_context());
+    return framework::OpKernelType(ctx.Input<framework::LoDTensor>("X")->type(),
+                                   ctx.device_context());
   }
 };
 
@@ -175,9 +174,8 @@ class FakeQuantizeRangeAbsMaxOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::LoDTensor>("X")->type()),
-        ctx.device_context());
+    return framework::OpKernelType(ctx.Input<framework::LoDTensor>("X")->type(),
+                                   ctx.device_context());
   }
 };
 

paddle/fluid/operators/fc_op.cc

@@ -79,9 +79,8 @@ framework::OpKernelType FCOp::GetExpectedKernelType(
     library = framework::LibraryType::kMKLDNN;
     layout = framework::DataLayout::kMKLDNN;
   }
-  return framework::OpKernelType(
-      framework::ToDataType(ctx.Input<Tensor>("Input")->type()), ctx.GetPlace(),
-      layout, library);
+  return framework::OpKernelType(ctx.Input<Tensor>("Input")->type(),
+                                 ctx.GetPlace(), layout, library);
 }
 
 void FCOpGrad::InferShape(framework::InferShapeContext* ctx) const {
@@ -111,9 +110,8 @@ framework::OpKernelType FCOpGrad::GetExpectedKernelType(
     library = framework::LibraryType::kMKLDNN;
     layout = framework::DataLayout::kMKLDNN;
   }
-  return framework::OpKernelType(
-      framework::ToDataType(ctx.Input<Tensor>("Input")->type()), ctx.GetPlace(),
-      layout, library);
+  return framework::OpKernelType(ctx.Input<Tensor>("Input")->type(),
+                                 ctx.GetPlace(), layout, library);
 }
 
 void FCOpMaker::Make() {

paddle/fluid/operators/fill_constant_op.cc

@@ -59,9 +59,9 @@ class FillConstantOp : public framework::OperatorBase {
 
     if (force_cpu) {
       auto cpu = platform::CPUPlace();
-      tensor->mutable_data(cpu, framework::ToTypeIndex(data_type));
+      tensor->mutable_data(cpu, data_type);
     } else {
-      tensor->mutable_data(dev_place, framework::ToTypeIndex(data_type));
+      tensor->mutable_data(dev_place, data_type);
     }
 
     platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();

paddle/fluid/operators/fill_op.cc

@@ -55,7 +55,7 @@ class FillOp : public framework::OperatorBase {
         static_cast<framework::proto::VarType::Type>(Attr<int>("dtype"));
     platform::CPUPlace cpu;
     auto force_cpu = Attr<bool>("force_cpu");
-    out.mutable_data(force_cpu ? cpu : place, framework::ToTypeIndex(dtype));
+    out.mutable_data(force_cpu ? cpu : place, dtype);
 
     framework::LoDTensor tensor;
 
@@ -64,7 +64,7 @@ class FillOp : public framework::OperatorBase {
     } else {
       // Always make tensor in CPU memory.
       tensor.Resize(out.dims());
-      tensor.mutable_data(cpu, framework::ToTypeIndex(dtype));
+      tensor.mutable_data(cpu, dtype);
     }
 
     framework::VisitDataType(

paddle/fluid/operators/fused/fused_elemwise_activation_op.cc

@@ -135,9 +135,8 @@ class FusedElemwiseActivationOp : public framework::OperatorWithKernel {
     PADDLE_ENFORCE_EQ(ctx.Input<framework::Tensor>("X")->type(),
                       ctx.Input<framework::Tensor>("Y")->type(),
                       "The element's type of input should be the same.");
-    auto input_data_type =
-        framework::ToDataType(ctx.Input<framework::Tensor>("X")->type());
-    return framework::OpKernelType(input_data_type, ctx.GetPlace());
+    return framework::OpKernelType(ctx.Input<framework::Tensor>("X")->type(),
+                                   ctx.GetPlace());
   }
 };
 
@@ -324,9 +323,8 @@ class FusedElemwiseActivationOpGrad : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
-    auto input_data_type_index = ctx.Input<framework::Tensor>("Y")->type();
-    auto input_data_type = framework::ToDataType(input_data_type_index);
-    return framework::OpKernelType(input_data_type, ctx.GetPlace());
+    return framework::OpKernelType(ctx.Input<framework::Tensor>("Y")->type(),
+                                   ctx.GetPlace());
   }
 };
 }  // namespace operators

paddle/fluid/operators/fused/fused_embedding_fc_lstm_op.cc

@@ -115,8 +115,7 @@ void FusedEmbeddingFCLSTMOp::InferShape(
 framework::OpKernelType FusedEmbeddingFCLSTMOp::GetExpectedKernelType(
     const framework::ExecutionContext& ctx) const {
   return framework::OpKernelType(
-      framework::ToDataType(
-          ctx.Input<framework::LoDTensor>("Embeddings")->type()),
+      ctx.Input<framework::LoDTensor>("Embeddings")->type(),
       ctx.device_context());
 }
 

paddle/fluid/operators/fused/fusion_gru_op.cc

@@ -93,9 +93,8 @@ void FusionGRUOp::InferShape(framework::InferShapeContext* ctx) const {
 
 framework::OpKernelType FusionGRUOp::GetExpectedKernelType(
     const framework::ExecutionContext& ctx) const {
-  return framework::OpKernelType(
-      framework::ToDataType(ctx.Input<framework::LoDTensor>("X")->type()),
-      ctx.device_context());
+  return framework::OpKernelType(ctx.Input<framework::LoDTensor>("X")->type(),
+                                 ctx.device_context());
 }
 
 void FusionGRUOpMaker::Make() {

paddle/fluid/operators/fused/fusion_lstm_op.cc

@@ -117,9 +117,8 @@ void FusionLSTMOp::InferShape(framework::InferShapeContext* ctx) const {
 
 framework::OpKernelType FusionLSTMOp::GetExpectedKernelType(
     const framework::ExecutionContext& ctx) const {
-  return framework::OpKernelType(
-      framework::ToDataType(ctx.Input<framework::LoDTensor>("X")->type()),
-      ctx.device_context());
+  return framework::OpKernelType(ctx.Input<framework::LoDTensor>("X")->type(),
+                                 ctx.device_context());
 }
 
 void FusionLSTMOpMaker::Make() {

paddle/fluid/operators/fused/fusion_seqconv_eltadd_relu_op.cc

@@ -61,9 +61,8 @@ void FusionSeqConvEltAddReluOp::InferShape(
 
 framework::OpKernelType FusionSeqConvEltAddReluOp::GetExpectedKernelType(
     const framework::ExecutionContext& ctx) const {
-  return framework::OpKernelType(
-      framework::ToDataType(ctx.Input<framework::LoDTensor>("X")->type()),
-      ctx.device_context());
+  return framework::OpKernelType(ctx.Input<framework::LoDTensor>("X")->type(),
+                                 ctx.device_context());
 }
 
 void FusionSeqConvEltAddReluOpMaker::Make() {

paddle/fluid/operators/fused/fusion_seqexpand_concat_fc_op.cc

@@ -67,9 +67,8 @@ void FusionSeqExpandConcatFCOp::InferShape(
 
 framework::OpKernelType FusionSeqExpandConcatFCOp::GetExpectedKernelType(
     const framework::ExecutionContext& ctx) const {
-  return framework::OpKernelType(
-      framework::ToDataType(ctx.MultiInput<LoDTensor>("X")[0]->type()),
-      ctx.device_context());
+  return framework::OpKernelType(ctx.MultiInput<LoDTensor>("X")[0]->type(),
+                                 ctx.device_context());
 }
 
 void FusionSeqExpandConcatFCOpMaker::Make() {

paddle/fluid/operators/gather_op.cc

@@ -42,9 +42,8 @@ class GatherOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("X")->type()),
-        ctx.device_context());
+    return framework::OpKernelType(ctx.Input<Tensor>("X")->type(),
+                                   ctx.device_context());
   }
 };
 
@@ -60,9 +59,8 @@ class GatherGradOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("X")->type()),
-        ctx.device_context());
+    return framework::OpKernelType(ctx.Input<Tensor>("X")->type(),
+                                   ctx.device_context());
   }
 };
 

paddle/fluid/operators/grid_sampler_op.cc

@@ -63,9 +63,9 @@ class GridSampleOp : public framework::OperatorWithKernel {
       library_ = framework::LibraryType::kCUDNN;
     }
 #endif
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("X")->type()), ctx.GetPlace(),
-        framework::DataLayout::kAnyLayout, library_);
+    return framework::OpKernelType(ctx.Input<Tensor>("X")->type(),
+                                   ctx.GetPlace(),
+                                   framework::DataLayout::kAnyLayout, library_);
   }
 };
 
@@ -159,9 +159,9 @@ class GridSampleOpGrad : public framework::OperatorWithKernel {
       library_ = framework::LibraryType::kCUDNN;
     }
 #endif
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("X")->type()), ctx.GetPlace(),
-        framework::DataLayout::kAnyLayout, library_);
+    return framework::OpKernelType(ctx.Input<Tensor>("X")->type(),
+                                   ctx.GetPlace(),
+                                   framework::DataLayout::kAnyLayout, library_);
   }
 };
 

paddle/fluid/operators/group_norm_op.cc

@@ -141,8 +141,7 @@ class GroupNormGradOp : public framework::OperatorWithKernel {
     if (t == nullptr) {
       PADDLE_THROW("can't find Y@GRAD");
     }
-    return framework::OpKernelType(framework::ToDataType(t->type()),
-                                   ctx.GetPlace());
+    return framework::OpKernelType(t->type(), ctx.GetPlace());
   }
 };
 

paddle/fluid/operators/hierarchical_sigmoid_op.cc

@@ -76,9 +76,8 @@ class HierarchicalSigmoidOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::LoDTensor>("X")->type()),
-        ctx.GetPlace());
+    return framework::OpKernelType(ctx.Input<framework::LoDTensor>("X")->type(),
+                                   ctx.GetPlace());
   }
 };
 
@@ -163,9 +162,8 @@ class HierarchicalSigmoidGradOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::LoDTensor>("X")->type()),
-        ctx.GetPlace());
+    return framework::OpKernelType(ctx.Input<framework::LoDTensor>("X")->type(),
+                                   ctx.GetPlace());
   }
 };
 

paddle/fluid/operators/interpolate_op.cc

@@ -55,8 +55,8 @@ class InterpolateOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("X")->type()), ctx.GetPlace());
+    return framework::OpKernelType(ctx.Input<Tensor>("X")->type(),
+                                   ctx.GetPlace());
   }
 };
 
@@ -124,8 +124,8 @@ class InterpolateOpGrad : public framework::OperatorWithKernel {
 
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("X")->type()), ctx.GetPlace());
+    return framework::OpKernelType(ctx.Input<Tensor>("X")->type(),
+                                   ctx.GetPlace());
   }
 };
 

paddle/fluid/operators/is_empty_op.cc

@@ -35,8 +35,7 @@ class IsEmptyOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
     framework::OpKernelType kt = framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::LoDTensor>("X")->type()),
-        platform::CPUPlace());
+        ctx.Input<framework::LoDTensor>("X")->type(), platform::CPUPlace());
     return kt;
   }
 };

paddle/fluid/operators/isfinite_op.cc

@@ -40,10 +40,9 @@ class OverflowOp : public framework::OperatorWithKernel {
     int dtype = -1;
     auto *x_var = ctx.InputVar("X");
     if (x_var->IsType<framework::LoDTensor>()) {
-      dtype = framework::ToDataType(x_var->Get<framework::LoDTensor>().type());
+      dtype = x_var->Get<framework::LoDTensor>().type();
     } else if (x_var->IsType<framework::SelectedRows>()) {
-      dtype = framework::ToDataType(
-          x_var->Get<framework::SelectedRows>().value().type());
+      dtype = x_var->Get<framework::SelectedRows>().value().type();
     } else {
       PADDLE_THROW("Cannot find the input data type by all input data");
     }

paddle/fluid/operators/layer_norm_op.cc

@@ -153,8 +153,7 @@ class LayerNormGradOp : public framework::OperatorWithKernel {
     if (t == nullptr) {
       PADDLE_THROW("can't find Y@GRAD");
     }
-    return framework::OpKernelType(framework::ToDataType(t->type()),
-                                   ctx.GetPlace());
+    return framework::OpKernelType(t->type(), ctx.GetPlace());
   }
 };
 

paddle/fluid/operators/linear_chain_crf_op.cc

@@ -184,9 +184,8 @@ class LinearChainCRFOp : public framework::OperatorWithKernel {
   // is determined by its input "Emission".
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<LoDTensor>("Emission")->type()),
-        platform::CPUPlace());
+    return framework::OpKernelType(ctx.Input<LoDTensor>("Emission")->type(),
+                                   platform::CPUPlace());
   }
 };
 
@@ -244,9 +243,7 @@ class LinearChainCRFGradOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
     return framework::OpKernelType(
-        framework::ToDataType(
-            ctx.Input<LoDTensor>(framework::GradVarName("LogLikelihood"))
-                ->type()),
+        ctx.Input<LoDTensor>(framework::GradVarName("LogLikelihood"))->type(),
         platform::CPUPlace());
   }
 };

paddle/fluid/operators/load_combine_op.cc

@@ -69,7 +69,7 @@ class LoadCombineOp : public framework::OperatorBase {
       // Get data from fin to tensor
       DeserializeFromStream(*buffer, tensor, dev_ctx);
 
-      auto in_dtype = framework::ToDataType(tensor->type());
+      auto in_dtype = tensor->type();
       auto out_dtype =
           load_as_fp16 ? framework::proto::VarType::FP16 : in_dtype;
 

paddle/fluid/operators/load_op.cc

@@ -65,7 +65,7 @@ class LoadOp : public framework::OperatorBase {
     DeserializeFromStream(fin, tensor, dev_ctx);
 
     auto load_as_fp16 = Attr<bool>("load_as_fp16");
-    auto in_dtype = framework::ToDataType(tensor->type());
+    auto in_dtype = tensor->type();
     auto out_dtype = load_as_fp16 ? framework::proto::VarType::FP16 : in_dtype;
 
     if (in_dtype != out_dtype) {

paddle/fluid/operators/lod_reset_op.cc

@@ -39,9 +39,8 @@ class LoDResetOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::LoDTensor>("X")->type()),
-        ctx.device_context());
+    return framework::OpKernelType(ctx.Input<framework::LoDTensor>("X")->type(),
+                                   ctx.device_context());
   }
 };
 
@@ -144,9 +143,8 @@ class LoDResetGradOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::LoDTensor>("X")->type()),
-        ctx.device_context());
+    return framework::OpKernelType(ctx.Input<framework::LoDTensor>("X")->type(),
+                                   ctx.device_context());
   }
 };
 

paddle/fluid/operators/lod_tensor_to_array_op.cc

@@ -72,7 +72,7 @@ struct LoDTensorToArrayFunctor : public boost::static_visitor<void> {
     LoDTensorToArrayFunctorImpl<DeviceContext> func;
     func.prev_functor_ = this;
     func.dev_ctx_ = dev_ctx;
-    framework::VisitDataType(framework::ToDataType(input_.type()), func);
+    framework::VisitDataType(input_.type(), func);
   }
 };
 

paddle/fluid/operators/lookup_sparse_table_op.cc

@@ -63,8 +63,7 @@ class LookupSparseTableOp : public framework::OperatorBase {
     out_shape[0] = ids_t.numel();
     out_t->Resize(out_shape);
     out_t->mutable_data(cpu, w_t->value().type());
-    PADDLE_ENFORCE_EQ(framework::ToDataType(w_t->value().type()),
-                      framework::proto::VarType::FP32,
+    PADDLE_ENFORCE_EQ(w_t->value().type(), framework::proto::VarType::FP32,
                       "The sparse table only support FP32");
     w_t->Get(ids_t, out_t, true, is_test);
     out_t->set_lod(ids_t.lod());

paddle/fluid/operators/lrn_op.cc

@@ -145,9 +145,8 @@ framework::OpKernelType GetExpectedLRNKernel(
   }
 #endif
 
-  return framework::OpKernelType(
-      framework::ToDataType(ctx.Input<Tensor>("X")->type()), ctx.GetPlace(),
-      layout_, library_);
+  return framework::OpKernelType(ctx.Input<Tensor>("X")->type(), ctx.GetPlace(),
+                                 layout_, library_);
 }
 }  // namespace
 

paddle/fluid/operators/lstm_op.cc

@@ -96,8 +96,7 @@ class LSTMOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
     return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::LoDTensor>("Input")->type()),
-        ctx.device_context());
+        ctx.Input<framework::LoDTensor>("Input")->type(), ctx.device_context());
   }
 };
 
@@ -261,8 +260,7 @@ class LSTMGradOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
     return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::LoDTensor>("Input")->type()),
-        ctx.device_context());
+        ctx.Input<framework::LoDTensor>("Input")->type(), ctx.device_context());
   }
 };
 

paddle/fluid/operators/lstmp_op.cc

@@ -113,8 +113,7 @@ class LSTMPOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
     return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::LoDTensor>("Input")->type()),
-        ctx.device_context());
+        ctx.Input<framework::LoDTensor>("Input")->type(), ctx.device_context());
   }
 };
 
@@ -312,8 +311,7 @@ class LSTMPGradOp : public framework::OperatorWithKernel {
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
     return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<framework::LoDTensor>("Input")->type()),
-        ctx.device_context());
+        ctx.Input<framework::LoDTensor>("Input")->type(), ctx.device_context());
   }
 };
 

paddle/fluid/operators/math/math_function.cc

@@ -77,16 +77,14 @@ template <>
 void set_constant_with_place<platform::CPUPlace>(
     const platform::DeviceContext& context, framework::Tensor* tensor,
     float value) {
-  framework::VisitDataType(framework::ToDataType(tensor->type()),
-                           TensorSetConstantCPU(tensor, value));
+  framework::VisitDataType(tensor->type(), TensorSetConstantCPU(tensor, value));
 }
 
 template <>
 void set_constant_with_place<platform::CUDAPinnedPlace>(
     const platform::DeviceContext& context, framework::Tensor* tensor,
     float value) {
-  framework::VisitDataType(framework::ToDataType(tensor->type()),
-                           TensorSetConstantCPU(tensor, value));
+  framework::VisitDataType(tensor->type(), TensorSetConstantCPU(tensor, value));
 }
 
 struct TensorSetConstantWithPlace : public boost::static_visitor<void> {

paddle/fluid/operators/math/math_function.cu

@@ -65,7 +65,7 @@ template <>
 void set_constant_with_place<platform::CUDAPlace>(
     const platform::DeviceContext& context, framework::Tensor* tensor,
     float value) {
-  framework::VisitDataType(framework::ToDataType(tensor->type()),
+  framework::VisitDataType(tensor->type(),
                            TensorSetConstantGPU(context, tensor, value));
 }
 

paddle/fluid/operators/mean_iou_op.cc

@@ -44,9 +44,8 @@ class MeanIoUOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("Predictions")->type()),
-        ctx.GetPlace());
+    return framework::OpKernelType(ctx.Input<Tensor>("Predictions")->type(),
+                                   ctx.GetPlace());
   }
 };
 

paddle/fluid/operators/mean_op.cc

@@ -61,9 +61,7 @@ class MeanGradOp : public framework::OperatorWithKernel {
 
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    auto input_data_type =
-        framework::ToDataType(ctx.Input<Tensor>("X")->type());
-
+    auto input_data_type = ctx.Input<Tensor>("X")->type();
     return framework::OpKernelType(input_data_type, ctx.GetPlace());
   }
 };

paddle/fluid/operators/merge_lod_tensor_op.cc

@@ -63,9 +63,7 @@ class MergeLoDTensorOp : public framework::OperatorBase {
 
     platform::Place place = dev_place;
     int64_t batch_size = in_true.dims()[0] + in_false.dims()[0];
-
-    std::type_index data_type =
-        in_true.IsInitialized() ? in_true.type() : in_false.type();
+    auto data_type = in_true.IsInitialized() ? in_true.type() : in_false.type();
     int rank;
     framework::DDim in_dims;
     if (in_true.IsInitialized()) {

paddle/fluid/operators/metrics/accuracy_op.cc

@@ -55,9 +55,8 @@ class AccuracyOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("Out")->type()),
-        ctx.GetPlace());
+    return framework::OpKernelType(ctx.Input<Tensor>("Out")->type(),
+                                   ctx.GetPlace());
   }
 };
 

paddle/fluid/operators/metrics/auc_op.cc

@@ -51,9 +51,8 @@ class AucOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("Predict")->type()),
-        platform::CPUPlace());
+    return framework::OpKernelType(ctx.Input<Tensor>("Predict")->type(),
+                                   platform::CPUPlace());
   }
 };
 

paddle/fluid/operators/metrics/precision_recall_op.cc

@@ -82,9 +82,8 @@ class PrecisionRecallOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("MaxProbs")->type()),
-        ctx.device_context());
+    return framework::OpKernelType(ctx.Input<Tensor>("MaxProbs")->type(),
+                                   ctx.device_context());
   }
 };
 

paddle/fluid/operators/multiplex_op.cc

@@ -53,9 +53,8 @@ class MultiplexOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.MultiInput<Tensor>("X")[0]->type()),
-        ctx.device_context());
+    return framework::OpKernelType(ctx.MultiInput<Tensor>("X")[0]->type(),
+                                   ctx.device_context());
   }
 };
 
@@ -123,9 +122,8 @@ class MultiplexGradOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext& ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.MultiInput<Tensor>("X")[0]->type()),
-        ctx.device_context());
+    return framework::OpKernelType(ctx.MultiInput<Tensor>("X")[0]->type(),
+                                   ctx.device_context());
   }
 };
 

paddle/fluid/operators/nce_op.cc

@@ -69,9 +69,8 @@ class NCEOp : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("Input")->type()),
-        platform::CPUPlace());
+    return framework::OpKernelType(ctx.Input<Tensor>("Input")->type(),
+                                   platform::CPUPlace());
   }
 };
 
@@ -214,9 +213,8 @@ class NCEOpGrad : public framework::OperatorWithKernel {
  protected:
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
-    return framework::OpKernelType(
-        framework::ToDataType(ctx.Input<Tensor>("Input")->type()),
-        platform::CPUPlace());
+    return framework::OpKernelType(ctx.Input<Tensor>("Input")->type(),
+                                   platform::CPUPlace());
   }
 };
 

paddle/fluid/operators/optimizers/adadelta_op.cc

@@ -70,9 +70,8 @@ class AdadeltaOp : public framework::OperatorWithKernel {
 
   framework::OpKernelType GetExpectedKernelType(
       const framework::ExecutionContext &ctx) const override {
-    auto input_data_type =
-        framework::ToDataType(ctx.Input<Tensor>("Param")->type());
-    return framework::OpKernelType(input_data_type, ctx.GetPlace());
+    return framework::OpKernelType(ctx.Input<Tensor>("Param")->type(),
+                                   ctx.GetPlace());
   }
 };