refactor TypeSystem

make typesystem simpler

paddle/fluid/CMakeLists.txt

@@ -13,3 +13,5 @@ add_subdirectory(pybind)
 add_subdirectory(train)
 # NOTE: please add subdirectory inference at last.
 add_subdirectory(inference)
+
+add_subdirectory(lite)

paddle/fluid/framework/tensor.h

@@ -80,6 +80,8 @@ class Tensor {
   template <typename T>
   const T* data() const;
 
+  const void* raw_data() const { return holder_->ptr(); }
+
   inline bool IsInitialized() const;
 
   /**

paddle/fluid/inference/analysis/dot.h

@@ -24,6 +24,9 @@
 #include <unordered_map>
 #include <vector>
 #include "paddle/fluid/lite/utils/logging.h"
+#ifndef LITE_WITH_LIGHT_WEIGHT_FRAMEWORK
+#include <glog/logging.h>
+#endif
 
 namespace paddle {
 namespace inference {

paddle/fluid/lite/CMakeLists.txt

@@ -2,6 +2,11 @@ if (NOT WITH_LITE)
     return()
 endif()
 
+message(WARNING "Enable Lite")
+message(STATUS "LIGHT_FRAMEWORK: ${LITE_WITH_LIGHT_WEIGHT_FRAMEWORK}")
+message(STATUS "LITE_WITH_CUDA: ${LITE_WITH_CUDA}")
+message(STATUS "LITE_WITH_X86: ${LITE_WITH_X86}")
+
 add_subdirectory(core)
 add_subdirectory(x86)
 add_subdirectory(host)

paddle/fluid/lite/api/cxx_api_bin.cc

+// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
 #include "paddle/fluid/lite/api/cxx_api.h"
 #include "paddle/fluid/lite/core/mir/passes.h"
 #include "paddle/fluid/lite/core/op_registry.h"
@@ -45,14 +59,13 @@ void Run(const char* model_dir) {
 }  // namespace lite
 }  // namespace paddle
 
-int main(int argc, char** argv ) {
+int main(int argc, char** argv) {
   CHECK_EQ(argc, 2) << "usage: ./cmd <model_dir>";
   paddle::lite::Run(argv[1]);
 
   return 0;
 }
 
-
 USE_LITE_OP(mul);
 USE_LITE_OP(fc);
 USE_LITE_OP(scale);

paddle/fluid/lite/core/CMakeLists.txt

@@ -13,7 +13,7 @@ else()
   set(tensor_lite hvy_tensor)
 endif()
 
-proto_library(framework_proto SRCS framework.proto)
+proto_library(framework_proto_lite SRCS framework.proto)
 
 cc_library(kernel_lite SRCS kernel.cc DEPS type_system target_wrapper_lite)
 cc_library(variable_lite SRCS variable.cc)
@@ -22,7 +22,7 @@ cc_library(scope_lite SRCS scope.cc)
 cc_library(context_lite SRCS context.cc DEPS any_lite)
 cc_library(op_lite SRCS op_lite.cc DEPS scope_lite op_registry_lite compatible_pb_lite)
 cc_library(types_lite SRCS types.cc)
-cc_library(type_system SRCS type_system.cc DEPS ${tensor_lite})
+cc_library(type_system SRCS type_system.cc DEPS ${tensor_lite} target_wrapper_lite)
 
 cc_library(kernel_executor_lite SRCS kernel_executor.cc DEPS mir_ssa_graph kernel_lite)
 cc_library(program_lite SRCS program.cc DEPS op_lite kernel_lite)
@@ -37,14 +37,14 @@ endif()
 
 cc_library(program_fake_utils SRCS program_fake_utils.cc DEPS mir_ssa_graph
         scope_lite op_registry_lite proto_desc op_lite
-        ops_lite
-        host_kernels
+        ${ops_lite}
+        ${host_kernels}
         )
 
 lite_cc_test(test_scope_lite SRCS scope_test.cc DEPS scope_lite)
 lite_cc_test(test_kernel_lite SRCS kernel_test.cc DEPS kernel_lite target_wrapper_x86)
 lite_cc_test(test_op_lite SRCS op_lite_test.cc DEPS op_lite)
 lite_cc_test(test_tensor_lite SRCS lite_tensor_test.cc DEPS lite_tensor)
-lite_cc_test(test_type_system SRCS type_system_test.cc DEPS type_system)
+lite_cc_test(test_type_system SRCS type_system_test.cc DEPS type_system utils_lite)
 lite_cc_test(test_optimizer_lite SRCS optimizer_test.cc DEPS mir_pass_manager program_fake_utils mir_passes)
 lite_cc_test(test_types_lite SRCS types_test.cc DEPS types_lite)

paddle/fluid/lite/core/hvy_tensor.h

@@ -83,6 +83,8 @@ class TensorHvy : public TensorBase<TensorHvy> {
     return data_.data<T>();
   }
 
+  const void* raw_data() const { return data_.raw_data(); }
+
   template <typename DimT>
   void Resize(const DimT& dims) {
     LOG(INFO) << "dims.size " << dims.size();

paddle/fluid/lite/core/mir/CMakeLists.txt

@@ -22,15 +22,15 @@ endif()
 cc_test(test_mir_pass_manager SRCS pass_manager_test.cc DEPS mir_pass_manager mir_passes)
 cc_test(test_ssa_graph SRCS ssa_graph_test.cc DEPS
         mir_ssa_graph scope_lite op_lite
-        ops_lite
-        host_kernels
+        ${ops_lite}
+        ${host_kernels}
         mir_passes
         mir_pass_manager
         program_fake_utils
         )
 set(test_variable_place_infrence_pass_DEPS
-        ops_lite
-        host_kernels
+        ${ops_lite}
+        ${host_kernels}
         mir_passes
         mir_pass_manager
         optimizer_lite

paddle/fluid/lite/core/mir/runtime_context_assign_pass.cc

@@ -60,7 +60,7 @@ class RuntimeContextAssignPass : public StmtPass {
 #ifdef LITE_WITH_CUDA
   std::unique_ptr<KernelContext> NewCudaContext() {
     std::unique_ptr<KernelContext> ctx(new KernelContext);
-    auto& cuda = ctx->AsCudaContext();
+    auto& cuda = ctx->As<CUDAContext>();
     // Some initialization here.
     CHECK(cublas_fp32_) << "cublas_fp32 should be set first";
     cuda.blas_fp32 = cublas_fp32_;

paddle/fluid/lite/core/op_lite.cc

@@ -67,9 +67,8 @@ bool OpLite::Run() {
 
 bool OpLite::Attach(const OpDesc &opdesc, lite::Scope *scope) {
   // valid_places_.clear();
-  LOG(INFO) << "valid_places " << valid_places_.size();
   CHECK(scope != nullptr);
-  CHECK(!op_info_.get());
+  // CHECK(!op_info_.get());
   scope_ = scope;
   op_info_.reset(new OpInfo);  // Force clean the out-of-date infomation.
   op_info_->Build(opdesc.ReadonlyProto());

paddle/fluid/lite/core/op_lite.h

@@ -49,9 +49,7 @@ class OpInfo;
 class OpLite : public Registry {
  public:
   OpLite() = default;
-  OpLite(const std::string &type) : op_type_(type) {
-    LOG(INFO) << "valid places " << valid_places_.size();
-  }
+  OpLite(const std::string &type) : op_type_(type) {}
   OpLite(const std::vector<Place> &valid_places) : valid_places_(valid_places) {
     LOG(INFO) << "valid places " << valid_places.size();
   }

paddle/fluid/lite/core/op_registry.h

@@ -21,6 +21,8 @@
 #include "paddle/fluid/lite/core/target_wrapper.h"
 #include "paddle/fluid/lite/utils/all.h"
 
+using LiteType = paddle::lite::Type;
+
 namespace paddle {
 namespace lite {
 

paddle/fluid/lite/core/program.h

@@ -106,7 +106,7 @@ struct Instruct {
   void Run() {
     CHECK(op_);
     CHECK(kernel_);
-    if (UNLIKELY(first_epoch_)) {
+    if (first_epoch_) {
       first_epoch_ = false;
       CHECK(op_->CheckShape());
     }

paddle/fluid/lite/core/target_wrapper.h

@@ -48,32 +48,27 @@ enum class DataLayoutType : int {
 
 // Some helper macro to get a specific TargetType.
 #define TARGET(item__) paddle::lite::TargetType::item__
-#define TARGET_VAL(item__) static_cast<int>(TARGET(item__))
 // Some helper macro to get a specific PrecisionType.
 #define PRECISION(item__) paddle::lite::PrecisionType::item__
-#define PRECISION_VAL(item__) static_cast<int>(PRECISION(item__))
 #define DATALAYOUT(item__) paddle::lite::DataLayoutType::item__
 
-constexpr const int kNumPrecisions = PRECISION_VAL(NUM);
-constexpr const int kNumTargets = TARGET_VAL(NUM);
-
-static const std::string target2string[] = {"unk", "host", "x86", "cuda",
-                                            "any"};
 static const std::string& TargetToStr(TargetType target) {
+  static const std::string target2string[] = {"unk", "host", "x86", "cuda",
+                                              "any"};
   auto x = static_cast<int>(target);
   CHECK_LT(x, static_cast<int>(TARGET(NUM)));
   return target2string[x];
 }
 
-static const std::string precision2string[] = {"unk", "float", "int8", "any"};
 static const std::string& PrecisionToStr(PrecisionType precision) {
+  static const std::string precision2string[] = {"unk", "float", "int8", "any"};
   auto x = static_cast<int>(precision);
   CHECK_LT(x, static_cast<int>(PRECISION(NUM)));
   return precision2string[x];
 }
 
-static const std::string datalayout2string[] = {"unk", "NCHW", "any"};
 static const std::string& DataLayoutToStr(DataLayoutType layout) {
+  static const std::string datalayout2string[] = {"unk", "NCHW", "any"};
   auto x = static_cast<int>(layout);
   CHECK_LT(x, static_cast<int>(DATALAYOUT(NUM)));
   return datalayout2string[x];

paddle/fluid/lite/core/tensor.h

@@ -54,7 +54,7 @@ class DDimBase {
 
   value_type production() const {
     value_type res = 1;
-    for (int i = 0; i < const_self()->size(); i++) {
+    for (size_t i = 0; i < const_self()->size(); i++) {
       res *= (*const_self())[i];
     }
     return res;
@@ -142,6 +142,8 @@ class TensorBase {
     return const_self()->data();
   }
 
+  const void *raw_data() const { return const_self()->data(); }
+
   size_t data_size() const { return const_self()->dims().production(); }
 
   void ShareDataWith(const TensorBase &other) { self()->ShareDataWith(other); }

paddle/fluid/lite/core/type_system.cc

@@ -13,14 +13,10 @@
 // limitations under the License.
 
 #include "paddle/fluid/lite/core/type_system.h"
-#include "type_system.h"
 
 namespace paddle {
 namespace lite {
 
-// ------------------------- GetType specification ----------------------------
-// ------------------------- end GetType specification ------------------------
-
 size_t ParamTypeRegistry::KernelIdTy::hash() const {
   std::hash<std::string> h;
   size_t hash = h(kernel_type);
@@ -31,26 +27,21 @@ size_t ParamTypeRegistry::KernelIdTy::hash() const {
 }
 
 std::ostream &operator<<(std::ostream &os, const Type &other) {
-  if (other.IsUnsupported()) {
-    os << "<Unsupported>";
-    return os;
-  }
-  if (other.IsVoid()) {
-    os << "<Void>";
-    return os;
-  }
-  if (other.IsTensor()) {
-    os << "<Tensor:";
-  } else {
-    os << "<";
-  }
-  os << TargetToStr(other.target()) << "/" << PrecisionToStr(other.precision())
-     << "/" << DataLayoutToStr(other.layout()) << ">";
+  os << other.name();
   return os;
 }
 
+// An map is used to maintain a global repo for types. We don't use
+// MACROs with static variables for that the TypeSystem should only used in
+// compile time, that is not performance sensitive, and a map-based way is
+// easier to implement and maintain.
+//
+// The map is declared in each Type::GetXXX method other than in the Type class
+// so that it will force to construct before any usage.
+
 const Type *Type::GetTensorTy(TargetType target, PrecisionType precision,
                               DataLayoutType layout, int device) {
+  static std::map<size_t, const Type *> type_repo;
   // NOTE quite naive implementation here, but not performance sensitive.
   DataType::ID type_id = DataType::ID::Tensor;
 
@@ -72,17 +63,16 @@ const Type *Type::GetTensorTy(TargetType target, PrecisionType precision,
   name << device;
   name << ">";
 
-  auto it = type_repo_.find(v);
-  if (it == type_repo_.end()) {
+  if (!type_repo[v])
     // The Types should alive across the process life, no need to delete.
-    type_repo_[v] =
+    type_repo[v] =
         new Type(type_id, name.str(), target, precision, layout, device);
-  }
-  return type_repo_[v];
+  return type_repo[v];
 }
 
 const Type *Type::GetTensorListTy(TargetType target, PrecisionType precision,
                                   DataLayoutType layout, int device) {
+  static std::map<size_t, const Type *> type_repo;
   DataType::ID type_id = DataType::ID::TensorList;
 
 #define HASH_ONE(x) v = hash_combine(v, hasher(static_cast<int>(x)))
@@ -103,28 +93,50 @@ const Type *Type::GetTensorListTy(TargetType target, PrecisionType precision,
   name << device;
   name << ">";
 
-  if (!type_repo_[v])
+  if (!type_repo[v])
     // The Types should alive across the process life, no need to delete.
-    type_repo_[v] =
+    type_repo[v] =
         new Type(type_id, name.str(), target, precision, layout, device);
-  return type_repo_[v];
+  return type_repo[v];
 }
 
 const Type *Type::GetUnsupportedTy() {
+  static std::map<size_t, const Type *> type_repo;
   std::hash<int> hasher;
   size_t v = hasher(static_cast<int>(DataType::ID::Unsupported));
-  if (!type_repo_[v])
-    type_repo_[v] =
+  if (!type_repo[v])
+    type_repo[v] =
         new Type(DataType::ID::Unsupported, "Unsupported", TARGET(kUnk),
                  PRECISION(kUnk), DATALAYOUT(kUnk), -1);
+  return type_repo[v];
 }
 
 const Type *Type::GetVoidTy() {
+  static std::map<size_t, const Type *> type_repo;
   std::hash<int> hasher;
   size_t v = hasher(static_cast<int>(DataType::ID::Void));
-  if (!type_repo_[v])
-    type_repo_[v] = new Type(DataType::ID::Void, "Void", TARGET(kAny),
-                             PRECISION(kAny), DATALAYOUT(kAny), -1);
+  if (!type_repo[v])
+    type_repo[v] = new Type(DataType::ID::Void, "Void", TARGET(kAny),
+                            PRECISION(kAny), DATALAYOUT(kAny), -1);
+  return type_repo[v];
+}
+
+const Type *Type::Get(DataType::ID type_id, TargetType target,
+                      PrecisionType precision, DataLayoutType layout,
+                      int device) {
+  switch (type_id) {
+    case DataType::ID::Void:
+      return GetVoidTy();
+    case DataType::ID::Unsupported:
+      return GetUnsupportedTy();
+    case DataType::ID::Tensor:
+      return GetTensorTy(target, precision, layout, device);
+    case DataType::ID::TensorList:
+      return GetTensorListTy(target, precision, layout, device);
+    default:
+      LOG(FATAL) << "Unknown Type found";
+      return nullptr;
+  }
 }
 
 }  // namespace lite

paddle/fluid/lite/core/type_system.h

@@ -133,6 +133,11 @@ class Type : public DataType {
   /// Get an Void type.
   static const Type* GetVoidTy();
 
+  static const Type* Get(DataType::ID type_id, TargetType target = TARGET(kUnk),
+                         PrecisionType precision = PRECISION(kUnk),
+                         DataLayoutType layout = DATALAYOUT(kUnk),
+                         int device = 0);
+
   TargetType target() const { return place_.target; }
   PrecisionType precision() const { return place_.precision; }
   DataLayoutType layout() const { return place_.layout; }
@@ -154,12 +159,6 @@ class Type : public DataType {
        DataLayoutType layout = DataLayoutType::kNCHW, short device = 0)
       : DataType(id), place_{target, precision, layout, device}, name_(name) {}
 
-  // An map is used here to maintain a global repo for types. We don't use
-  // MACROs with static variables for that the TypeSystem should only used in
-  // compile time, that is not performance sensitive, and a map-based way is
-  // easier to implement and maintain.
-  static std::map<size_t, const Type*> type_repo_;
-
   Place place_;
   const std::string name_;
 };
@@ -203,22 +202,6 @@ static bool TypeCompatibleTo(const Type& a, const Type& b) {
          PrecisionCompatibleTo(a, b) && DeviceCompatibleTo(a, b);
 }
 
-// -------------------------------- predefined types ---------------------------
-// TODO(Superjomn) make all the Types' constructs protected to make sure there
-// is only one instance across the system.
-class VoidTy : public Type {
- public:
-  VoidTy() : Type(ID::Void, "Void") {}
-};
-class UnsupportedTy : public Type {
- public:
-  UnsupportedTy() : Type(ID::Unsupported, "Unsupported", false /*is_tensor*/) {}
-};
-
-const Type* LookupType(DataType::ID type_id, bool is_unknown, bool is_tensor,
-                       Place place);
-// ------------------------- end predefined types ---------------------------
-
 /*
  * ParamType is used to represent a data type of a parameter for the kernel. It
  * can represent any Variable data type.
@@ -226,13 +209,12 @@ const Type* LookupType(DataType::ID type_id, bool is_unknown, bool is_tensor,
  * registered in the `TypeSystem`.
  */
 struct ParamType {
-  Place tensor_place{};
   const Type* type;
 
   ParamType() = default;
-  ParamType(const Type* type) : type(type) { tensor_place = type->place(); }
+  ParamType(const Type* type) : type(type) {}
 
-  std::string DebugString() const { return tensor_place.DebugString(); }
+  std::string DebugString() const { return type->name(); }
 };
 
 /*

paddle/fluid/lite/core/type_system_test.cc

@@ -25,6 +25,10 @@ TEST(TypeSystem, CheckDuplicateGet) {
       Type::GetTensorTy(TARGET(kHost), PRECISION(kFloat), DATALAYOUT(kNCHW));
 
   ASSERT_EQ(tensor_ty, tensor_ty1);
+
+  ASSERT_EQ(tensor_ty->target(), TARGET(kHost));
+  ASSERT_EQ(tensor_ty->precision(), PRECISION(kFloat));
+  ASSERT_EQ(tensor_ty->layout(), DATALAYOUT(kNCHW));
 }
 
 }  // namespace lite

paddle/fluid/lite/kernels/cuda/io_copy_compute.cc

@@ -50,7 +50,7 @@ class IoCopyHostToCudaCompute
           param.x->target() == TARGET(kX86));
     LOG(INFO) << "copy size " << param.x->data_size();
     auto* data = param.y->mutable_data<int8_t>(TARGET(kCUDA));
-    CopyFromHostSync(data, param.x->data<int8_t>(), param.x->data_size());
+    CopyFromHostSync(data, param.x->raw_data(), param.x->data_size());
   }
 
   std::unique_ptr<type_infer_handler_t> GetTypeInferHandler() override {
@@ -63,8 +63,9 @@ class IoCopyHostToCudaCompute
 
       auto out_place = type->place();
       out_place.target = TARGET(kCUDA);
-      auto* out_type = LookupType(type->id(), type->IsUnsupported(),
-                                  type->IsUnsupported(), out_place);
+      auto* out_type =
+          Type::Get(type->id(), out_place.target, out_place.precision,
+                    out_place.layout, out_place.device);
       return out_type;
     };
     return res;
@@ -98,17 +99,13 @@ class IoCopyCudaToHostCompute
 REGISTER_LITE_KERNEL(io_copy, kCUDA, kAny, kAny,
                      paddle::lite::kernels::cuda::IoCopyHostToCudaCompute,
                      host_to_device)
-    .BindInput("Input", {paddle::lite::Type::Get<paddle::lite::TensorAnyTy>(
-                            TARGET(kHost))})
-    .BindOutput("Out", {paddle::lite::Type::Get<paddle::lite::TensorAnyTy>(
-                           TARGET(kCUDA))})
+    .BindInput("Input", {LiteType::GetTensorTy(TARGET(kHost))})
+    .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kCUDA))})
     .Finalize();
 
 REGISTER_LITE_KERNEL(io_copy, kCUDA, kAny, kAny,
                      paddle::lite::kernels::cuda::IoCopyCudaToHostCompute,
                      device_to_host)
-    .BindInput("Input", {paddle::lite::Type::Get<paddle::lite::TensorAnyTy>(
-                            TARGET(kCUDA))})
-    .BindOutput("Out", {paddle::lite::Type::Get<paddle::lite::TensorAnyTy>(
-                           TARGET(kHost))})
+    .BindInput("Input", {LiteType::GetTensorTy(TARGET(kCUDA))})
+    .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kHost))})
     .Finalize();

paddle/fluid/lite/kernels/cuda/mul_compute.cc

@@ -25,10 +25,7 @@ namespace cuda {}  // namespace cuda
 
 REGISTER_LITE_KERNEL(mul, kCUDA, kFloat, kNCHW,
                      paddle::lite::kernels::cuda::MulCompute, def)
-    .BindInput("X", {paddle::lite::Type::Get<paddle::lite::TensorFp32NCHWTy>(
-                        TARGET(kCUDA))})
-    .BindInput("Y", {paddle::lite::Type::Get<paddle::lite::TensorFp32NCHWTy>(
-                        TARGET(kCUDA))})
-    .BindOutput("Out", {paddle::lite::Type::Get<paddle::lite::TensorFp32NCHWTy>(
-                           TARGET(kCUDA))})
+    .BindInput("X", {LiteType::GetTensorTy(TARGET(kCUDA))})
+    .BindInput("Y", {LiteType::GetTensorTy(TARGET(kCUDA))})
+    .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kCUDA))})
     .Finalize();

paddle/fluid/lite/kernels/cuda/mul_compute.h

@@ -36,7 +36,7 @@ class MulCompute : public KernelLite<TARGET(kCUDA), PRECISION(kFloat)> {
 
   void Run() override {
     CHECK(context_) << "running context should be set first";
-    auto& context = context_->AsCudaContext();
+    auto& context = context_->As<CUDAContext>();
     CHECK(context.blas_fp32) << "blas should init first";
     /*
     auto& blas = *context.blas_fp32;

paddle/fluid/lite/kernels/host/fc_compute.cc

@@ -53,13 +53,8 @@ void FcCompute::Run() {
 
 REGISTER_LITE_KERNEL(fc, kHost, kFloat, kNCHW,
                      paddle::lite::kernels::host::FcCompute, def)
-    .BindInput("Input",
-               {paddle::lite::Type::Get<paddle::lite::TensorFp32NCHWTy>(
-                   TARGET(kHost))})
-    .BindInput("Bias", {paddle::lite::Type::Get<paddle::lite::TensorFp32NCHWTy>(
-                           TARGET(kHost))})
-    .BindInput("W", {paddle::lite::Type::Get<paddle::lite::TensorFp32NCHWTy>(
-                        TARGET(kHost))})
-    .BindOutput("Out", {paddle::lite::Type::Get<paddle::lite::TensorFp32NCHWTy>(
-                           TARGET(kHost))})
+    .BindInput("Input", {LiteType::GetTensorTy(TARGET(kHost))})
+    .BindInput("Bias", {LiteType::GetTensorTy(TARGET(kHost))})
+    .BindInput("W", {LiteType::GetTensorTy(TARGET(kHost))})
+    .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kHost))})
     .Finalize();

paddle/fluid/lite/kernels/host/feed_compute.cc

@@ -43,8 +43,6 @@ class FeedCompute
 
 REGISTER_LITE_KERNEL(feed, kHost, kAny, kAny,
                      paddle::lite::kernels::host::FeedCompute, def)
-    .BindInput("X", {paddle::lite::Type::Get<paddle::lite::TensorAnyTy>(
-                        TARGET(kHost))})
-    .BindOutput("Out", {paddle::lite::Type::Get<paddle::lite::TensorAnyTy>(
-                           TARGET(kHost))})
+    .BindInput("X", {LiteType::GetTensorTy(TARGET(kHost))})
+    .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kHost))})
     .Finalize();

paddle/fluid/lite/kernels/host/fetch_compute.cc

@@ -44,8 +44,8 @@ class FetchCompute
 
 REGISTER_LITE_KERNEL(fetch, kHost, kAny, kAny,
                      paddle::lite::kernels::host::FetchCompute, def)
-    .BindInput("X", {paddle::lite::Type::Get<paddle::lite::TensorAnyTy>(
-                        TARGET(kHost))})
-    .BindOutput("Out", {paddle::lite::Type::Get<paddle::lite::TensorListAnyTy>(
-                           TARGET(kHost))})
+    .BindInput("X", {LiteType::GetTensorTy(TARGET(kHost), PRECISION(kAny),
+                                           DATALAYOUT(kAny), -1)})
+    .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kHost), PRECISION(kAny),
+                                              DATALAYOUT(kAny), -1)})
     .Finalize();

paddle/fluid/lite/kernels/host/mul_compute.cc

@@ -74,10 +74,7 @@ class MulCompute : public KernelLite<TARGET(kHost), PRECISION(kFloat)> {
 
 REGISTER_LITE_KERNEL(mul, kHost, kFloat, kNCHW,
                      paddle::lite::kernels::host::MulCompute, def)
-    .BindInput("X", {paddle::lite::Type::Get<paddle::lite::TensorFp32NCHWTy>(
-                        TARGET(kHost))})
-    .BindInput("Y", {paddle::lite::Type::Get<paddle::lite::TensorFp32NCHWTy>(
-                        TARGET(kHost))})
-    .BindOutput("Out", {paddle::lite::Type::Get<paddle::lite::TensorFp32NCHWTy>(
-                           TARGET(kHost))})
+    .BindInput("X", {LiteType::GetTensorTy(TARGET(kHost))})
+    .BindInput("Y", {LiteType::GetTensorTy(TARGET(kHost))})
+    .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kHost))})
     .Finalize();

paddle/fluid/lite/kernels/host/scale_compute.cc

@@ -52,8 +52,6 @@ class ScaleCompute : public KernelLite<TARGET(kHost), PRECISION(kFloat)> {
 
 REGISTER_LITE_KERNEL(scale, kHost, kFloat, kNCHW,
                      paddle::lite::kernels::host::ScaleCompute, def)
-    .BindInput("X", {paddle::lite::Type::Get<paddle::lite::TensorFp32NCHWTy>(
-                        TARGET(kHost))})
-    .BindOutput("Out", {paddle::lite::Type::Get<paddle::lite::TensorFp32NCHWTy>(
-                           TARGET(kHost))})
+    .BindInput("X", {LiteType::GetTensorTy(TARGET(kHost))})
+    .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kHost))})
     .Finalize();

paddle/fluid/lite/model_parser/CMakeLists.txt

@@ -3,7 +3,7 @@ lite_cc_test(test_model_parser_lite SRCS model_parser_test.cc DEPS model_parser_
 if(LITE_WITH_LIGHT_WEIGHT_FRAMEWORK)
     cc_library(compatible_pb_lite SRCS compatible_pb.cc DEPS op_desc_lite var_desc_lite)
 else()
-    cc_library(compatible_pb_lite SRCS compatible_pb.cc DEPS framework_proto proto_desc)
+    cc_library(compatible_pb_lite SRCS compatible_pb.cc DEPS framework_proto_lite proto_desc)
 endif(LITE_WITH_LIGHT_WEIGHT_FRAMEWORK)
 
 set(model_parser_deps variable_lite scope_lite ${tensor_lite} scope_lite

paddle/fluid/lite/model_parser/pb/CMakeLists.txt

-cc_library(var_desc_lite SRCS var_desc.cc DEPS framework_proto)
-cc_library(op_desc_lite SRCS op_desc.cc DEPS framework_proto)
+cc_library(var_desc_lite SRCS var_desc.cc DEPS framework_proto_lite)
+cc_library(op_desc_lite SRCS op_desc.cc DEPS framework_proto_lite)

paddle/fluid/lite/utils/cp_logging.cc

+// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
 #include "paddle/fluid/lite/utils/cp_logging.h"
 
 namespace paddle {

paddle/fluid/lite/utils/cp_logging.h

+// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
 #ifdef LITE_WITH_LIGHT_WEIGHT_FRAMEWORK
 #include "paddle/fluid/lite/utils/logging.h"
 #else  // LITE_WITH_LIGHT_WEIGHT_FRAMEWORK

paddle/fluid/lite/utils/logging.h

@@ -22,6 +22,8 @@
 #include <iostream>
 #include <sstream>
 
+#ifdef LITE_WITH_LIGHT_WEIGHT_FRAMEWORK
+
 // LOG()
 #define LOG(status) LOG_##status.stream()
 #define LOG_ERROR LOG_INFO
@@ -86,3 +88,5 @@ class LogMessageFatal : public LogMessage {
 
 }  // namespace lite
 }  // namespace paddle
+
+#endif  // LITE_WITH_LIGHT_FRAMEWORK

paddle/fluid/lite/utils/macros.h

@@ -22,10 +22,13 @@
 
 #define LITE_UNIMPLEMENTED CHECK(false) << "Not Implemented";
 
+/*
 #ifndef LIKELY
 #define LIKELY(x) __builtin_expect(!!(x), 1)
 #endif
+
 #ifndef UNLIKELY
 //#define UNLIKELY(x) __built_expect(!!(x), 0)
 #define UNLIKELY(x) (x)
 #endif
+ */