enable optimized model persist

paddle/fluid/lite/api/CMakeLists.txt

@@ -1,7 +1,7 @@
 if(LITE_WITH_CUDA)
-    cc_library(cxx_api_lite_cuda SRCS cxx_api.cc DEPS scope_lite host_kernels ops_lite optimizer_lite target_wrapper_host target_wrapper_cuda kernels_cuda)
+    cc_library(cxx_api_lite_cuda SRCS cxx_api.cc DEPS scope_lite host_kernels ops_lite optimizer_lite target_wrapper_host target_wrapper_cuda kernels_cuda optimizer_lite)
     nv_test(test_cxx_api_lite_cuda SRCS cxx_api_test.cc DEPS cxx_api_lite_cuda model_parser_lite)
 else()
-    cc_library(cxx_api_lite SRCS cxx_api.cc DEPS scope_lite op_executor_lite host_kernels ops_lite optimizer_lite target_wrapper_host )
+    cc_library(cxx_api_lite SRCS cxx_api.cc DEPS scope_lite op_executor_lite host_kernels ops_lite optimizer_lite target_wrapper_host)
     cc_test(test_cxx_api_lite SRCS cxx_api_test.cc DEPS cxx_api_lite model_parser_lite target_wrapper_host host_kernels)
 endif()

paddle/fluid/lite/api/cxx_api.cc

@@ -13,7 +13,15 @@
 // limitations under the License.
 
 #include "paddle/fluid/lite/api/cxx_api.h"
+#include "paddle/fluid/platform/port.h"
 
 namespace paddle {
-namespace lite {}  // namespace lite
+namespace lite {
+
+void Predictor::SaveModel(const std::string &dir) {
+  MkDirRecursively(dir.c_str());
+  program_->PersistModel(dir, program_desc_);
+}
+
+}  // namespace lite
 }  // namespace paddle

paddle/fluid/lite/api/cxx_api.h

@@ -31,19 +31,19 @@ class Predictor {
 
   void Build(const std::string& model_path, const Place& prefer_place,
              const std::vector<Place>& valid_places) {
-    framework::proto::ProgramDesc prog;
-    LoadModel(model_path, scope_.get(), &prog);
+    LoadModel(model_path, scope_.get(), &program_desc_);
 
-    Program program(prog, scope_, valid_places);
+    Program program(program_desc_, scope_, valid_places);
 
-    Optimizer optimizer;
-    optimizer.KernelPickPreferPlace(prefer_place);
+    optimizer_.KernelPickPreferPlace(prefer_place);
     core::KernelPickFactor factor;
     factor.ConsiderTarget();
-    optimizer.Run(std::move(program), valid_places, factor);
-    program_ = optimizer.GenRuntimeProgram();
+    optimizer_.Run(std::move(program), valid_places, factor);
+    program_ = optimizer_.GenRuntimeProgram();
   }
 
+  void SaveModel(const std::string& dir);
+
   // Get offset-th col of feed.
   Tensor* GetInput(size_t offset) {
     auto* _feed_list = program_->exec_scope()->FindVar("feed");
@@ -65,7 +65,13 @@ class Predictor {
 
   void Run() { program_->Run(); }
 
+  const framework::proto::ProgramDesc& program_desc() const {
+    return program_desc_;
+  }
+
  private:
+  Optimizer optimizer_;
+  framework::proto::ProgramDesc program_desc_;
   std::shared_ptr<Scope> scope_;
   std::unique_ptr<RuntimeProgram> program_;
 };

paddle/fluid/lite/api/cxx_api_test.cc

@@ -36,7 +36,7 @@ TEST(CXXApi, test) {
   });
 #endif
 
-  predictor.Build("/home/chunwei/project2/models/model2",
+  predictor.Build("/home/chunwei/project/models/model2",
                   Place{TARGET(kCUDA), PRECISION(kFloat)}, valid_places);
 
   auto* input_tensor = predictor.GetInput(0);
@@ -59,6 +59,15 @@ TEST(CXXApi, test) {
   LOG(INFO) << "out " << *out;
 }
 
+TEST(CXXApi, save_model) {
+  lite::Predictor predictor;
+  std::vector<Place> valid_places({Place{TARGET(kHost), PRECISION(kFloat)}});
+  predictor.Build("/home/chunwei/project/models/model2",
+                  Place{TARGET(kCUDA), PRECISION(kFloat)}, valid_places);
+
+  predictor.SaveModel("./optimized_model");
+}
+
 }  // namespace lite
 }  // namespace paddle
 

paddle/fluid/lite/core/CMakeLists.txt

@@ -12,13 +12,13 @@ cc_library(op_executor_lite SRCS op_executor.cc DEPS scope_lite tensor_lite op_l
 cc_library(kernel_executor_lite SRCS kernel_executor.cc DEPS mir_ssa_graph kernel_lite)
 cc_library(types_lite SRCS types.cc)
 cc_library(type_system SRCS type_system.cc DEPS tensor_lite)
-cc_library(optimizer_lite SRCS optimizer.cc DEPS mir_pass_manager)
 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
   )
 cc_library(program_lite SRCS program.cc DEPS op_lite kernel_lite)
+cc_library(optimizer_lite SRCS optimizer.cc DEPS mir_pass_manager model_parser_lite program_lite)
 
 cc_test(test_scope_lite SRCS scope_test.cc DEPS scope_lite)
 cc_test(test_kernel_lite SRCS kernel_test.cc DEPS target_wrapper_x86)

paddle/fluid/lite/core/kernel.h

@@ -96,6 +96,14 @@ class KernelBase {
   // Generate the key of the parameter type.
   std::string GenParamTypeKey() const;
 
+  std::string SerializeKernelType() const {
+    std::stringstream ss;
+    ss << op_type() << "/";
+    ss << alias_ << "/";
+    ss << place();
+    return ss.str();
+  }
+
   virtual ~KernelBase() = default;
   void Torch() {}
 

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

@@ -22,7 +22,7 @@ namespace mir {
 
 void GenerateProgramPass::Apply(std::unique_ptr<mir::SSAGraph>& graph) {
   LOG(INFO) << "final program \n" << Visualize(graph.get());
-  for (auto& item : graph->InstructTopologicalOrder()) {
+  for (auto& item : graph->StmtTopologicalOrder()) {
     if (item->IsStmt()) {
       auto& stmt = item->AsStmt();
       LOG(INFO) << stmt;

paddle/fluid/lite/core/mir/generate_program_pass.h

@@ -31,6 +31,7 @@ class GenerateProgramPass : public ProgramPass {
   void Apply(std::unique_ptr<mir::SSAGraph>& graph) override;
 
   std::unique_ptr<RuntimeProgram> GenProgram() {
+    LOG(INFO) << "insts.size " << insts_.size();
     std::unique_ptr<RuntimeProgram> program(
         new RuntimeProgram(std::move(insts_)));
     return program;

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

@@ -71,7 +71,7 @@ void SSAGraph::SortHelper(
   ret->push_back(node);
 }
 
-std::vector<mir::Node *> SSAGraph::InstructTopologicalOrder() {
+std::vector<mir::Node *> SSAGraph::StmtTopologicalOrder() {
   CheckBidirectionalConnection();
 
   std::stack<mir::Node *> stack;

paddle/fluid/lite/core/mir/ssa_graph.h

@@ -39,7 +39,7 @@ class SSAGraph : GraphBase {
 
   mir::Node *Argument(const std::string &name);
 
-  std::vector<mir::Node *> InstructTopologicalOrder();
+  std::vector<mir::Node *> StmtTopologicalOrder();
 
   // The inputs of the graph.
   std::vector<mir::Node *> inputs();

paddle/fluid/lite/core/mir/variable_place_inference_pass.h

@@ -58,7 +58,7 @@ class VariablePlaceInferencePass : public DebugPass {
 
   void InferenceArgumentPlace(SSAGraph* graph) {
     VLOG(3) << "param-type-registry:\n" << ParamTypeRegistry::Global();
-    for (auto& x : graph->InstructTopologicalOrder()) {
+    for (auto& x : graph->StmtTopologicalOrder()) {
       auto& inst = x->AsStmt();
       // The IoCopyOp is a tool operator, it won't support the type inference.
       if (inst.op_type == "io_copy") continue;

paddle/fluid/lite/core/optimizer.cc

@@ -13,8 +13,11 @@
 // limitations under the License.
 
 #include "paddle/fluid/lite/core/optimizer.h"
+#include <fstream>
 #include "paddle/fluid/lite/core/mir/static_kernel_pick_pass.h"
 #include "paddle/fluid/lite/core/mir/type_target_transform_pass.h"
+#include "paddle/fluid/lite/model_parser/model_parser.h"
+#include "paddle/fluid/lite/utils/all.h"
 
 namespace paddle {
 namespace lite {

paddle/fluid/lite/core/optimizer.h

@@ -22,6 +22,7 @@
 #include "paddle/fluid/lite/core/mir/type_target_transform_pass.h"
 #include "paddle/fluid/lite/core/program.h"
 #include "paddle/fluid/lite/core/types.h"
+#include "paddle/fluid/lite/model_parser/model_parser.h"
 
 namespace paddle {
 namespace lite {
@@ -35,6 +36,7 @@ class Optimizer {
   void Run(Program&& program, const std::vector<Place>& valid_places,
            core::KernelPickFactor kernel_pick_factor,
            const std::vector<std::string>& passes = {}) {
+    program_ = &program;
     valid_places_ = valid_places;
     CHECK(!valid_places.empty()) << "At least one valid_place should be set";
     CHECK(!graph_) << "duplicate optimize found";
@@ -100,6 +102,11 @@ class Optimizer {
     return *graph_;
   }
 
+  mir::SSAGraph* mutable_ssa_graph() {
+    CHECK(graph_);
+    return graph_.get();
+  }
+
  protected:
   void SpecifyKernelPickTactic(core::KernelPickFactor factor);
 
@@ -117,6 +124,7 @@ class Optimizer {
   std::unique_ptr<mir::SSAGraph> graph_;
   std::vector<Place> valid_places_;
   lite::Scope* exec_scope_{};
+  Program* program_{};
 };
 
 }  // namespace lite

paddle/fluid/lite/core/optimizer_test.cc

@@ -28,15 +28,10 @@ TEST(Optimizer, test) {
   auto program = ProgramFaker();
   std::vector<Place> places({Place{TARGET(kHost), PRECISION(kFloat)}});
 
-  auto* pick_pass =
-      mir::PassManager::Global().LookUp<mir::StaticKernelPickPass>(
-          "static_kernel_pick_pass");
-  ASSERT_TRUE(pick_pass != nullptr);
-  pick_pass->mutable_kernel_pick_factors()
-      ->ConsiderTarget()
-      .ConsiderPrecision();
+  core::KernelPickFactor factor;
+  factor.ConsiderTarget();
 
-  optimizer.Run(std::move(program), places);
+  optimizer.Run(std::move(program), places, factor);
   auto runtime_program = optimizer.GenRuntimeProgram();
   LOG(INFO) << "num statements " << runtime_program->num_instructions();
 }
@@ -45,4 +40,4 @@ TEST(Optimizer, test) {
 }  // namespace paddle
 
 USE_LITE_OP(fc);
-USE_LITE_KERNEL(fc, kHost, kFloat, def);
+USE_LITE_KERNEL(fc, kHost, kFloat, kNCHW, def);

paddle/fluid/lite/core/program.cc

@@ -13,3 +13,59 @@
 // limitations under the License.
 
 #include "paddle/fluid/lite/core/program.h"
+#include "paddle/fluid/lite/core/optimizer.h"
+
+namespace paddle {
+namespace lite {
+
+void RuntimeProgram::PersistModel(const std::string &path,
+                                  const framework::proto::ProgramDesc &desc) {
+  // Persist model.
+  const std::string model_path = path + "/__model__";
+  std::ofstream model_ostream(model_path, std::ios_base::binary);
+  CHECK(model_ostream.is_open());
+  const std::string pb_str = SerializeModelTopology(desc);
+  model_ostream.write(pb_str.c_str(), pb_str.size());
+
+  // Persist params.
+  const std::string params_path = path + "/params";
+  CHECK(!IsFileExists(params_path)) << "file " << params_path
+                                    << " exists, can't overwrite";
+  std::ofstream params_ostream(params_path, std::ios_base::binary);
+  CHECK(params_ostream.is_open());
+  framework::proto::ProgramDesc latest_program;
+  latest_program.ParseFromString(pb_str);
+  SerializeParams(params_ostream, latest_program);
+}
+
+std::string RuntimeProgram::SerializeModelTopology(
+    const framework::proto::ProgramDesc &desc) {
+  const std::string kKernelTypeAttr = "__@kernel_type_attr@__";
+  auto program_dummy = desc;
+  program_dummy.mutable_blocks(0)->clear_ops();
+  for (auto &node : instructions_) {
+    auto desc_dummy = node.op()->op_info()->desc();
+    OpDesc desc(desc_dummy);
+    desc.SetAttr(kKernelTypeAttr, node.kernel()->SerializeKernelType());
+    // append new opdesc
+    *program_dummy.mutable_blocks(0)->add_ops() = *desc.Proto();
+  }
+  return program_dummy.SerializeAsString();
+}
+
+void RuntimeProgram::SerializeParams(
+    std::ostream &os, const framework::proto::ProgramDesc &desc) {
+  std::vector<std::string> ws;
+  for (auto &item : desc.blocks(0).vars()) {
+    if (item.name() == "feed" || item.name() == "fetch") continue;
+    if (item.persistable()) {
+      ws.push_back(item.name());
+    }
+  }
+
+  CHECK(exec_scope_);
+  SerializeTensors(os, *exec_scope_, ws);
+}
+
+}  // namespace lite
+}  // namespace paddle

paddle/fluid/lite/core/program.h

@@ -19,6 +19,7 @@
 #include "paddle/fluid/framework/program_desc.h"
 #include "paddle/fluid/lite/core/kernel.h"
 #include "paddle/fluid/lite/core/kernel.h"
+#include "paddle/fluid/lite/core/mir/node.h"
 #include "paddle/fluid/lite/core/op_lite.h"
 #include "paddle/fluid/lite/core/op_registry.h"
 
@@ -115,6 +116,9 @@ struct Instruction {
     return os;
   }
 
+  const OpLite* op() const { return op_.get(); }
+  const KernelBase* kernel() const { return kernel_.get(); }
+
  private:
   std::shared_ptr<OpLite> op_;
   std::unique_ptr<KernelBase> kernel_;
@@ -128,8 +132,8 @@ class RuntimeProgram {
  public:
   explicit RuntimeProgram(std::vector<Instruction>&& insts)
       : instructions_(std::move(insts)) {
-    if (insts.empty()) {
-      LOG(ERROR) << "no instructions";
+    if (instructions_.empty()) {
+      LOG(FATAL) << "no instructions";
     }
   }
 
@@ -140,11 +144,20 @@ class RuntimeProgram {
     }
   }
 
+  // Serialize the graph and save to the disk.
+  void PersistModel(const std::string& path,
+                    const framework::proto::ProgramDesc& desc);
+
   void set_exec_scope(lite::Scope* x) { exec_scope_ = x; }
   lite::Scope* exec_scope() { return exec_scope_; }
 
   size_t num_instructions() const { return instructions_.size(); }
 
+ protected:
+  std::string SerializeModelTopology(const framework::proto::ProgramDesc& desc);
+  void SerializeParams(std::ostream& os,
+                       const framework::proto::ProgramDesc& desc);
+
  private:
   RuntimeProgram(const RuntimeProgram&) = delete;
   std::vector<Instruction> instructions_;

paddle/fluid/lite/core/program_fake_utils.h

@@ -32,21 +32,19 @@ Program FakeProgram() {
     auto b1v = program.scope->Var(b1)->GetMutable<Tensor>();
     auto out1v = program.scope->Var(out1)->GetMutable<Tensor>();
 
-    framework::OpDesc desc;
+    lite::OpDesc desc;
     desc.SetInput("Input", {x});
     desc.SetInput("W", {w1});
     desc.SetInput("Bias", {b1});
     desc.SetOutput("Out", {out1});
     desc.SetType("fc");
-    desc.SetAttr("in_num_col_dims", 1);
-    desc.Flush();
+    desc.SetAttr<int>("in_num_col_dims", 1);
 
     // add to input
     program.tmp_vars.push_back(w1);
     program.tmp_vars.push_back(b1);
 
     auto fc_op = LiteOpRegistry::Global().Create("fc");
-    fc_op->PickKernel({Place{TARGET(kHost), PRECISION(kFloat)}});
     fc_op->Attach(desc, program.scope.get());
     program.ops.emplace_back(std::move(fc_op));
 

paddle/fluid/lite/core/target_wrapper.h

@@ -164,6 +164,8 @@ class TargetWrapper {
 };
 
 // This interface should be specified by each kind of target.
+using TargetWrapperHost = TargetWrapper<TARGET(kHost)>;
+using TargetWrapperX86 = TargetWrapperHost;
 template <>
 class TargetWrapper<TARGET(kHost)> {
  public:
@@ -196,6 +198,8 @@ class TargetWrapper<TARGET(kHost)> {
 };
 
 #ifdef LITE_WITH_CUDA
+using TargetWrapperCuda =
+    TargetWrapper<TARGET(kCUDA), cudaStream_t, cudaEvent_t>;
 // This interface should be specified by each kind of target.
 template <>
 class TargetWrapper<TARGET(kCUDA), cudaStream_t, cudaEvent_t> {

paddle/fluid/lite/core/tensor.h

@@ -58,7 +58,7 @@ class Tensor {
 
   const DDim& dims() const { return dims_; }
 
-  const LoD& lod() { return lod_; }
+  const LoD& lod() const { return lod_; }
   LoD* mutable_lod() { return &lod_; }
 
   template <typename T>

paddle/fluid/lite/model_parser/CMakeLists.txt

@@ -1,4 +1,3 @@
-cc_library(model_parser_lite SRCS model_parser.cc DEPS variable_lite scope_lite tensor_lite scope_lite)
 cc_library(runtime_lite SRCS runtime.cc)
 cc_test(test_model_parser_lite SRCS model_parser_test.cc DEPS model_parser_lite)
 if(LITE_WITH_LIGHT_WEIGHT_FRAMEWORK)
@@ -7,5 +6,8 @@ else()
     cc_library(compatible_pb_lite SRCS compatible_pb.cc DEPS framework_proto)
 endif(LITE_WITH_LIGHT_WEIGHT_FRAMEWORK)
 
+cc_library(model_parser_lite SRCS model_parser.cc DEPS variable_lite scope_lite tensor_lite scope_lite
+compatible_pb_lite)
+
 
 add_subdirectory(pb)

paddle/fluid/lite/model_parser/model_parser.cc

@@ -37,6 +37,7 @@ int SizeOfType(framework::proto::VarType::Type type) {
     default:
       LOG(FATAL) << "unknown data type";
   }
+  return -1;
 }
 
 void TensorFromStream(std::istream &is, lite::Tensor *tensor) {
@@ -162,5 +163,73 @@ void LoadModel(const std::string &model_dir, Scope *scope,
   }
 }
 
+void TensorToStream(std::ostream &os, const lite::Tensor &tensor) {
+  {  // the 1st field, uint32_t version
+    constexpr uint32_t version = 0;
+    os.write(reinterpret_cast<const char *>(&version), sizeof(version));
+  }
+
+  {
+    int size = tensor.lod().size();
+    // the 2st field, LoD information
+    // uint64_t lod_level
+    // uint64_t lod_level_1 size in byte.
+    // int*     lod_level_1 data
+    // ...
+    os.write(reinterpret_cast<const char *>(&size), sizeof(size));
+
+    for (auto &each : tensor.lod()) {
+      size = each.size() * sizeof(each.front());
+      os.write(reinterpret_cast<const char *>(&size), sizeof(size));
+      os.write(reinterpret_cast<const char *>(each.data()),
+               static_cast<std::streamsize>(size));
+    }
+  }
+
+  {  // the 2nd field, tensor description
+    // int32_t  size
+    // void*    protobuf message
+    framework::proto::VarType::TensorDesc desc;
+    desc.set_data_type(framework::proto::VarType_Type_LOD_TENSOR);
+    auto dims = tensor.dims();
+    auto *pb_dims = desc.mutable_dims();
+    pb_dims->Resize(static_cast<int>(dims.size()), 0);
+    std::copy(dims.begin(), dims.end(), pb_dims->begin());
+    int32_t size = desc.ByteSize();
+    os.write(reinterpret_cast<const char *>(&size), sizeof(size));
+    auto out = desc.SerializeAsString();
+    os.write(out.data(), size);
+  }
+  {  // the 3rd field, tensor data
+    uint64_t size = tensor.memory_size();
+    CHECK_LT(size, std::numeric_limits<std::streamsize>::max())
+        << "Index overflow when writing tensor";
+
+#ifdef LITE_WITH_CUDA
+    if (tensor.target() == TARGET(kCUDA)) {
+      std::unique_ptr<char> tmp_buffer(new char[size]);
+      TargetWrapperCuda::MemcpySync(tmp_buffer.get(), tensor.data<char>(),
+                                    tensor.memory_size(), IoDirection::DtoH);
+      os.write(static_cast<const char *>(tmp_buffer.get()),
+               static_cast<std::streamsize>(size));
+    } else
+#endif  // LITE_WITH_CUDA
+    {
+      os.write(static_cast<const char *>(tensor.data<void>()),
+               static_cast<std::streamsize>(size));
+    }
+  }
+}
+
+void SerializeTensors(std::ostream &os, const lite::Scope &scope,
+                      const std::vector<std::string> &vars) {
+  // Store all the persistable vars.
+  for (const auto &_var : vars) {
+    auto *var = scope.FindVar(_var);
+    const auto &tensor = var->Get<lite::Tensor>();
+    TensorToStream(os, tensor);
+  }
+}
+
 }  // namespace lite
 }  // namespace paddle

paddle/fluid/lite/model_parser/model_parser.h

@@ -40,5 +40,12 @@ void LoadParam(const std::string& path, Variable* out);
 void LoadModel(const std::string& model_dir, Scope* scope,
                framework::proto::ProgramDesc* prog);
 
+// Serialize tensors to ostream.
+void SerializeTensors(std::ostream& os, const lite::Scope& scope,
+                      const std::vector<std::string>& vars);
+
+// LoDTensor to ostream
+void TensorToStream(std::ostream& os, const lite::Tensor& tensor);
+
 }  // namespace lite
 }  // namespace paddle

paddle/fluid/lite/model_parser/pb/op_desc.cc

@@ -13,3 +13,31 @@
 // limitations under the License.
 
 #include "paddle/fluid/lite/model_parser/pb/op_desc.h"
+
+namespace paddle {
+namespace lite {
+namespace pb {
+
+template <>
+void OpDesc::SetAttr<std::string>(const std::string &name,
+                                  const std::string &v) {
+  auto &xs = *desc_.mutable_attrs();
+  auto it = std::find_if(
+      xs.begin(), xs.end(),
+      [&](const framework::proto::OpDesc_Attr &x) { return x.name() == name; });
+  if (it == xs.end()) {
+    auto *attr = xs.Add();
+    attr->set_name(name);
+    it = std::find_if(xs.begin(), xs.end(),
+                      [&](const framework::proto::OpDesc_Attr &x) {
+                        return x.name() == name;
+                      });
+  }
+
+  it->set_type(framework::proto::STRING);
+  it->set_s(v.c_str());
+}
+
+}  // namespace pb
+}  // namespace lite
+}  // namespace paddle

paddle/fluid/lite/model_parser/pb/op_desc.h

@@ -120,28 +120,24 @@ class OpDesc {
     if (it == xs.end()) {
       auto *attr = xs.Add();
       attr->set_name(name);
-      it = std::find(xs.begin(), xs.end(), name);
+      it = std::find_if(xs.begin(), xs.end(),
+                        [&](const framework::proto::OpDesc_Attr &x) {
+                          return x.name() == name;
+                        });
     }
 
-    switch (typeid(T).hash_code()) {
-      case typeid(int).hash_code():
-        it->set_type(framework::proto::INT);
-        it->set_i(v);
-        break;
-      case typeid(float).hash_code():
-        it->set_type(framework::proto::FLOAT);
-        it->set_f(v);
-        break;
-      case typeid(std::string).hash_code():
-        it->set_type(framework::proto::STRING);
-        it->set_s(v.c_str());
-        break;
-      case typeid(std::string).hash_code():
-        it->set_type(framework::proto::BOOLEAN);
-        it->set_b(v);
-        break;
-      default:
-        LOG(FATAL) << "unsupport attr type";
+    size_t hash = typeid(T).hash_code();
+    if (hash == typeid(int).hash_code()) {
+      it->set_type(framework::proto::INT);
+      it->set_i(v);
+    } else if (hash == typeid(float).hash_code()) {
+      it->set_type(framework::proto::FLOAT);
+      it->set_f(v);
+    } else if (hash == typeid(bool).hash_code()) {
+      it->set_type(framework::proto::BOOLEAN);
+      it->set_b(v);
+    } else {
+      LOG(FATAL) << "unsupport attr type";
     }
   }
 
@@ -229,6 +225,10 @@ class OpDesc {
   framework::proto::OpDesc desc_;
 };
 
+template <>
+void OpDesc::SetAttr<std::string>(const std::string &name,
+                                  const std::string &v);
+
 }  // namespace pb
 }  // namespace lite
 }  // namespace paddle

paddle/fluid/lite/utils/all.h

@@ -17,5 +17,6 @@
 #include "paddle/fluid/lite/utils/check.h"
 #include "paddle/fluid/lite/utils/factory.h"
 #include "paddle/fluid/lite/utils/hash.h"
+#include "paddle/fluid/lite/utils/io.h"
 #include "paddle/fluid/lite/utils/macros.h"
 #include "paddle/fluid/lite/utils/varient.h"