!13552 uniform interface, remove c API

From: @yangjie159
Reviewed-by: @wangchengyuan,@hangangqiang
Signed-off-by: @wangchengyuan

mindspore/lite/micro/cmake/file_list.cmake

@@ -19,8 +19,6 @@ set(CODER_GENERATOR_SRC
         ${MICRO_DIR}/coder/generator/generator.cc
         ${MICRO_DIR}/coder/generator/inference/inference_generator.cc
         ${MICRO_DIR}/coder/generator/train/train_generator.cc
-        ${MICRO_DIR}/coder/generator/component/component.cc
-        ${MICRO_DIR}/coder/generator/component/benchmark_component.cc
         ${MICRO_DIR}/coder/generator/component/common_component.cc
         ${MICRO_DIR}/coder/generator/component/weight_component.cc
         ${MICRO_DIR}/coder/generator/component/cmake_component.cc
@@ -33,8 +31,6 @@ set(CODER_GENERATOR_SRC
         ${MICRO_DIR}/coder/generator/component/const_blocks/license.cc
         ${MICRO_DIR}/coder/generator/component/const_blocks/load_input.cc
         ${MICRO_DIR}/coder/generator/component/const_blocks/benchmark.cc
-        ${MICRO_DIR}/coder/generator/component/const_blocks/micro_tensor.cc
-        ${MICRO_DIR}/coder/generator/component/const_blocks/thread_pool.cc
         )
 
 set(MINDSPORE_CORE

mindspore/lite/micro/coder/coder.cc

@@ -27,7 +27,7 @@
 #include "securec/include/securec.h"
 #include "src/common/file_utils.h"
 #include "src/common/utils.h"
-#include "coder/coder_config.h"
+#include "coder/config.h"
 #include "coder/generator/component/component.h"
 
 namespace mindspore::lite::micro {
@@ -40,7 +40,6 @@ class CoderFlags : public virtual FlagParser {
     AddFlag(&CoderFlags::code_module_name_, "moduleName", "Input code module name", "");
     AddFlag(&CoderFlags::target_, "target", "generated code target, x86| ARM32M| ARM32A| ARM64", "x86");
     AddFlag(&CoderFlags::code_mode_, "codeMode", "generated code mode, Inference | Train", "Inference");
-    AddFlag(&CoderFlags::interface_, "interface", "the interface of generated code, CPP | C", "CPP");
     AddFlag(&CoderFlags::support_parallel_, "supportParallel", "whether support parallel launch, true | false", false);
     AddFlag(&CoderFlags::debug_mode_, "debugMode", "dump the tensors data for debugging, true | false", false);
   }
@@ -52,7 +51,6 @@ class CoderFlags : public virtual FlagParser {
   std::string code_module_name_;
   std::string code_path_;
   std::string code_mode_;
-  std::string interface_;
   bool debug_mode_{false};
   std::string target_;
 };
@@ -90,8 +88,6 @@ int Coder::Init(const CoderFlags &flags) const {
   static const std::map<std::string, Target> kTargetMap = {
     {"x86", kX86}, {"ARM32M", kARM32M}, {"ARM32A", kARM32A}, {"ARM64", kARM64}, {"All", kAllTargets}};
   static const std::map<std::string, CodeMode> kCodeModeMap = {{"Inference", Inference}, {"Train", Train}};
-  static const std::map<std::string, Interface> kInterfaceMap = {{"CPP", Interface_CPP}, {"C", Interface_C}};
-
   Configurator *config = Configurator::GetInstance();
 
   std::vector<std::function<bool()>> parsers;
@@ -109,13 +105,6 @@ int Coder::Init(const CoderFlags &flags) const {
     return true;
   });
 
-  parsers.emplace_back([&flags, config]() -> bool {
-    auto item = kInterfaceMap.find(flags.interface_);
-    MS_CHECK_TRUE_RET_BOOL(item != kInterfaceMap.end(), "unsupported interface: " + flags.code_mode_);
-    config->set_interface(item->second);
-    return true;
-  });
-
   parsers.emplace_back([&flags, config]() -> bool {
     if (flags.support_parallel_ && config->target() == kARM32M) {
       MS_LOG(ERROR) << "arm32M cannot support parallel.";

mindspore/lite/micro/coder/config.h

@@ -22,35 +22,6 @@
 namespace mindspore::lite::micro {
 enum Target { kX86 = 0, kARM32M = 1, kARM32A = 2, kARM64 = 3, kAllTargets = 4, kTargetUnknown = 99 };
 enum CodeMode { Inference = 0, Train = 1, Code_Unknown = 99 };
-enum Interface { Interface_CPP = 0, Interface_C = 1, Interface_Unknown = 99 };
-
-inline const char *EnumNameTarget(Target target) {
-  switch (target) {
-    case kX86:
-      return "kX86";
-    case kARM32M:
-      return "kARM32M";
-    case kARM32A:
-      return "kARM32A";
-    case kARM64:
-      return "kARM64";
-    case kAllTargets:
-      return "kAllTargets";
-    default:
-      return "kTargetUnknown";
-  }
-}
-
-inline const char *EnumNameCodeMode(CodeMode codeMode) {
-  switch (codeMode) {
-    case Inference:
-      return "Inference";
-    case Train:
-      return "Train";
-    default:
-      return "Code_Unknown";
-  }
-}
 
 class Configurator {
  public:
@@ -71,9 +42,6 @@ class Configurator {
   void set_code_mode(CodeMode code_mode) { code_mode_ = code_mode; }
   CodeMode code_mode() const { return code_mode_; }
 
-  void set_interface(Interface interface) { interface_ = interface; }
-  Interface interface() const { return interface_; }
-
   void set_debug_mode(bool debug) { debug_mode_ = debug; }
   bool debug_mode() const { return debug_mode_; }
 
@@ -88,7 +56,6 @@ class Configurator {
   std::string code_path_;
   Target target_{kTargetUnknown};
   CodeMode code_mode_{Code_Unknown};
-  Interface interface_{Interface_CPP};
   bool support_parallel_{false};
   bool debug_mode_{false};
 };

mindspore/lite/micro/coder/context.cc

@@ -15,7 +15,7 @@
  */
 
 #include "coder/context.h"
-#include "coder/coder_config.h"
+#include "coder/config.h"
 #include "coder/allocator/allocator.h"
 
 namespace mindspore::lite::micro {

mindspore/lite/micro/coder/generator/component/benchmark_component.cc

@@ -1,177 +0,0 @@
-/**
- * Copyright 2021 Huawei Technologies Co., Ltd
- *
- * 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 "coder/generator/component/benchmark_component.h"
-#include <memory>
-#include "coder/generator/component/const_blocks/license.h"
-#include "coder/log.h"
-#include "include/errorcode.h"
-#include "nnacl/op_base.h"
-
-namespace mindspore::lite::micro {
-constexpr int kWarmUp = 3;
-void CodeBenchmarkHeader(std::ofstream &ofs, const std::string &header) {
-  ofs << g_hwLicense;
-  ofs << "#include <stdio.h>\n"
-         "#include <string.h>\n"
-         "#include <stdlib.h>\n"
-         "#include <stdint.h>\n"
-         "#include \"microtensor.h\"\n"
-         "#include \"load_input.h\"\n"
-         "#include \"debug_utils.h\"\n";
-  ofs << "#include \"" << header << "\"\n";
-}
-
-void CodeBenchmarkUsage(std::ofstream &ofs) {
-  ofs << "void usage() {\n"
-         "  printf(\n"
-         "    \"-- mindspore micro params usage:\\n\"\n"
-         "    \"args[0]: executable file\\n\"\n"
-         "    \"args[1]: inputs binary file\\n\"\n"
-         "    \"args[2]: model weight binary file\\n\"\n"
-         "    \"args[3]: loop count for performance test\\n\"\n"
-         "    \"args[4]: runtime thread num\\n\"\n"
-         "    \"args[5]: runtime thread bind mode\\n\\n\");\n"
-         "}\n\n";
-}
-
-void CodeBenchmarkWarmup(std::ofstream &ofs, const std::string &module_name) {
-  ofs << "// the default number of warm-ups is 3\n"
-      << "void " << module_name << "_WarmUp() {\n"
-      << "  for (int i = 0; i < " << kWarmUp << "; ++i) {\n"
-      << "    " << module_name << "_Inference();\n"
-      << "  }\n"
-      << "}\n";
-}
-
-void CodeBenchmarkSetInputs(std::ofstream &ofs, const std::string &module_name,
-                            const std::unique_ptr<CoderContext> &ctx) {
-  ofs << "int main(int argc, char **argv) {\n"
-         "  if (argc < 2) {\n"
-         "    MICRO_ERROR(\"input command is invalid\\n\");\n"
-         "    usage();\n"
-         "    return RET_ERROR;\n"
-         "  }\n";
-  std::vector<Tensor *> inputs = ctx->graph_inputs();
-  size_t inputs_num = inputs.size();
-  ofs << "  // input shape: ";
-  std::for_each(inputs.begin(), inputs.end(), [&](Tensor *t) {
-    ofs << "[ ";
-    for (int i : t->shape()) {
-      ofs << i << ", ";
-    }
-    ofs << "], ";
-  });
-  ofs << "\n";
-  ofs << "  void *inputs_binbuf[" << inputs_num << "];\n";
-  ofs << "  int inputs_size[" << inputs_num << "] = {";
-  for (size_t i = 0; i < inputs_num; ++i) {
-    Tensor *input = inputs[i];
-    ofs << input->Size() << ", ";
-  }
-  ofs << "};\n";
-  ofs << "  int ret = ReadInputsFile(argv[1], inputs_binbuf, inputs_size, " << inputs_num
-      << ");\n"
-         "  if (ret != RET_OK) {\n"
-         "    MICRO_ERROR(\"read inputs file failed\");\n"
-         "    return RET_ERROR;\n"
-         "  }\n";
-  ofs << "  ret = " << module_name << "_SetInputs((const void **)inputs_binbuf, " << inputs_num
-      << ");\n"
-         "  if (ret != RET_OK) {\n"
-         "    MICRO_ERROR(\"set inputs failed\");\n"
-         "    return RET_ERROR;\n"
-         "  }\n";
-}
-
-void CodeBenchmarkSetBuffer(std::ofstream &ofs, const std::string &module_name) {
-  ofs << "  int total_buffer_size = " << module_name << "_GetBufferSize();\n";
-  ofs << "  void *buffer = malloc(total_buffer_size);\n";
-  ofs << "  if (buffer == NULL ){\n"
-         "     MICRO_ERROR(\"malloc memory buffer failed\");\n"
-         "     return RET_ERROR;\n"
-         "  }\n";
-  ofs << "  ret = " << module_name
-      << "_SetBuffer(buffer);\n"
-         "  if (ret != RET_OK) {\n"
-         "    MICRO_ERROR(\"set inputs failed\");\n"
-         "    return RET_ERROR;\n"
-         "  }\n";
-}
-
-void CodeBenchmarkInitWeight(std::ofstream &ofs, const std::string &module_name) {
-  ofs << "  int weight_size = 0;\n"
-         "  void *weight_buffer = ReadInputData(argv[2], &weight_size); \n"
-         "  if("
-      << module_name
-      << "_Init(weight_buffer, weight_size) != RET_OK) {\n"
-         "    MICRO_ERROR(\"model init failed\");\n"
-         "    "
-      << module_name
-      << "_FreeResource();\n"
-         "    return RET_ERROR;\n"
-         "  }\n"
-         "  free(weight_buffer);\n"
-         "  weight_buffer = NULL;\n";
-}
-
-void CodeBenchmarkInference(std::ofstream &ofs, const std::string &module_name) {
-  ofs << "  if (argc >= 4) {\n"
-      << "    " << module_name << "_WarmUp();\n"
-      << "    uint64_t timeAvg = 0;\n"
-      << "    int loop_count = atoi(argv[3]);\n"
-      << "    printf(\"======Inference Start======\\n\");\n"
-      << "    printf(\"cycles: %d\\n\", loop_count);\n"
-      << "    for (int i = 0; i < loop_count; i++) {\n"
-      << "      uint64_t runBegin = GetTimeUs();\n"
-      << "      " << module_name << "_Inference();\n"
-      << "      uint64_t runEnd = GetTimeUs();\n"
-      << "      uint64_t time = runEnd - runBegin;\n"
-      << "      timeAvg += time;\n"
-      << "    }\n"
-      << "    float cunCost = (float)timeAvg / 1000.0f;\n"
-      << "    printf(\"=======Inference End=======\\n\");\n"
-         "    printf(\"total time:\\t %.5fms, per time: \\t %.5fms\\n\", cunCost, cunCost/loop_count);\n"
-      << "  }\n";
-  ofs << "  " << module_name << "_Inference();\n";
-}
-
-void CodeBenchmarkPrintOutputs(std::ofstream &ofs, const std::string &module_name) {
-  ofs << "  // print model outputs \n";
-  ofs << "  const MicroTensorList *outs = " << module_name << "_GetOutputs();\n";
-  ofs << "  for (int i = 0; i < outs->num; ++i) {\n"
-         "      MicroTensor *tensor = outs->tensor + i;\n"
-         "      PrintTensorData(tensor);\n"
-         "  }\n";
-  ofs << "  printf(\"" << module_name << " inference success.\\n\");\n";
-}
-
-/**
- * 1. free malloc memory buffer
- * 2. set input and buffer to NULL, and free packed weight memory
- * 3. free input binary memory
- */
-void CodeBenchmarkFreeResourse(std::ofstream &ofs, const std::string &module_name, size_t inputs_num) {
-  ofs << "  free(buffer);\n";
-  ofs << "  " << module_name << "_FreeResource();\n";
-  ofs << "  for (int i = 0; i < " << inputs_num << "; ++i) {\n";
-  ofs << "    free(inputs_binbuf[i]);\n"
-         "  }\n"
-         "  return RET_OK;\n"
-         "}\n\n";
-}
-
-}  // namespace mindspore::lite::micro

mindspore/lite/micro/coder/generator/component/benchmark_component.h

@@ -1,50 +0,0 @@
-/**
- * Copyright 2021 Huawei Technologies Co., Ltd
- *
- * 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.
- */
-
-#ifndef MINDSPORE_LITE_MICRO_CODER_GENERATOR_BENCHMARK_COMPONENT_H_
-#define MINDSPORE_LITE_MICRO_CODER_GENERATOR_BENCHMARK_COMPONENT_H_
-
-#include <map>
-#include <string>
-#include <vector>
-#include <memory>
-#include <fstream>
-#include "src/tensor.h"
-#include "coder/context.h"
-
-namespace mindspore::lite::micro {
-void CodeBenchmarkHeader(std::ofstream &ofs, const std::string &header);
-
-void CodeBenchmarkUsage(std::ofstream &ofs);
-
-void CodeBenchmarkWarmup(std::ofstream &ofs, const std::string &module_name);
-
-void CodeBenchmarkSetInputs(std::ofstream &ofs, const std::string &module_name,
-                            const std::unique_ptr<CoderContext> &ctx);
-
-void CodeBenchmarkSetBuffer(std::ofstream &ofs, const std::string &module_name);
-
-void CodeBenchmarkInitWeight(std::ofstream &ofs, const std::string &module_name);
-
-void CodeBenchmarkInference(std::ofstream &ofs, const std::string &module_name);
-
-void CodeBenchmarkPrintOutputs(std::ofstream &ofs, const std::string &module_name);
-
-void CodeBenchmarkFreeResourse(std::ofstream &ofs, const std::string &module_name, size_t inputs_num);
-
-}  // namespace mindspore::lite::micro
-
-#endif  // MINDSPORE_LITE_MICRO_CODER_GENERATOR_BENCHMARK_COMPONENT_H_

mindspore/lite/micro/coder/generator/component/cmake_component.cc

@@ -32,10 +32,11 @@ void CodeCMakeNetLibrary(std::ofstream &ofs, const std::unique_ptr<CoderContext>
     ofs << "    " << c_file << ".o\n";
   }
   ofs << "    net_weight.c.o\n"
-      << "    net.c.o\n";
+      << "    net.c.o\n"
-  if (config->interface() == Interface_CPP) {
+      << "    session.cc.o\n"
-    ofs << "    session.cc.o\n"
+      << "    tensor.cc.o\n";
-        << "    tensor.cc.o\n";
+  if (config->debug_mode()) {
+    ofs << "    debug_utils.c.o\n";
   }
   ofs << ")\n";
   std::set<std::string> kernel_cmake_asm_set_files = ctx->asm_files();

mindspore/lite/micro/coder/generator/component/cmake_component.h

@@ -23,7 +23,7 @@
 #include <memory>
 #include <fstream>
 #include "src/tensor.h"
-#include "coder/coder_config.h"
+#include "coder/config.h"
 #include "coder/context.h"
 
 namespace mindspore::lite::micro {

mindspore/lite/micro/coder/generator/component/common_component.cc

@@ -25,12 +25,6 @@
 #include "nnacl/op_base.h"
 
 namespace mindspore::lite::micro {
-void CodeSourceFileInclude(std::ofstream &ofs, const std::string &weight_file, const std::string &header) {
-  ofs << g_hwLicense << "#include \"microtensor.h\"\n"
-      << "#include \"" << weight_file << "\"\n"
-      << "#include \"" << header << "\"\n\n";
-}
-
 void CodeSessionCompileGraph(std::ofstream &ofs, const std::unique_ptr<CoderContext> &ctx) {
   std::vector<Tensor *> inputs = ctx->graph_inputs();
   std::vector<Tensor *> outputs = ctx->graph_outputs();
@@ -84,7 +78,7 @@ void CodeCopyOutputsImplement(std::ofstream &ofs, const std::unique_ptr<CoderCon
          "}\n\n";
 }
 
-void CodeInputAndOutputState(std::ofstream &ofs, const std::string &module_name) {
+void CodeInputState(std::ofstream &ofs, const std::string &module_name) {
   ofs << "/**\n"
       << "  * set input tensors\n"
       << "  * @param inputs, the input data ptr's array of the model, the tensors' count of input may be greater than "
@@ -92,37 +86,9 @@ void CodeInputAndOutputState(std::ofstream &ofs, const std::string &module_name)
       << "  * @param num, the input data's number of the model.\n"
       << "  **/\n"
       << "int " << module_name << "_SetInputs(const void **inputs, int num);\n\n";
-
-  ofs << "/**\n"
-      << "  * get output tensor of the model \n"
-      << "  **/\n"
-      << "const MicroTensorList *" << module_name << "_GetOutputs();\n\n";
 }
 
-void PrintMicroTensors(std::ofstream &ofs, std::vector<Tensor *> tensors, const std::string &name,
+void CodeInputImplement(std::ofstream &ofs, const std::string &module_name, const std::unique_ptr<CoderContext> &ctx) {
-                       const std::map<Tensor *, std::string> &tensors_map) {
-  for (size_t i = 0; i < tensors.size(); ++i) {
-    Tensor *tensor = tensors[i];
-    auto item = tensors_map.find(tensor);
-    if (item == tensors_map.end()) {
-      MS_LOG(ERROR) << "nonexistent tensor";
-      break;
-    }
-    ofs << "  static int dim" << i << "[] = {";
-    for (size_t j = 0; j < tensor->shape().size(); ++j) {
-      ofs << tensor->shape()[j] << ", ";
-    }
-    ofs << "};\n"
-        << "  " << name << "[" << i << "].ndim = " << tensor->shape().size() << ";\n"
-        << "  " << name << "[" << i << "].dim = dim" << i << ";\n"
-        << "  " << name << "[" << i << "].type = " << EnumMicroTensorDataType(tensor->data_type()) << ";\n"
-        << "  " << name << "[" << i << "].format = " << EnumMicroTensorFormat(tensor->format()) << ";\n"
-        << "  " << name << "[" << i << "].data =" << item->second << ";\n";
-  }
-}
-
-void CodeInputAndOutputImplement(std::ofstream &ofs, const std::string &module_name,
-                                 const std::unique_ptr<CoderContext> &ctx) {
   // input tensors
   std::vector<Tensor *> inputs = ctx->graph_inputs();
   for (size_t i = 0; i < inputs.size(); ++i) {
@@ -140,20 +106,6 @@ void CodeInputAndOutputImplement(std::ofstream &ofs, const std::string &module_n
     ofs << "\t" << ctx->input_name() << i << " = inputs[" << i << "];\n";
   }
   ofs << "  return RET_OK;\n}\n";
-
-  // output tensors
-  std::vector<Tensor *> outputs = ctx->graph_outputs();
-  size_t output_num = outputs.size();
-  std::string output_name = ctx->output_name();
-
-  ofs << "const MicroTensorList* " << module_name << "_GetOutputs() {\n"
-      << "  static MicroTensor " << output_name << "[" << output_num << "] ;\n";
-
-  PrintMicroTensors(ofs, outputs, output_name, ctx->tensors_map());
-  ofs << "  static MicroTensorList  " << module_name << "_TensorArray;\n"
-      << "  " << module_name << "_TensorArray.num = " << output_num << ";\n"
-      << "  " << module_name << "_TensorArray.tensor = &" << output_name << "[0];\n"
-      << "  return  &" << module_name << "_TensorArray; \n}\n";
 }
 
 void CodeGraphQuantArgsState(std::ofstream &ofs, const std::string &module_name) {

mindspore/lite/micro/coder/generator/component/common_component.h

@@ -26,16 +26,13 @@
 #include "coder/context.h"
 
 namespace mindspore::lite::micro {
-void CodeSourceFileInclude(std::ofstream &ofs, const std::string &weight_file, const std::string &header);
-
 void CodeSessionCompileGraph(std::ofstream &ofs, const std::unique_ptr<CoderContext> &ctx);
 
 void CodeCopyOutputsState(std::ofstream &ofs);
 void CodeCopyOutputsImplement(std::ofstream &ofs, const std::unique_ptr<CoderContext> &ctx);
 
-void CodeInputAndOutputState(std::ofstream &ofs, const std::string &module_name);
+void CodeInputState(std::ofstream &ofs, const std::string &module_name);
-void CodeInputAndOutputImplement(std::ofstream &ofs, const std::string &module_name,
+void CodeInputImplement(std::ofstream &ofs, const std::string &module_name, const std::unique_ptr<CoderContext> &ctx);
-                                 const std::unique_ptr<CoderContext> &ctx);
 
 void CodeGraphQuantArgsState(std::ofstream &ofs, const std::string &module_name);
 void CodeGraphQuantArgsImplement(std::ofstream &ofs, const std::string &module_name,

mindspore/lite/micro/coder/generator/component/component.cc

@@ -1,43 +0,0 @@
-/**
- * Copyright 2021 Huawei Technologies Co., Ltd
- *
- * 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 "coder/generator/component/component.h"
-
-namespace mindspore::lite::micro {
-
-const char *kModelName = "net";
-const char *kSession = "session";
-
-const char *kByteType = "unsigned char *";
-const char *kConstByteType = "const unsigned char *";
-
-const char *kNameSpaceMindSpore = "namespace mindspore";
-const char *kNameSpaceLite = "namespace lite";
-
-const char *kExternCpp = R"RAW(
-#ifdef __cplusplus
-extern "C" {
-#endif
-
-)RAW";
-
-const char *kEndExternCpp = R"RAW(
-#ifdef __cplusplus
-}
-#endif
-
-)RAW";
-
-}  // namespace mindspore::lite::micro

mindspore/lite/micro/coder/generator/component/component.h

@@ -19,18 +19,30 @@
 
 namespace mindspore::lite::micro {
 
-extern const char *kModelName;
+constexpr auto kModelName = "net";
 
-extern const char *kSession;
+constexpr auto kSourcePath = "/src/";
 
-extern const char *kByteType;
+constexpr auto kBenchmarkPath = "/benchmark/";
-extern const char *kConstByteType;
+constexpr auto kBenchmarkFile = "benchmark.cc";
 
-extern const char *kNameSpaceMindSpore;
+constexpr auto kSession = "session";
-extern const char *kNameSpaceLite;
+constexpr auto kTensor = "tensor";
 
-extern const char *kExternCpp;
+constexpr auto kNameSpaceMindSpore = "namespace mindspore";
-extern const char *kEndExternCpp;
+constexpr auto kNameSpaceLite = "namespace lite";
+
+constexpr auto kDebugUtils = "debug_utils.h";
+
+constexpr auto kExternCpp =
+  "#ifdef __cplusplus\n"
+  "extern \"C\" {\n"
+  "#endif\n";
+
+constexpr char kEndExternCpp[] =
+  "#ifdef __cplusplus\n"
+  "}\n"
+  "#endif\n";
 
 }  // namespace mindspore::lite::micro
 

mindspore/lite/micro/coder/generator/component/const_blocks/benchmark.cc

@@ -19,6 +19,7 @@
 namespace mindspore::lite::micro {
 
 const char *benchmark_source = R"RAW(
+
 /**
  * Copyright 2021 Huawei Technologies Co., Ltd
  *
@@ -58,6 +59,55 @@ void usage() {
     "args[5]: runtime thread bind mode\n\n");
 }
 
+template <typename T>
+void PrintData(void *data, size_t data_number) {
+  if (data == nullptr) {
+    return;
+  }
+  auto casted_data = static_cast<T *>(data);
+  for (size_t i = 0; i < 10 && i < data_number; i++) {
+    std::cout << std::to_string(casted_data[i]) << ", ";
+  }
+  std::cout << std::endl;
+}
+
+void TensorToString(tensor::MSTensor *tensor) {
+  uint8_t i = 0;
+  std::cout << "uint8: " << i << std::endl;
+
+  std::cout << "Name: " << tensor->tensor_name();
+  std::cout << ", DataType: " << tensor->data_type();
+  std::cout << ", Size: " << tensor->Size();
+  std::cout << ", Shape:";
+  for (auto &dim : tensor->shape()) {
+    std::cout << " " << dim;
+  }
+  std::cout << ", Data:" << std::endl;
+  switch (tensor->data_type()) {
+    case kNumberTypeFloat32: {
+      PrintData<float>(tensor->MutableData(), tensor->ElementsNum());
+    } break;
+    case kNumberTypeFloat16: {
+      PrintData<int16_t>(tensor->MutableData(), tensor->ElementsNum());
+    } break;
+    case kNumberTypeInt32: {
+      PrintData<int32_t>(tensor->MutableData(), tensor->ElementsNum());
+    } break;
+    case kNumberTypeInt16: {
+      PrintData<int16_t>(tensor->MutableData(), tensor->ElementsNum());
+    } break;
+    case kNumberTypeInt8: {
+      PrintData<int8_t>(tensor->MutableData(), tensor->ElementsNum());
+    } break;
+    case kNumberTypeUInt8: {
+      PrintData<uint8_t>(tensor->MutableData(), tensor->ElementsNum());
+    } break;
+    default:
+      std::cout << "Unsupported data type to print" << std::endl;
+      break;
+  }
+}
+
 int main(int argc, const char **argv) {
   if (argc < 2) {
     std::cout << "input command is invalid\n" << std::endl;
@@ -104,7 +154,7 @@ int main(int argc, const char **argv) {
   std::cout << "output size: " << outputs.size() << std::endl;
   for (const auto &item : outputs) {
     auto output = item.second;
-    std::cout << "name: " << output->tensor_name() << ", size: " << output->Size() << std::endl;
+    TensorToString(output);
   }
 
   std::cout << "run benchmark success" << std::endl;

mindspore/lite/micro/coder/generator/component/const_blocks/cmake_lists.cc

@@ -26,7 +26,12 @@ if(NOT DEFINED MODEL_LIB)
     message(FATAL_ERROR "MODEL_LIB not set")
 endif()
 
+if(NOT DEFINED HEADER_PATH)
+    message(FATAL_ERROR "HEADER_PATH not set")
+endif()
+
 get_filename_component(MODEL_LIB ${MODEL_LIB} ABSOLUTE BASE_DIR ${CMAKE_CURRENT_BINARY_DIR})
+get_filename_component(HEADER_PATH ${HEADER_PATH} ABSOLUTE BASE_DIR ${CMAKE_CURRENT_BINARY_DIR})
 
 function(parse_lib_info lib_full_path lib_name lib_path)
     string(FIND "${lib_full_path}" "/" POS REVERSE)
@@ -68,9 +73,9 @@ if("${CMAKE_BUILD_TYPE}" STREQUAL "Debug")
     set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -fvisibility=default")
     set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fvisibility=default")
 else()
-    set(CMAKE_C_FLAGS "-fPIC -fPIE -D_FORTIFY_SOURCE=2 -O2 -Wall -Werror -fstack-protector-strong -Wno-attributes \
+    set(CMAKE_C_FLAGS "-fPIC -fPIE -D_FORTIFY_SOURCE=2 -O3 -Wall -Werror -fstack-protector-strong -Wno-attributes \
     -Wno-deprecated-declarations -Wno-missing-braces ${CMAKE_C_FLAGS}")
-    set(CMAKE_CXX_FLAGS "-fPIC -fPIE -D_FORTIFY_SOURCE=2 -O2 -Wall -Werror -fstack-protector-strong -Wno-attributes \
+    set(CMAKE_CXX_FLAGS "-fPIC -fPIE -D_FORTIFY_SOURCE=2 -O3 -Wall -Werror -fstack-protector-strong -Wno-attributes \
     -Wno-deprecated-declarations -Wno-missing-braces -Wno-overloaded-virtual ${CMAKE_CXX_FLAGS}")
 endif()
 link_directories(${MODEL_LIB_PATH})
@@ -92,8 +97,13 @@ if(NOT DEFINED OP_HEADER_PATH)
     message(FATAL_ERROR "OP_HEADER_PATH not set")
 endif()
 
+if(NOT DEFINED HEADER_PATH)
+    message(FATAL_ERROR "HEADER_PATH not set")
+endif()
+
 get_filename_component(OP_LIB ${OP_LIB} ABSOLUTE BASE_DIR ${CMAKE_CURRENT_BINARY_DIR})
 get_filename_component(OP_HEADER_PATH ${OP_HEADER_PATH} ABSOLUTE BASE_DIR ${CMAKE_CURRENT_BINARY_DIR})
+get_filename_component(HEADER_PATH ${HEADER_PATH} ABSOLUTE BASE_DIR ${CMAKE_CURRENT_BINARY_DIR})
 
 message("operator lib path: ${OP_LIB}")
 message("operator header path: ${OP_HEADER_PATH}")
@@ -130,9 +140,9 @@ if("${CMAKE_BUILD_TYPE}" STREQUAL "Debug")
     set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -fvisibility=default")
     set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fvisibility=default")
 else()
-    set(CMAKE_C_FLAGS "-fPIC -fPIE -D_FORTIFY_SOURCE=2 -O2 -Wall -Werror -fstack-protector-strong -Wno-attributes \
+    set(CMAKE_C_FLAGS "-fPIC -fPIE -D_FORTIFY_SOURCE=2 -O3 -Wall -Werror -fstack-protector-strong -Wno-attributes \
     -Wno-deprecated-declarations -Wno-missing-braces ${CMAKE_C_FLAGS}")
-    set(CMAKE_CXX_FLAGS "-fPIC -fPIE -D_FORTIFY_SOURCE=2 -O2 -Wall -Werror -fstack-protector-strong -Wno-attributes \
+    set(CMAKE_CXX_FLAGS "-fPIC -fPIE -D_FORTIFY_SOURCE=2 -O3 -Wall -Werror -fstack-protector-strong -Wno-attributes \
     -Wno-deprecated-declarations -Wno-missing-braces -Wno-overloaded-virtual ${CMAKE_CXX_FLAGS}")
 endif()
 

mindspore/lite/micro/coder/generator/component/const_blocks/debug_utils.cc

@@ -42,14 +42,54 @@ const char *debug_utils_h = R"RAW(
 #include <sys/time.h>
 #include <time.h>
 #include <stdint.h>
-#include "microtensor.h"
+
+#define MICRO_INFO(content, args...) \
+  { printf("[INFO] %s|%d: " #content "\r\n", __func__, __LINE__, ##args); }
+#define MICRO_ERROR(content, args...) \
+  { printf("[ERROR] %s|%d: " #content "\r\n", __func__, __LINE__, ##args); }
+
+enum DataType {
+  DataType_DT_FLOAT = 0,
+  DataType_DT_FLOAT16 = 1,
+  DataType_DT_INT8 = 2,
+  DataType_DT_INT32 = 3,
+  DataType_DT_UINT8 = 4,
+  DataType_DT_INT16 = 5,
+  DataType_DT_UINT32 = 8,
+  DataType_DT_INT64 = 9,
+  DataType_DT_UINT16 = 10,
+  DataType_DT_UNDEFINED = 16,
+  DataType_MIN = DataType_DT_FLOAT,
+  DataType_MAX = DataType_DT_UNDEFINED
+};
+
+enum Format {
+  Format_NCHW = 0,
+  Format_NHWC = 1,
+  Format_HWKC = 2,
+  Format_HWCK = 3,
+  Format_KCHW = 4,
+  Format_CKHW = 5,
+  Format_KHWC = 6,
+  Format_CHWK = 7,
+  Format_NC4HW4 = 100,
+  Format_NUM_OF_FORMAT = 101,
+  Format_MIN = Format_NCHW,
+  Format_MAX = Format_NUM_OF_FORMAT
+};
+
+typedef struct {
+  enum DataType type;
+  enum Format format;
+  int ndim;
+  int *dim;
+  void *data;
+} MicroTensor;
 
 void PrintTensor(MicroTensor *tensor, FILE *output_file, const char *is_input);
 
 void PrintTensorData(MicroTensor *tensor);
 
-uint64_t GetTimeUs();
-
 #endif  // MINDSPORE_LITE_MICRO_MICRODEBUGUTIL_H_
 
 )RAW";
@@ -259,17 +299,6 @@ void PrintTensor(MicroTensor *tensor, FILE *output_file, const char *is_input) {
   (void)fflush(output_file);
 }
 
-uint64_t GetTimeUs() {
-  const int USEC = 1000000;
-  const int MSEC = 1000;
-  struct timespec ts = {0, 0};
-  if (clock_gettime(CLOCK_MONOTONIC, &ts) != 0) {
-    return 0;
-  }
-  uint64_t retval = (uint64_t)((ts.tv_sec * USEC) + (ts.tv_nsec / MSEC));
-  return retval;
-}
-
 )RAW";
 
 }  // namespace mindspore::lite::micro

mindspore/lite/micro/coder/generator/component/const_blocks/micro_tensor.cc

@@ -1,111 +0,0 @@
-/**
- * Copyright 2021 Huawei Technologies Co., Ltd
- *
- * 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 "coder/generator/component/const_blocks/micro_tensor.h"
-
-namespace mindspore::lite::micro {
-
-const char *micro_tensor_h = R"RAW(
-/**
- * Copyright 2021 Huawei Technologies Co., Ltd
- *
- * 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.
- */
-
-#ifndef MSMICRO_TENSOR_H
-#define MSMICRO_TENSOR_H
-
-#include <stdlib.h>
-#include <string.h>
-#include <stdio.h>
-#include <stdbool.h>
-#include <stdint.h>
-
-#define MICRO_INFO(content, args...) \
-  { printf("[INFO] %s|%d: " #content "\r\n", __func__, __LINE__, ##args); }
-#define MICRO_ERROR(content, args...) \
-  { printf("[ERROR] %s|%d: " #content "\r\n", __func__, __LINE__, ##args); }
-
-enum STATUS {
-  RET_OK = 0,
-  RET_ERROR = 1,
-};
-
-enum DataType {
-  DataType_DT_FLOAT = 0,
-  DataType_DT_FLOAT16 = 1,
-  DataType_DT_INT8 = 2,
-  DataType_DT_INT32 = 3,
-  DataType_DT_UINT8 = 4,
-  DataType_DT_INT16 = 5,
-  DataType_DT_UINT32 = 8,
-  DataType_DT_INT64 = 9,
-  DataType_DT_UINT16 = 10,
-  DataType_DT_UNDEFINED = 16,
-  DataType_MIN = DataType_DT_FLOAT,
-  DataType_MAX = DataType_DT_UNDEFINED
-};
-
-enum Format {
-  Format_NCHW = 0,
-  Format_NHWC = 1,
-  Format_HWKC = 2,
-  Format_HWCK = 3,
-  Format_KCHW = 4,
-  Format_CKHW = 5,
-  Format_KHWC = 6,
-  Format_CHWK = 7,
-  Format_NC4HW4 = 100,
-  Format_NUM_OF_FORMAT = 101,
-  Format_MIN = Format_NCHW,
-  Format_MAX = Format_NUM_OF_FORMAT
-};
-
-typedef struct {
-  enum DataType type;
-  enum Format format;
-  int ndim;
-  int *dim;
-  void *data;
-} MicroTensor;
-
-typedef struct {
-  int num;
-  MicroTensor *tensor;
-} MicroTensorList;
-
-typedef struct {
-  float in_scale;
-  float out_scale;
-  int in_zero_point;
-  int out_zero_point;
-} GraphQuantArgs;
-
-#endif  // MSMICRO_TENSOR_H
-
-)RAW";
-
-}  // namespace mindspore::lite::micro

mindspore/lite/micro/coder/generator/component/const_blocks/micro_tensor.h

@@ -1,25 +0,0 @@
-/**
- * Copyright 2021 Huawei Technologies Co., Ltd
- *
- * 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.
- */
-#ifndef MINDSPORE_LITE_MICRO_CODER_GENERATOR_CONST_BLOCKS_MICRO_TENSOR_H_
-#define MINDSPORE_LITE_MICRO_CODER_GENERATOR_CONST_BLOCKS_MICRO_TENSOR_H_
-
-namespace mindspore::lite::micro {
-
-extern const char *micro_tensor_h;
-
-}  // namespace mindspore::lite::micro
-
-#endif  // MINDSPORE_LITE_MICRO_CODER_GENERATOR_CONST_BLOCKS_MICRO_TENSOR_H_

mindspore/lite/micro/coder/generator/component/const_blocks/thread_pool.cc

@@ -1,99 +0,0 @@
-/**
- * Copyright 2021 Huawei Technologies Co., Ltd
- *
- * 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 "coder/generator/component/const_blocks/thread_pool.h"
-
-namespace mindspore::lite::micro {
-
-const char *thread_pool_h = R"RAW(
-/**
- * Copyright 2021 Huawei Technologies Co., Ltd
- *
- * 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.
- */
-
-#ifndef MINDSPORE_LITE_SRC_RUNTIME_THREAD_POOL_H_
-#define MINDSPORE_LITE_SRC_RUNTIME_THREAD_POOL_H_
-
-#include <stdbool.h>
-
-#define MAX_TASK_NUM (2)
-
-// brief BindMode defined for holding bind cpu strategy argument.
-typedef enum {
-  NO_BIND_MODE = 0, /**< no bind */
-  HIGHER_MODE = 1,  /**< bind higher cpu first */
-  MID_MODE = 2      /**< bind middle cpu first */
-} BindMode;
-
-struct ThreadPool;
-
-struct ThreadPool *CreateThreadPool(int thread_num, int mode);
-
-/**
- *
- * @param session_index, support multi session
- * @param job
- * @param content
- * @param task_num
- */
-int ParallelLaunch(struct ThreadPool *thread_pool, int (*job)(void *, int), void *content, int task_num);
-
-/**
- * bind each thread to specified cpu core
- * @param is_bind
- * @param mode
- */
-int BindThreads(struct ThreadPool *thread_pool, bool is_bind, int mode);
-
-/**
- * activate the thread pool
- * @param thread_pool_id
- */
-void ActivateThreadPool(struct ThreadPool *thread_pool);
-
-/**
- * deactivate the thread pool
- * @param thread_pool_id
- */
-void DeactivateThreadPool(struct ThreadPool *thread_pool);
-
-/**
- *
- * @return current thread num
- */
-int GetCurrentThreadNum(struct ThreadPool *thread_pool);
-
-/**
- * destroy thread pool, and release resource
- */
-void DestroyThreadPool(struct ThreadPool *thread_pool);
-
-#endif  // MINDSPORE_LITE_SRC_RUNTIME_THREAD_POOL_H_
-
-)RAW";
-
-}  // namespace mindspore::lite::micro

mindspore/lite/micro/coder/generator/component/const_blocks/thread_pool.h

@@ -1,26 +0,0 @@
-/**
- * Copyright 2021 Huawei Technologies Co., Ltd
- *
- * 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.
- */
-
-#ifndef MINDSPORE_LITE_MICRO_CODER_GENERATOR_CONST_BLOCKS_THREAD_POOL_H_
-#define MINDSPORE_LITE_MICRO_CODER_GENERATOR_CONST_BLOCKS_THREAD_POOL_H_
-
-namespace mindspore::lite::micro {
-
-extern const char *thread_pool_h;
-
-}  // namespace mindspore::lite::micro
-
-#endif  // MINDSPORE_LITE_MICRO_CODER_GENERATOR_CONST_BLOCKS_THREAD_POOL_H_

mindspore/lite/micro/coder/generator/component/weight_component.cc

@@ -30,8 +30,11 @@ void CodeWeightFileHeader(std::ofstream &ofs, const std::unique_ptr<CoderContext
   }
   ofs << "#include <stdlib.h>\n"
       << "#include <string.h>\n"
-      << "#include \"microtensor.h\"\n\n"
       << "extern unsigned char *" << ctx->buffer_name() << ";\n";
+  ofs << "enum STATUS {\n"
+         "  RET_OK = 0,\n"
+         "  RET_ERROR = 1,\n"
+         "};\n\n";
 }
 
 void CodeModelParamsState(std::ofstream &ofs, const std::map<std::string, Tensor *> &weights) {

mindspore/lite/micro/coder/generator/component/weight_component.h

@@ -23,7 +23,7 @@
 #include <memory>
 #include <fstream>
 #include "src/tensor.h"
-#include "coder/coder_config.h"
+#include "coder/config.h"
 #include "coder/context.h"
 
 namespace mindspore::lite::micro {

mindspore/lite/micro/coder/generator/generator.cc

@@ -17,14 +17,13 @@
 #include <sys/stat.h>
 #include <set>
 #include <fstream>
+#include "coder/generator/component/component.h"
 #include "coder/generator/component/cmake_component.h"
 #include "coder/generator/component/weight_component.h"
 #include "coder/generator/component/common_component.h"
-#include "coder/generator/component/const_blocks/micro_tensor.h"
 #include "coder/generator/component/const_blocks/cmake_lists.h"
 #include "coder/generator/component/const_blocks/debug_utils.h"
 #include "coder/generator/component/const_blocks/load_input.h"
-#include "coder/generator/component/const_blocks/thread_pool.h"
 #include "coder/generator/component/const_blocks/msession.h"
 #include "coder/generator/component/const_blocks/mtensor.h"
 #include "coder/generator/component/const_blocks/benchmark.h"
@@ -51,14 +50,8 @@ Generator::Generator(std::unique_ptr<CoderContext> ctx) {
   this->net_inc_hfile_ = module_name + ".h";
   this->net_src_cfile_ = module_name + ".c";
   this->net_weight_hfile_ = module_name + "_weight.h";
-  if (config_->interface() == Interface_CPP) {
+  this->net_src_file_path_ = config_->code_path() + kSourcePath;
-    this->net_main_cfile_ = "benchmark.cc";
+  this->net_main_file_path_ = config_->code_path() + kBenchmarkPath;
-  } else {
-    this->net_main_cfile_ = "benchmark.c";
-  }
-  this->net_src_file_path_ = config_->code_path() + "/src/";
-  this->net_inc_file_path_ = config_->code_path() + "/include/";
-  this->net_main_file_path_ = config_->code_path() + "/benchmark/";
   origin_umask_ = umask(user_umask_);
   MS_LOG(DEBUG) << "origin umask: " << origin_umask_ << ", user umask: " << user_umask_;
 }
@@ -86,16 +79,11 @@ int Generator::CodeBenchmarkCMakeFile() {
   MS_CHECK_TRUE(!ofs.bad(), "filed to open file");
   MS_LOG(INFO) << "write " << test_cmake_file;
   ofs << "include_directories(${CMAKE_CURRENT_SOURCE_DIR})\n";
-  if (config_->interface() == Interface_CPP) {
+  ofs << "include_directories(${CMAKE_CURRENT_SOURCE_DIR}/../src/)\n";
-    ofs << "include_directories(${CMAKE_CURRENT_SOURCE_DIR}/../src/)\n";
+  ofs << "include_directories(${HEADER_PATH})\n";
-    ofs << "include_directories(${HEADER_PATH})\n";
-  } else {
-    ofs << "include_directories(${CMAKE_CURRENT_SOURCE_DIR}/../include/)\n";
-  }
   ofs << "set(SRC_FILES\n";
-  ofs << "\t\t" << net_main_cfile_ << "\n";
+  ofs << "\t\t" << kBenchmarkFile << "\n";
   ofs << "\t\tload_input.c\n";
-  ofs << "\t\tdebug_utils.c\n";
   ofs << ")\n";
   ofs.close();
   return RET_OK;
@@ -113,23 +101,17 @@ int Generator::CodeSourceCMakeFile() {
 
 int Generator::CodeStaticContent() {
   std::vector<std::pair<std::string, std::string>> const_blocks = {
-    {net_src_file_path_ + "CMakeLists.txt", src_cmake_lists_txt},
-    {net_main_file_path_ + "debug_utils.h", debug_utils_h},
-    {net_main_file_path_ + "debug_utils.c", debug_utils_c},
     {net_main_file_path_ + "load_input.h", load_input_h},
     {net_main_file_path_ + "load_input.c", load_input_c},
-    {net_main_file_path_ + "CMakeLists.txt", bench_cmake_lists_txt}};
+    {net_main_file_path_ + "CMakeLists.txt", bench_cmake_lists_txt},
-  if (config_->interface() == Interface_CPP) {
+    {net_main_file_path_ + "benchmark.cc", benchmark_source},
-    const_blocks.emplace_back(net_src_file_path_ + "microtensor.h", micro_tensor_h);
+    {net_src_file_path_ + "CMakeLists.txt", src_cmake_lists_txt},
-    const_blocks.emplace_back(net_src_file_path_ + "session.h", session_header);
+    {net_src_file_path_ + "session.h", session_header},
-    const_blocks.emplace_back(net_src_file_path_ + "tensor.h", tensor_header);
+    {net_src_file_path_ + "tensor.h", tensor_header},
-    const_blocks.emplace_back(net_src_file_path_ + "tensor.cc", tensor_source);
+    {net_src_file_path_ + "tensor.cc", tensor_source}};
-    const_blocks.emplace_back(net_main_file_path_ + "benchmark.cc", benchmark_source);
+  if (config_->debug_mode()) {
-  } else {
+    const_blocks.emplace_back(std::make_pair(net_src_file_path_ + "debug_utils.h", debug_utils_h));
-    const_blocks.emplace_back(net_inc_file_path_ + "microtensor.h", micro_tensor_h);
+    const_blocks.emplace_back(std::make_pair(net_src_file_path_ + "debug_utils.c", debug_utils_c));
-  }
-  if (config_->support_parallel()) {
-    const_blocks.emplace_back(net_inc_file_path_ + "thread_pool.h", thread_pool_h);
   }
   for (const auto &static_block : const_blocks) {
     std::string file_name = static_block.first;
@@ -190,11 +172,7 @@ int Generator::GenerateCode() {
   MS_CHECK_RET_CODE(CodeSourceCMakeFile(), "code net cmake file failed.");
   MS_CHECK_RET_CODE(CodeBenchmarkCMakeFile(), "code benchmark cmake file failed.");
   MS_CHECK_RET_CODE(CodeStaticContent(), "code static content failed.");
-  if (config_->interface() == Interface_CPP) {
+  MS_CHECK_RET_CODE(CodeSessionImplement(), "code session file failed.");
-    MS_CHECK_RET_CODE(CodeSessionImplement(), "code session file failed.");
-  } else {
-    MS_CHECK_RET_CODE(CodeBenchmarkFile(), "code benchmark file failed.");
-  }
   return RET_OK;
 }
 }  // namespace mindspore::lite::micro

mindspore/lite/micro/coder/generator/generator.h

@@ -29,7 +29,7 @@
 #include "include/errorcode.h"
 #include "src/tensor.h"
 #include "coder/log.h"
-#include "coder/coder_config.h"
+#include "coder/config.h"
 #include "coder/context.h"
 #include "coder/utils/type_cast.h"
 
@@ -43,7 +43,6 @@ class Generator {
   int GenerateCode();
 
  protected:
-  virtual int CodeBenchmarkFile() = 0;
   virtual int CodeNetHFile() = 0;
   virtual int CodeNetCFile() = 0;
   virtual int CodeWeightFile();
@@ -56,10 +55,8 @@ class Generator {
   bool is_get_quant_args_{false};
   std::string net_inc_hfile_;
   std::string net_src_cfile_;
-  std::string net_main_cfile_;
   std::string net_weight_hfile_;
 
-  std::string net_inc_file_path_;
   std::string net_src_file_path_;
   std::string net_main_file_path_;
 

mindspore/lite/micro/coder/generator/inference/inference_generator.cc

@@ -19,7 +19,6 @@
 #include <string>
 #include "coder/generator/component/common_component.h"
 #include "coder/generator/component/parallel_component.h"
-#include "coder/generator/component/benchmark_component.h"
 #include "coder/generator/component/weight_component.h"
 #include "coder/generator/component/const_blocks/license.h"
 #include "coder/generator/component/component.h"
@@ -27,11 +26,7 @@
 namespace mindspore::lite::micro {
 int InferenceGenerator::CodeNetHFile() {
   std::string net_include_file;
-  if (config_->interface() == Interface_CPP) {
+  net_include_file = net_src_file_path_ + net_inc_hfile_;
-    net_include_file = net_src_file_path_ + net_inc_hfile_;
-  } else {
-    net_include_file = net_inc_file_path_ + net_inc_hfile_;
-  }
   std::ofstream ofs(net_include_file);
   MS_CHECK_TRUE(!ofs.bad(), "filed to open file");
   MS_LOG(INFO) << "write " << net_include_file;
@@ -39,12 +34,9 @@ int InferenceGenerator::CodeNetHFile() {
   if (config_->support_parallel()) {
     ofs << "#include \"thread_pool.h\"\n";
   }
-  ofs << "#include \"microtensor.h\"\n\n";
   ofs << kExternCpp;
-  CodeInputAndOutputState(ofs, config_->module_name());
+  CodeInputState(ofs, config_->module_name());
-  if (config_->interface() == Interface_CPP) {
+  CodeCopyOutputsState(ofs);
-    CodeCopyOutputsState(ofs);
-  }
   if (is_get_quant_args_) {
     CodeGraphQuantArgsState(ofs, config_->module_name());
   }
@@ -65,14 +57,17 @@ int InferenceGenerator::CodeNetCFile() {
   std::ofstream ofs(net_impl_file);
   MS_CHECK_TRUE(!ofs.bad(), "filed to open file");
   MS_LOG(INFO) << "write " << net_impl_file;
-  CodeSourceFileInclude(ofs, net_weight_hfile_, net_inc_hfile_);
+  ofs << g_hwLicense << "\n"
+      << "#include \"" << net_weight_hfile_ << "\"\n"
+      << "#include \"" << net_inc_hfile_ << "\"\n\n";
+  if (config_->debug_mode()) {
+    ofs << "#include \"" << kDebugUtils << "\"\n";
+  }
   if (config_->support_parallel()) {
     CodeSetGlobalThreadPoolImplement(ofs, config_->module_name());
   }
-  CodeInputAndOutputImplement(ofs, config_->module_name(), ctx_);
+  CodeInputImplement(ofs, config_->module_name(), ctx_);
-  if (config_->interface() == Interface_CPP) {
+  CodeCopyOutputsImplement(ofs, ctx_);
-    CodeCopyOutputsImplement(ofs, ctx_);
-  }
   CodeInitResourceImplement(ofs, config_->module_name(), ctx_);
   CodeFreeResourceImplement(ofs, config_->module_name(), ctx_);
   if (is_get_quant_args_) {
@@ -82,34 +77,4 @@ int InferenceGenerator::CodeNetCFile() {
   ofs.close();
   return RET_OK;
 }
-
-int InferenceGenerator::CodeBenchmarkFile() {
-  std::string net_main_impl_file = net_main_file_path_ + net_main_cfile_;
-  std::ofstream ofs(net_main_impl_file);
-  MS_LOG(INFO) << "write " << net_main_impl_file;
-  MS_CHECK_TRUE(!ofs.bad(), "filed to open file");
-  std::vector<Tensor *> inputs = ctx_->graph_inputs();
-  size_t inputs_num = inputs.size();
-
-  CodeBenchmarkHeader(ofs, net_inc_hfile_);
-  CodeBenchmarkUsage(ofs);
-  CodeBenchmarkWarmup(ofs, config_->module_name());
-
-  CodeBenchmarkSetInputs(ofs, config_->module_name(), ctx_);
-  CodeBenchmarkSetBuffer(ofs, config_->module_name());
-  if (config_->target() != kARM32M) {
-    CodeBenchmarkInitWeight(ofs, config_->module_name());
-  }
-  if (config_->support_parallel()) {
-    CodeCreateThreadPool(ofs, config_->module_name());
-  }
-  CodeBenchmarkInference(ofs, config_->module_name());
-  CodeBenchmarkPrintOutputs(ofs, config_->module_name());
-  if (config_->support_parallel()) {
-    CodeDestroyThreadPool(ofs);
-  }
-  CodeBenchmarkFreeResourse(ofs, config_->module_name(), inputs_num);
-  ofs.close();
-  return RET_OK;
-}
 }  // namespace mindspore::lite::micro

mindspore/lite/micro/coder/generator/inference/inference_generator.h

@@ -30,8 +30,6 @@ class InferenceGenerator : public Generator {
  private:
   int CodeNetHFile() override;
   int CodeNetCFile() override;
-
-  int CodeBenchmarkFile() override;
 };
 }  // namespace mindspore::lite::micro
 #endif  // MINDSPORE_LITE_MICRO_CODER_GENERATOR_INFERENCE_GENERATOR_H_

mindspore/lite/micro/coder/generator/train/train_generator.cc

@@ -18,7 +18,6 @@
 #include <vector>
 #include <string>
 #include "coder/generator/component/common_component.h"
-#include "coder/generator/component/benchmark_component.h"
 #include "coder/generator/component/weight_component.h"
 #include "coder/generator/component/train_component.h"
 #include "coder/generator/component/const_blocks/license.h"
@@ -35,7 +34,7 @@ void TrainGenerator::CodeGradientFunc(std::ofstream &ofs) const {
 }
 
 int TrainGenerator::CodeNetHFile() {
-  std::string net_include_file = net_inc_file_path_ + net_inc_hfile_;
+  std::string net_include_file = net_src_file_path_ + net_inc_hfile_;
   std::ofstream ofs(net_include_file);
   MS_CHECK_TRUE(!ofs.bad(), "filed to open file");
   MS_LOG(INFO) << "write " << net_include_file;
@@ -45,7 +44,7 @@ int TrainGenerator::CodeNetHFile() {
   }
   ofs << "#include \"microtensor.h\"\n\n";
   CodeTrainParams(ofs);
-  CodeInputAndOutputState(ofs, config_->module_name());
+  CodeInputState(ofs, config_->module_name());
   if (config_->target() != kARM32M) {
     CodeInitWeightState(ofs, config_->module_name());
   }
@@ -61,8 +60,7 @@ int TrainGenerator::CodeNetCFile() {
   std::ofstream ofs(net_impl_file);
   MS_CHECK_TRUE(!ofs.bad(), "filed to open file");
   MS_LOG(INFO) << "write " << net_impl_file;
-  CodeSourceFileInclude(ofs, net_weight_hfile_, net_inc_hfile_);
+  CodeInputImplement(ofs, config_->module_name(), ctx_);
-  CodeInputAndOutputImplement(ofs, config_->module_name(), ctx_);
   CodeInitResourceImplement(ofs, config_->module_name(), ctx_);
   CodeFreeResourceImplement(ofs, config_->module_name(), ctx_);
   CodeFeaturesImplement(ofs, config_->module_name(), ctx_);
@@ -72,26 +70,4 @@ int TrainGenerator::CodeNetCFile() {
   ofs.close();
   return RET_OK;
 }
-
-int TrainGenerator::CodeBenchmarkFile() {
-  std::string net_main_impl_file = net_main_file_path_ + net_main_cfile_;
-  std::ofstream ofs(net_main_impl_file);
-  MS_LOG(INFO) << "write " << net_main_impl_file;
-  MS_CHECK_TRUE(!ofs.bad(), "filed to open file");
-  std::vector<Tensor *> inputs = ctx_->graph_inputs();
-  size_t inputs_num = inputs.size();
-  CodeBenchmarkHeader(ofs, net_inc_hfile_);
-  CodeBenchmarkUsage(ofs);
-  CodeBenchmarkWarmup(ofs, config_->module_name());
-  CodeBenchmarkSetInputs(ofs, config_->module_name(), ctx_);
-  CodeBenchmarkSetBuffer(ofs, config_->module_name());
-  if (config_->target() != kARM32M) {
-    CodeBenchmarkInitWeight(ofs, config_->module_name());
-  }
-  CodeBenchmarkInference(ofs, config_->module_name());
-  CodeBenchmarkPrintOutputs(ofs, config_->module_name());
-  CodeBenchmarkFreeResourse(ofs, config_->module_name(), inputs_num);
-  ofs.close();
-  return RET_OK;
-}
 }  // namespace mindspore::lite::micro

mindspore/lite/micro/coder/generator/train/train_generator.h

@@ -30,9 +30,6 @@ class TrainGenerator : public Generator {
  private:
   int CodeNetHFile() override;
   int CodeNetCFile() override;
-
-  int CodeBenchmarkFile() override;
-
   void CodeGradientFunc(std::ofstream &ofs) const;
 };
 }  // namespace mindspore::lite::micro

mindspore/lite/micro/coder/graph.h

@@ -22,7 +22,7 @@
 #include <unordered_map>
 #include <vector>
 #include <string>
-#include "coder/coder_config.h"
+#include "coder/config.h"
 #include "include/context.h"
 #include "include/model.h"
 #include "schema/inner/model_generated.h"

mindspore/lite/micro/coder/opcoders/nnacl/int8/convolution_depthwise_int8_coder.cc

@@ -86,7 +86,9 @@ int ConvolutionDepthwiseINT8Coder::DoCode(CoderContext *const context) {
     {"nnacl/int8/conv_depthwise_int8.h", "nnacl/int8/pack_int8.h", "wrapper/int8/convolution_depthwise_int8_wrapper.h"},
     {"conv_depthwise_int8.c", "fixed_point.c", "pack_int8.c", "conv_int8.c", "winograd_transform.c",
      "convolution_depthwise_int8_wrapper.c"},
-    {"ConvDwInt8Row.S", "ConvDwInt8PostAlign4.S", "ConvDwInt8PostAlign4PerChannel.S"});
+    {"ConvDwInt8Row.S", "ConvDwInt8PostAlign4.S", "ConvDwInt8PostAlign4PerChannel.S", "ConvDw3x3Int8Stride2.S",
+     "ConvDw3x3Int8.S", "ConvDw3x3Int8Vertical.S", "ConvDw3x3Int8Horizontal.S", "ConvDw3x3Int8Corner.S",
+     "MatmulOptR4Int8.S", "ConvDwInt8Center.S", "DeconvDwInt8Center.S", "DeconvDwInt8Post.S", "MatmulDpInt8Opt.S"});
   nnacl::NNaclInt8Serializer code;
   code.precision(kPrecision);
   // call the op function

mindspore/lite/micro/coder/opcoders/op_coder_register.cc

@@ -16,6 +16,7 @@
 #include "coder/opcoders/op_coder_register.h"
 #include <utility>
 #include <string>
+#include "coder/utils/type_cast.h"
 namespace mindspore::lite::micro {
 
 bool CoderKey::operator<(const CoderKey rhs) const {

mindspore/lite/micro/coder/opcoders/op_coder_register.h

@@ -23,7 +23,7 @@
 #include <string>
 #include "src/lite_kernel.h"
 #include "include/model.h"
-#include "coder/coder_config.h"
+#include "coder/config.h"
 namespace mindspore::lite::micro {
 class OperatorCoder;
 using CoderCreatorFunc = std::function<std::unique_ptr<OperatorCoder>(

mindspore/lite/micro/coder/session.h

@@ -23,7 +23,7 @@
 #include "schema/inner/model_generated.h"
 #include "coder/graph.h"
 #include "coder/context.h"
-#include "coder/coder_config.h"
+#include "coder/config.h"
 #include "coder/allocator/allocator.h"
 #include "coder/opcoders/op_coder.h"
 

mindspore/lite/micro/coder/utils/dir_utils.cc

@@ -32,7 +32,7 @@ constexpr _mode_t kMicroDirMode = 0777;
 constexpr __mode_t kMicroDirMode = 0777;
 #endif
 
-static std::array<std::string, 3> kWorkDirs = {"src", "include", "benchmark"};
+static std::array<std::string, 3> kWorkDirs = {"src", "benchmark"};
 
 bool DirExists(const std::string &dir_path) {
   struct stat file_info;

mindspore/lite/micro/coder/utils/type_cast.cc

@@ -126,4 +126,21 @@ std::string EnumMicroTensorDataType(TypeId type) {
       return "DataType_DT_UNDEFINED";
   }
 }
+
+std::string EnumNameTarget(Target target) {
+  switch (target) {
+    case kX86:
+      return "kX86";
+    case kARM32M:
+      return "kARM32M";
+    case kARM32A:
+      return "kARM32A";
+    case kARM64:
+      return "kARM64";
+    case kAllTargets:
+      return "kAllTargets";
+    default:
+      return "kTargetUnknown";
+  }
+}
 }  // namespace mindspore::lite::micro

mindspore/lite/micro/coder/utils/type_cast.h

@@ -26,6 +26,7 @@
 #include "securec/include/securec.h"
 #include "src/tensor.h"
 #include "nnacl/int8/quantize.h"
+#include "coder/config.h"
 
 namespace mindspore::lite::micro {
 std::string EnumNameDataType(TypeId type);
@@ -36,6 +37,8 @@ std::string EnumMicroTensorFormat(schema::Format format);
 
 std::string EnumMicroTensorDataType(TypeId type);
 
+std::string EnumNameTarget(Target target);
+
 /**
  * @tparam T
  * @param t, basic data type variable, or tensor