add increment building & remove redundant code & fix bug in benchmark

build.sh

@@ -444,11 +444,6 @@ build_protobuf() {
     fi
 }
 
-build_gtest() {
-    cd ${BASEPATH}
-    git submodule update --init --recursive third_party/googletest
-}
-
 gene_clhpp() {
     CL_SRC_DIR="${BASEPATH}/mindspore/lite/src/runtime/kernel/opencl/cl"
     for sub_dir in "${CL_SRC_DIR}"/*
@@ -530,9 +525,11 @@ build_lite()
       build_protobuf
     fi
     build_flatbuffer
-    build_gtest
 
     cd "${BASEPATH}/mindspore/lite"
+    if [[ "${INC_BUILD}" == "off" ]]; then
+        rm -rf build
+    fi
     mkdir -pv build
     cd build
     BUILD_TYPE="Release"

mindspore/lite/include/model.h

@@ -39,6 +39,7 @@ class Model {
  protected:
   std::shared_ptr<ModelImpl> modelImpl = nullptr;
 };
+
 class ModelBuilder {
  public:
   struct OutEdge {
@@ -54,4 +55,3 @@ class ModelBuilder {
 }  // namespace mindspore
 
 #endif  // MINDSPORE_LITE_INCLUDE_MODEL_H
-

mindspore/lite/src/lite_session.cc

@@ -68,44 +68,6 @@ int LiteSession::ConvertTensors(const lite::Model *model) {
   return RET_OK;
 }
 
-int LiteSession::ConvertKernels(const lite::Model *model, Context *context) {
-  //  MS_EXCEPTION_IF_NULL(model);
-  //  auto meta_graph = model->GetMetaGraph();
-  //  MS_EXCEPTION_IF_NULL(meta_graph);
-  //  uint32_t kernelCount = meta_graph->nodes()->size();
-  //  for (uint32_t i = 0; i < kernelCount; i++) {
-  //    auto cNode = meta_graph->nodes()->GetAs<schema::CNode>(i);
-  //    std::vector<tensor::Tensor *> inputs;
-  //    std::vector<tensor::Tensor *> outputs;
-  //    auto inIndexes = cNode->inputIndex();
-  //    for (size_t j = 0; j < inIndexes->size(); j++) {
-  //      inputs.emplace_back(this->tensors.at(size_t(inIndexes->GetAs<uint32_t>(j))));
-  //    }
-  //    auto outIndexes = cNode->outputIndex();
-  //    for (size_t j = 0; j < outIndexes->size(); j++) {
-  //      outputs.emplace_back(this->tensors.at(size_t(outIndexes->GetAs<uint32_t>(j))));
-  //    }
-  //    const auto *primitive = model->GetOp(cNode->name()->str());
-  //    if (primitive == nullptr) {
-  //      MS_LOG(ERROR) << "Op " << cNode->name()->str() << " should exist in model";
-  //      return RET_ERROR;
-  //    }
-  //    auto ret = primitive->InferShape(inputs, outputs);
-  //    if (0 != ret) {
-  //      MS_LOG(ERROR) << "InferShape failed, node : " << cNode->name()->str();
-  //      return ret;
-  //    }
-  //    auto *kernel = lite::KernelFactory::GetInstance()->GetKernel(inputs, outputs, cNode, context);
-  //    if (nullptr == kernel) {
-  //      MS_LOG(ERROR) << "Create kernel return nullptr, name: " << cNode->name()->str()
-  //                    << ", type: " << schema::EnumNamePrimitiveType(cNode->primitive()->value_type());
-  //      return RET_ERROR;
-  //    }
-  //    kernels.emplace_back(kernel);
-  //  }
-  return RET_OK;
-}
-
 void LiteSession::InitGraphInOutTensor(const lite::Model *model) {
   auto meta_graph = model->GetMetaGraph();
   MS_ASSERT(this->input_map.empty());

mindspore/lite/src/lite_session.h

@@ -56,7 +56,7 @@ class LiteSession : public session::LiteSession {
 
  protected:
   int ConvertTensors(const lite::Model *model);
-  int ConvertKernels(const lite::Model *model, Context *context);
+
   void InitGraphInOutTensor(const lite::Model *model);
 
  protected:

mindspore/lite/tools/benchmark/benchmark.cc

@@ -316,6 +316,8 @@ int Benchmark::MarkPerformance() {
 int Benchmark::MarkAccuracy() {
   MS_LOG(INFO) << "MarkAccuracy";
   for (size_t i = 0; i < msInputs.size(); i++) {
+    MS_ASSERT(msInputs.at(i) != nullptr);
+    MS_ASSERT(msInputs.at(i)->data_type() == TypeId::kNumberTypeFloat32);
     auto inData = reinterpret_cast<float *>(msInputs.at(i)->MutableData());
     std::cout << "InData" << i << ": ";
     for (size_t j = 0; j < 20; j++) {
@@ -331,14 +333,6 @@ int Benchmark::MarkAccuracy() {
 
   ReadCalibData();
   CompareOutput();
-  if (cleanData) {
-    for (auto &msOutput : msOutputs) {
-      for (auto &outputTensor : msOutput.second) {
-        delete outputTensor;
-      }
-    }
-    msOutputs.clear();
-  }
   return 0;
 }
 
@@ -407,10 +401,6 @@ int Benchmark::RunBenchmark(const std::string &deviceType) {
   }
 
   if (cleanData) {
-    for (auto &msInput : msInputs) {
-      delete msInput;
-    }
-    msInputs.clear();
     for (auto &data : calibData) {
       data.second->shape.clear();
       data.second->data.clear();