forked from mindspore-Ecosystem/mindspore
!4332 fix tools bugs
Merge pull request !4332 from yeyunpeng2020/master_time_profile
This commit is contained in:
commit
66d6334791
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@ -67,7 +67,7 @@ std::string RealPath(const char *path) {
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MS_LOG(ERROR) << "path is too long";
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return "";
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}
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std::shared_ptr<char> resolvedPath(new (std::nothrow) char[PATH_MAX]{0});
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auto resolvedPath = std::make_unique<char[]>(PATH_MAX);
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if (resolvedPath == nullptr) {
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MS_LOG(ERROR) << "new resolvedPath failed";
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return "";
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@ -26,7 +26,15 @@ namespace mindspore::lite {
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Model *Model::Import(const char *model_buf, size_t size) {
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auto model = new Model();
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if (model_buf == nullptr) {
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MS_LOG(ERROR) << "model buf is null";
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return nullptr;
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}
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model->model_impl_ = ModelImpl::Import(model_buf, size);
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if (model->model_impl_ == nullptr) {
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MS_LOG(ERROR) << "model impl is null";
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return nullptr;
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}
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return model;
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}
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@ -21,7 +21,10 @@
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namespace mindspore::lite {
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ModelImpl *ModelImpl::Import(const char *model_buf, size_t size) {
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MS_EXCEPTION_IF_NULL(model_buf);
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if (model_buf == nullptr) {
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MS_LOG(ERROR) << "The model buf is nullptr";
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return nullptr;
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}
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flatbuffers::Verifier verify((const uint8_t *)model_buf, size);
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if (!schema::VerifyMetaGraphBuffer(verify)) {
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MS_LOG(ERROR) << "The buffer is invalid and fail to create graph.";
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@ -154,6 +154,9 @@ void Converter::CreateQuantizer(FuncGraphPtr funcGraph, const converter::Flags *
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int RunConverter(int argc, const char **argv) {
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auto flags = new converter::Flags;
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auto status = flags->Init(argc, argv);
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if (status == RET_SUCCESS_EXIT) {
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return 0;
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}
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if (status != 0) {
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MS_LOG(ERROR) << "converter::Flags Init failed: " << status;
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return 1;
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@ -14,7 +14,6 @@
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* limitations under the License.
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*/
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#include <regex>
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#include <string>
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#include "tools/converter/converter_flags.h"
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@ -43,31 +42,31 @@ int Flags::Init(int argc, const char **argv) {
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Option<std::string> err = this->ParseFlags(argc, argv);
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if (err.IsSome()) {
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MS_LOG(ERROR) << err.Get();
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std::cerr << err.Get();
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std::cerr << this->Usage() << std::endl;
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return 1;
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}
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if (this->help) {
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std::cerr << this->Usage() << std::endl;
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return 0;
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std::cout << this->Usage() << std::endl;
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return RET_SUCCESS_EXIT;
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}
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if (this->modelFile.empty()) {
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MS_LOG(ERROR) << "INPUT MISSING: model file path is necessary";
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std::cerr << "INPUT MISSING: model file path is necessary";
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return 1;
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}
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if (this->outputFile.empty()) {
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MS_LOG(ERROR) << "INPUT MISSING: output file path is necessary";
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std::cerr << "INPUT MISSING: output file path is necessary";
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return 1;
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}
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if (this->outputFile.rfind('/') == this->outputFile.length() - 1) {
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MS_LOG(ERROR) << "INPUT ILLEGAL: outputFile must be a valid file path";
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std::cerr << "INPUT ILLEGAL: outputFile must be a valid file path";
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return 1;
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}
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if (this->fmkIn.empty()) {
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MS_LOG(ERROR) << "INPUT MISSING: fmk is necessary";
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std::cerr << "INPUT MISSING: fmk is necessary";
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return 1;
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}
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if (this->inputInferenceTypeIn == "FLOAT") {
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@ -75,7 +74,7 @@ int Flags::Init(int argc, const char **argv) {
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} else if (this->inputInferenceTypeIn == "UINT8") {
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this->inputInferenceType = 1;
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} else {
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MS_LOG(ERROR) << "INPUT INVALID: inputInferenceType is invalid: %s", this->inputInferenceTypeIn.c_str();
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std::cerr << "INPUT INVALID: inputInferenceType is invalid: %s", this->inputInferenceTypeIn.c_str();
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return 1;
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}
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if (this->fmkIn == "CAFFE") {
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@ -85,12 +84,12 @@ int Flags::Init(int argc, const char **argv) {
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} else if (this->fmkIn == "TFLITE") {
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this->fmk = FmkType_TFLITE;
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} else {
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MS_LOG(ERROR) << "INPUT ILLEGAL: fmk must be TFLITE|CAFFE|MS";
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std::cerr << "INPUT ILLEGAL: fmk must be TFLITE|CAFFE|MS";
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return 1;
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}
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if (this->fmk != FmkType_CAFFE && !weightFile.empty()) {
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MS_LOG(ERROR) << "INPUT ILLEGAL: weightFile is not a valid flag";
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std::cerr << "INPUT ILLEGAL: weightFile is not a valid flag";
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return 1;
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}
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if (this->quantTypeIn == "AwareTrainning") {
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@ -102,7 +101,7 @@ int Flags::Init(int argc, const char **argv) {
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} else if (this->quantTypeIn.empty()) {
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this->quantType = QuantType_QUANT_NONE;
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} else {
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MS_LOG(ERROR) << "INPUT ILLEGAL: quantType must be AwareTrainning|WeightQuant|PostTraining";
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std::cerr << "INPUT ILLEGAL: quantType must be AwareTrainning|WeightQuant|PostTraining";
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return 1;
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}
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@ -71,7 +71,7 @@ int TimeProfile::ReadInputFile() {
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}
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auto tensor_data_size = inTensor->Size();
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if (size != tensor_data_size) {
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MS_LOG(ERROR) << "Input binary file size error, required: " << tensor_data_size << " in fact: %zu" << size;
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MS_LOG(ERROR) << "Input binary file size error, required: " << tensor_data_size << " in fact: " << size;
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return RET_ERROR;
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}
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auto input_data = inTensor->MutableData();
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@ -90,7 +90,7 @@ int TimeProfile::LoadInput() {
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} else {
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auto status = ReadInputFile();
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if (status != RET_OK) {
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MS_LOG(ERROR) << "ReadInputFile error, " << status;
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MS_LOG(ERROR) << "ReadInputFile error " << status;
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return RET_ERROR;
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}
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}
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@ -149,10 +149,10 @@ int TimeProfile::InitCallbackParameter() {
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uint64_t opEnd = GetTimeUs();
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if (after_inputs.empty()) {
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MS_LOG(INFO) << "The num of beforeInputs is empty";
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MS_LOG(INFO) << "The num of after inputs is empty";
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}
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if (after_outputs.empty()) {
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MS_LOG(INFO) << "The num of beforeOutputs is empty";
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MS_LOG(INFO) << "The num of after outputs is empty";
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}
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float cost = static_cast<float>(opEnd - op_begin_) / 1000.0f;
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@ -297,22 +297,34 @@ int TimeProfile::RunTimeProfile() {
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size_t size = 0;
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char *graphBuf = ReadFile(_flags->model_path_.c_str(), &size);
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if (graphBuf == nullptr) {
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MS_LOG(ERROR) << "Load graph failed while running %s", modelName.c_str();
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MS_LOG(ERROR) << "Load graph failed while running " << modelName.c_str();
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delete graphBuf;
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delete session_;
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return RET_ERROR;
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}
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auto model = lite::Model::Import(graphBuf, size);
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delete graphBuf;
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if (model == nullptr) {
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MS_LOG(ERROR) << "Import model file failed while running " << modelName.c_str();
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delete session_;
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delete model;
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return RET_ERROR;
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}
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auto ret = session_->CompileGraph(model);
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if (ret != RET_OK) {
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MS_LOG(ERROR) << "Compile graph failed.";
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delete session_;
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delete model;
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return RET_ERROR;
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}
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// load input
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MS_LOG(INFO) << "start generate input data";
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auto status = LoadInput();
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if (status != 0) {
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if (status != RET_OK) {
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MS_LOG(ERROR) << "Generate input data error";
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delete session_;
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delete model;
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return status;
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}
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@ -324,6 +336,8 @@ int TimeProfile::RunTimeProfile() {
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ret = session_->RunGraph(before_call_back_, after_call_back_);
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if (ret != RET_OK) {
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MS_LOG(ERROR) << "Run graph failed.";
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delete session_;
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delete model;
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return RET_ERROR;
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}
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auto outputs = session_->GetOutputs();
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@ -345,14 +359,8 @@ int TimeProfile::RunTimeProfile() {
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printf("\n total time: %5.5f ms, kernel cost: %5.5f ms \n\n", runCost, op_cost_total_ / _flags->loop_count_);
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printf("-------------------------------------------------------------------------\n");
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for (auto &msInput : ms_inputs_) {
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delete msInput;
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}
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ms_inputs_.clear();
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delete graphBuf;
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delete session_;
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delete model;
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delete session_;
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return ret;
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}
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