fix time_profile and converter bug

mindspore/lite/src/common/file_utils.cc

@@ -67,7 +67,7 @@ std::string RealPath(const char *path) {
     MS_LOG(ERROR) << "path is too long";
     return "";
   }
-  std::shared_ptr<char> resolvedPath(new (std::nothrow) char[PATH_MAX]{0});
+  auto resolvedPath = std::make_unique<char[]>(PATH_MAX);
   if (resolvedPath == nullptr) {
     MS_LOG(ERROR) << "new resolvedPath failed";
     return "";

mindspore/lite/src/model.cc

@@ -26,7 +26,15 @@ namespace mindspore::lite {
 
 Model *Model::Import(const char *model_buf, size_t size) {
   auto model = new Model();
+  if (model_buf == nullptr) {
+    MS_LOG(ERROR) << "model buf is null";
+    return nullptr;
+  }
   model->model_impl_ = ModelImpl::Import(model_buf, size);
+  if (model->model_impl_ == nullptr) {
+    MS_LOG(ERROR) << "model impl is null";
+    return nullptr;
+  }
   return model;
 }
 

mindspore/lite/src/model_impl.cc

@@ -21,7 +21,10 @@
 
 namespace mindspore::lite {
 ModelImpl *ModelImpl::Import(const char *model_buf, size_t size) {
-  MS_EXCEPTION_IF_NULL(model_buf);
+  if (model_buf == nullptr) {
+    MS_LOG(ERROR) << "The model buf is nullptr";
+    return nullptr;
+  }
   flatbuffers::Verifier verify((const uint8_t *)model_buf, size);
   if (!schema::VerifyMetaGraphBuffer(verify)) {
     MS_LOG(ERROR) << "The buffer is invalid and fail to create graph.";

mindspore/lite/tools/converter/converter.cc

@@ -153,6 +153,9 @@ void Converter::CreateQuantizer(FuncGraphPtr funcGraph, const converter::Flags *
 int RunConverter(int argc, const char **argv) {
   auto flags = new converter::Flags;
   auto status = flags->Init(argc, argv);
+  if (status == RET_SUCCESS_EXIT) {
+    return 0;
+  }
   if (status != 0) {
     MS_LOG(ERROR) << "converter::Flags Init failed: " << status;
     return 1;

mindspore/lite/tools/converter/converter_flags.cc

@@ -14,7 +14,6 @@
  * limitations under the License.
  */
 
-#include <regex>
 #include <string>
 #include "tools/converter/converter_flags.h"
 
@@ -43,31 +42,31 @@ int Flags::Init(int argc, const char **argv) {
   Option<std::string> err = this->ParseFlags(argc, argv);
 
   if (err.IsSome()) {
-    MS_LOG(ERROR) << err.Get();
+    std::cerr << err.Get();
     std::cerr << this->Usage() << std::endl;
     return 1;
   }
 
   if (this->help) {
-    std::cerr << this->Usage() << std::endl;
-    return 0;
+    std::cout << this->Usage() << std::endl;
+    return RET_SUCCESS_EXIT;
   }
   if (this->modelFile.empty()) {
-    MS_LOG(ERROR) << "INPUT MISSING: model file path is necessary";
+    std::cerr << "INPUT MISSING: model file path is necessary";
     return 1;
   }
   if (this->outputFile.empty()) {
-    MS_LOG(ERROR) << "INPUT MISSING: output file path is necessary";
+    std::cerr << "INPUT MISSING: output file path is necessary";
     return 1;
   }
 
   if (this->outputFile.rfind('/') == this->outputFile.length() - 1) {
-    MS_LOG(ERROR) << "INPUT ILLEGAL: outputFile must be a valid file path";
+    std::cerr << "INPUT ILLEGAL: outputFile must be a valid file path";
     return 1;
   }
 
   if (this->fmkIn.empty()) {
-    MS_LOG(ERROR) << "INPUT MISSING: fmk is necessary";
+    std::cerr << "INPUT MISSING: fmk is necessary";
     return 1;
   }
   if (this->inputInferenceTypeIn == "FLOAT") {
@@ -75,7 +74,7 @@ int Flags::Init(int argc, const char **argv) {
   } else if (this->inputInferenceTypeIn == "UINT8") {
     this->inputInferenceType = 1;
   } else {
-    MS_LOG(ERROR) << "INPUT INVALID: inputInferenceType is invalid: %s", this->inputInferenceTypeIn.c_str();
+    std::cerr << "INPUT INVALID: inputInferenceType is invalid: %s", this->inputInferenceTypeIn.c_str();
     return 1;
   }
   if (this->fmkIn == "CAFFE") {
@@ -85,12 +84,12 @@ int Flags::Init(int argc, const char **argv) {
   } else if (this->fmkIn == "TFLITE") {
     this->fmk = FmkType_TFLITE;
   } else {
-    MS_LOG(ERROR) << "INPUT ILLEGAL: fmk must be TFLITE|CAFFE|MS";
+    std::cerr << "INPUT ILLEGAL: fmk must be TFLITE|CAFFE|MS";
     return 1;
   }
 
   if (this->fmk != FmkType_CAFFE && !weightFile.empty()) {
-    MS_LOG(ERROR) << "INPUT ILLEGAL: weightFile is not a valid flag";
+    std::cerr << "INPUT ILLEGAL: weightFile is not a valid flag";
     return 1;
   }
   if (this->quantTypeIn == "AwareTrainning") {
@@ -102,7 +101,7 @@ int Flags::Init(int argc, const char **argv) {
   } else if (this->quantTypeIn.empty()) {
     this->quantType = QuantType_QUANT_NONE;
   } else {
-    MS_LOG(ERROR) << "INPUT ILLEGAL: quantType must be AwareTrainning|WeightQuant|PostTraining";
+    std::cerr << "INPUT ILLEGAL: quantType must be AwareTrainning|WeightQuant|PostTraining";
     return 1;
   }
 

mindspore/lite/tools/time_profile/time_profile.cc

@@ -71,7 +71,7 @@ int TimeProfile::ReadInputFile() {
   }
   auto tensor_data_size = inTensor->Size();
   if (size != tensor_data_size) {
-    MS_LOG(ERROR) << "Input binary file size error, required: " << tensor_data_size << " in fact: %zu" << size;
+    MS_LOG(ERROR) << "Input binary file size error, required: " << tensor_data_size << " in fact: " << size;
     return RET_ERROR;
   }
   auto input_data = inTensor->MutableData();
@@ -90,7 +90,7 @@ int TimeProfile::LoadInput() {
   } else {
     auto status = ReadInputFile();
     if (status != RET_OK) {
-      MS_LOG(ERROR) << "ReadInputFile error, " << status;
+      MS_LOG(ERROR) << "ReadInputFile error " << status;
       return RET_ERROR;
     }
   }
@@ -149,10 +149,10 @@ int TimeProfile::InitCallbackParameter() {
     uint64_t opEnd = GetTimeUs();
 
     if (after_inputs.empty()) {
-      MS_LOG(INFO) << "The num of beforeInputs is empty";
+      MS_LOG(INFO) << "The num of after inputs is empty";
     }
     if (after_outputs.empty()) {
-      MS_LOG(INFO) << "The num of beforeOutputs is empty";
+      MS_LOG(INFO) << "The num of after outputs is empty";
     }
 
     float cost = static_cast<float>(opEnd - op_begin_) / 1000.0f;
@@ -297,22 +297,34 @@ int TimeProfile::RunTimeProfile() {
   size_t size = 0;
   char *graphBuf = ReadFile(_flags->model_path_.c_str(), &size);
   if (graphBuf == nullptr) {
-    MS_LOG(ERROR) << "Load graph failed while running %s", modelName.c_str();
+    MS_LOG(ERROR) << "Load graph failed while running " << modelName.c_str();
+    delete graphBuf;
+    delete session_;
     return RET_ERROR;
   }
   auto model = lite::Model::Import(graphBuf, size);
-
+  delete graphBuf;
+  if (model == nullptr) {
+    MS_LOG(ERROR) << "Import model file failed while running " << modelName.c_str();
+    delete session_;
+    delete model;
+    return RET_ERROR;
+  }
   auto ret = session_->CompileGraph(model);
   if (ret != RET_OK) {
     MS_LOG(ERROR) << "Compile graph failed.";
+    delete session_;
+    delete model;
     return RET_ERROR;
   }
 
   // load input
   MS_LOG(INFO) << "start generate input data";
   auto status = LoadInput();
-  if (status != 0) {
+  if (status != RET_OK) {
     MS_LOG(ERROR) << "Generate input data error";
+    delete session_;
+    delete model;
     return status;
   }
 
@@ -324,6 +336,8 @@ int TimeProfile::RunTimeProfile() {
     ret = session_->RunGraph(before_call_back_, after_call_back_);
     if (ret != RET_OK) {
       MS_LOG(ERROR) << "Run graph failed.";
+      delete session_;
+      delete model;
       return RET_ERROR;
     }
     auto outputs = session_->GetOutputs();
@@ -345,14 +359,8 @@ int TimeProfile::RunTimeProfile() {
 
   printf("\n total time:     %5.5f ms,   kernel cost:   %5.5f ms \n\n", runCost, op_cost_total_ / _flags->loop_count_);
   printf("-------------------------------------------------------------------------\n");
-
-  for (auto &msInput : ms_inputs_) {
-    delete msInput;
-  }
-  ms_inputs_.clear();
-  delete graphBuf;
-  delete session_;
   delete model;
+  delete session_;
   return ret;
 }