!4434 fix bug that lite_session GetInputs return repeated input tensor

Merge pull request !4434 from hangq/master

mindspore/lite/src/lite_session.cc

@@ -92,6 +92,16 @@ void LiteSession::InitGraphInputTensors(const lite::Model *model) {
   }
 }
 
+void LiteSession::InitGraphInputMSTensors(const lite::Model *model) {
+  auto meta_graph = model->GetMetaGraph();
+  MS_ASSERT(this->input_vec_.empty());
+  MS_ASSERT(meta_graph != nullptr);
+  for (auto &input_tensor : this->inputs_) {
+    MS_ASSERT(input_tensor != nullptr);
+    this->input_vec_.emplace_back(new lite::tensor::LiteTensor(input_tensor));
+  }
+}
+
 void LiteSession::InitGraphOutputTensors(const lite::Model *model) {
   auto meta_graph = model->GetMetaGraph();
   MS_ASSERT(this->outputs_.empty());
@@ -169,6 +179,7 @@ void LiteSession::InitGraphOutputMap(const lite::Model *model) {
 
 void LiteSession::InitGraphInOutTensors(const lite::Model *model) {
   InitGraphInputTensors(model);
+  InitGraphInputMSTensors(model);
   InitGraphOutputTensors(model);
   InitGraphInputMap(model);
   InitGraphOutputMap(model);
@@ -201,16 +212,7 @@ int LiteSession::CompileGraph(Model *model) {
 }
 
 std::vector<mindspore::tensor::MSTensor *> LiteSession::GetInputs() const {
-  std::vector<mindspore::tensor::MSTensor *> ret;
-  for (auto &iter : this->input_map_) {
-    auto &node_input_tensors = iter.second;
-    for (auto tensor : node_input_tensors) {
-      if (!IsContain(ret, tensor)) {
-        ret.emplace_back(tensor);
-      }
-    }
-  }
-  return ret;
+  return this->input_vec_;
 }
 
 int LiteSession::RunGraph(const session::KernelCallBack &before, const session::KernelCallBack &after) {

mindspore/lite/src/lite_session.h

@@ -57,13 +57,15 @@ class LiteSession : public session::LiteSession {
   int ConvertTensors(const lite::Model *model);
 
   void InitGraphInOutTensors(const lite::Model *model);
-
+  // init this->inputs_
   void InitGraphInputTensors(const lite::Model *model);
-
+  // init this->input_vec_
+  void InitGraphInputMSTensors(const lite::Model *model);
+  // init this->outputs_
   void InitGraphOutputTensors(const lite::Model *model);
-
+  // init this->input_map_
   void InitGraphInputMap(const lite::Model *model);
-
+  // init this->output_map_
   void InitGraphOutputMap(const lite::Model *model);
 
  protected:
@@ -74,6 +76,8 @@ class LiteSession : public session::LiteSession {
   std::vector<tensor::Tensor *> inputs_;
   // graph output tensors
   std::vector<tensor::Tensor *> outputs_;
+  // graph input MSTensors
+  std::vector<mindspore::tensor::MSTensor *> input_vec_;
   // graph input node name -- input tensors
   std::unordered_map<std::string, std::vector<mindspore::tensor::MSTensor *>> input_map_;
   // graph output node name -- output tensors

mindspore/lite/tools/benchmark/benchmark.cc

@@ -49,7 +49,8 @@ int Benchmark::GenerateInputData() {
     auto tensorByteSize = tensor->Size();
     auto status = GenerateRandomData(tensorByteSize, inputData);
     if (status != 0) {
-      MS_LOG(ERROR) << "GenerateRandomData for inTensor failed %d" << status;
+      std::cerr << "GenerateRandomData for inTensor failed: " << status << std::endl;
+      MS_LOG(ERROR) << "GenerateRandomData for inTensor failed:" << status;
       return status;
     }
   }
@@ -60,12 +61,14 @@ int Benchmark::LoadInput() {
   if (_flags->inDataPath.empty()) {
     auto status = GenerateInputData();
     if (status != 0) {
+      std::cerr << "Generate input data error " << status << std::endl;
       MS_LOG(ERROR) << "Generate input data error " << status;
       return status;
     }
   } else {
     auto status = ReadInputFile();
     if (status != 0) {
+      std::cerr << "ReadInputFile error, " << status << std::endl;
       MS_LOG(ERROR) << "ReadInputFile error, " << status;
       return status;
     }
@@ -97,6 +100,7 @@ int Benchmark::ReadInputFile() {
       char *binBuf = ReadFile(_flags->input_data_list[i].c_str(), &size);
       auto tensorDataSize = cur_tensor->Size();
       if (size != tensorDataSize) {
+        std::cerr << "Input binary file size error, required: %zu, in fact: %zu" << tensorDataSize << size << std::endl;
         MS_LOG(ERROR) << "Input binary file size error, required: %zu, in fact: %zu" << tensorDataSize << size;
         return RET_ERROR;
       }
@@ -113,11 +117,13 @@ int Benchmark::ReadCalibData() {
   // read calib data
   std::ifstream inFile(calibDataPath);
   if (!inFile.good()) {
+    std::cerr << "file: " << calibDataPath << " is not exist" << std::endl;
     MS_LOG(ERROR) << "file: " << calibDataPath << " is not exist";
     return RET_ERROR;
   }
 
   if (!inFile.is_open()) {
+    std::cerr << "file: " << calibDataPath << " open failed" << std::endl;
     MS_LOG(ERROR) << "file: " << calibDataPath << " open failed";
     inFile.close();
     return RET_ERROR;
@@ -181,6 +187,7 @@ float Benchmark::CompareData(const std::string &nodeName, std::vector<int> msSha
         oss << dim << ",";
       }
       oss << ") are different";
+      std::cerr << oss.str() << std::endl;
       MS_LOG(ERROR) << "%s", oss.str().c_str();
       return RET_ERROR;
     }
@@ -193,6 +200,7 @@ float Benchmark::CompareData(const std::string &nodeName, std::vector<int> msSha
       }
 
       if (std::isnan(msTensorData[j]) || std::isinf(msTensorData[j])) {
+        std::cerr << "Output tensor has nan or inf data, compare fail" << std::endl;
         MS_LOG(ERROR) << "Output tensor has nan or inf data, compare fail";
         return RET_ERROR;
       }
@@ -524,6 +532,13 @@ int Benchmark::Init() {
   return RET_OK;
 }
 
+Benchmark::~Benchmark() {
+  for (auto iter : this->calibData) {
+    delete (iter.second);
+  }
+  this->calibData.clear();
+}
+
 int RunBenchmark(int argc, const char **argv) {
   BenchmarkFlags flags;
   Option<std::string> err = flags.ParseFlags(argc, argv);

mindspore/lite/tools/benchmark/benchmark.h

@@ -104,7 +104,7 @@ class MS_API Benchmark {
  public:
   explicit Benchmark(BenchmarkFlags *flags) : _flags(flags) {}
 
-  virtual ~Benchmark() = default;
+  virtual ~Benchmark();
 
   int Init();
   int RunBenchmark(const std::string &deviceType = "NPU");