Create Ort::Env once per application and reuse it for all sessions

Author: xaviliz

src/algorithms/machinelearning/onnxpredict.cpp

@@ -181,19 +181,14 @@ std::string OnnxPredict::getTensorInfos(const std::vector<TensorInfo>& infos, co
 }
 
 void OnnxPredict::reset() {
-  //if (!_isConfigured) return;
+
   input_names.clear();
   output_names.clear();
   _inputNodes.clear();
   _outputNodes.clear();
-  
-  // TODO: execute the reset() at the beginning in configure()
-  // TODO: include here the model and session creation
 
   try{
-    // Define environment
-    _env = Ort::Env(ORT_LOGGING_LEVEL_WARNING, "multi_io_inference"); // {"default", "test", "multi_io_inference"}
-    
+
     // Reset session
     _session.reset();
 

src/algorithms/machinelearning/onnxpredict.h

@@ -101,7 +101,7 @@ class OnnxPredict : public Algorithm {
 
  public:
 
-  OnnxPredict() : _env(Ort::Env(ORT_LOGGING_LEVEL_WARNING, "test")),
+  OnnxPredict() : _env(Ort::Env(ORT_LOGGING_LEVEL_WARNING, "multi_io_inference")),      // {"default", "test", "multi_io_inference"} - reuse it for all sessions
     _sessionOptions(Ort::SessionOptions()), _session(nullptr), _runOptions(NULL), _isConfigured(false){
     declareInput(_poolIn, "poolIn", "the pool where to get the feature tensors");
     declareOutput(_poolOut, "poolOut", "the pool where to store the output tensors");