Upgrade to onnxruntime 1.13.1

src/cpp/model.hpp

@@ -12,8 +12,6 @@ const string instanceName{"larynx"};
 
 struct ModelSession {
   Ort::Session onnx;
-  vector<char *> inputNames;
-  vector<char *> outputNames;
   Ort::AllocatorWithDefaultOptions allocator;
   Ort::SessionOptions options;
   Ort::Env env;
@@ -48,19 +46,6 @@ void loadModel(string modelPath, ModelSession &session) {
   session.onnx = Ort::Session(session.env, modelPath.c_str(), session.options);
   auto endTime = chrono::steady_clock::now();
   auto loadDuration = chrono::duration<double>(endTime - startTime);
-
-  size_t numInputNodes = session.onnx.GetInputCount();
-  size_t numOutputNodes = session.onnx.GetOutputCount();
-
-  for (size_t i = 0; i < numInputNodes; i++) {
-    session.inputNames.push_back(
-        session.onnx.GetInputName(i, session.allocator));
-  }
-
-  for (size_t i = 0; i < numOutputNodes; i++) {
-    session.outputNames.push_back(
-        session.onnx.GetOutputName(i, session.allocator));
-  }
 }
 
 } // namespace larynx

src/cpp/synthesize.hpp

@@ -1,6 +1,7 @@
 #ifndef SYNTHESIZE_H_
 #define SYNTHESIZE_H_
 
+#include <array>
 #include <chrono>
 #include <limits>
 #include <memory>
@@ -64,12 +65,16 @@ void synthesize(SynthesisConfig &synthesisConfig, ModelSession &session,
         speakerIdShape.size()));
   }
 
+  // From export_onnx.py
+  array<const char *, 4> inputNames = {"input", "input_lengths", "scales",
+                                       "sid"};
+  array<const char *, 1> outputNames = {"output"};
+
   // Infer
   auto startTime = chrono::steady_clock::now();
-  auto outputTensors =
-      session.onnx.Run(Ort::RunOptions{nullptr}, session.inputNames.data(),
-                       inputTensors.data(), inputTensors.size(),
-                       session.outputNames.data(), session.outputNames.size());
+  auto outputTensors = session.onnx.Run(
+      Ort::RunOptions{nullptr}, inputNames.data(), inputTensors.data(),
+      inputTensors.size(), outputNames.data(), outputNames.size());
   auto endTime = chrono::steady_clock::now();
 
   if ((outputTensors.size() != 1) || (!outputTensors.front().IsTensor())) {