Adjusting eval sizes. Makes code neater and avoids some calculations

Author: ChSonnabend

Common/ML/src/OrtInterface.cxx

@@ -226,19 +226,18 @@ template std::vector<OrtDataType::Float16_t> OrtModel::inference<OrtDataType::Fl
 template <class I, class O>
 void OrtModel::inference(I* input, size_t input_size, O* output)
 {
-  std::vector<int64_t> inputShape{(int64_t)(input_size / mInputShapes[0][1]), (int64_t)mInputShapes[0][1]};
+  std::vector<int64_t> inputShape{input_size, (int64_t)mInputShapes[0][1]};
   Ort::Value inputTensor = Ort::Value(nullptr);
   if constexpr (std::is_same_v<I, OrtDataType::Float16_t>) {
-    inputTensor = Ort::Value::CreateTensor<Ort::Float16_t>(pImplOrt->memoryInfo, reinterpret_cast<Ort::Float16_t*>(input), input_size, inputShape.data(), inputShape.size());
+    inputTensor = Ort::Value::CreateTensor<Ort::Float16_t>(pImplOrt->memoryInfo, reinterpret_cast<Ort::Float16_t*>(input), input_size * mInputShapes[0][1], inputShape.data(), inputShape.size());
   } else {
-    inputTensor = Ort::Value::CreateTensor<I>(pImplOrt->memoryInfo, input, input_size, inputShape.data(), inputShape.size());
+    inputTensor = Ort::Value::CreateTensor<I>(pImplOrt->memoryInfo, input, input_size * mInputShapes[0][1], inputShape.data(), inputShape.size());
   }
 
-  std::vector<int64_t> outputShape{inputShape[0], mOutputShapes[0][1]};
-  size_t outputSize = (int64_t)(input_size * mOutputShapes[0][1] / mInputShapes[0][1]);
-  Ort::Value outputTensor = Ort::Value::CreateTensor<O>(pImplOrt->memoryInfo, output, outputSize, outputShape.data(), outputShape.size());
+  std::vector<int64_t> outputShape{input_size, mOutputShapes[0][1]};
+  Ort::Value outputTensor = Ort::Value::CreateTensor<O>(pImplOrt->memoryInfo, output, input_size * mOutputShapes[0][1], outputShape.data(), outputShape.size());
 
-  (pImplOrt->session)->Run(pImplOrt->runOptions, inputNamesChar.data(), &inputTensor, 1, outputNamesChar.data(), &outputTensor, outputNamesChar.size()); // TODO: Not sure if 1 is correct here
+  (pImplOrt->session)->Run(pImplOrt->runOptions, inputNamesChar.data(), &inputTensor, 1, outputNamesChar.data(), &outputTensor, outputNamesChar.size()); // TODO: Not sure if 1 is always correct here
 }
 
 template void OrtModel::inference<OrtDataType::Float16_t, float>(OrtDataType::Float16_t*, size_t, float*);

GPU/GPUTracking/TPCClusterFinder/GPUTPCNNClusterizerHost.cxx

@@ -57,11 +57,11 @@ GPUTPCNNClusterizerHost::GPUTPCNNClusterizerHost(const GPUSettingsProcessingNNcl
   }
 }
 
-void GPUTPCNNClusterizerHost::networkInference(o2::ml::OrtModel model, GPUTPCNNClusterizer& clusterer, size_t size, float* output, int32_t dtype)
+void GPUTPCNNClusterizerHost::networkInference(o2::ml::OrtModel model, GPUTPCNNClusterizer& clustererNN, size_t size, float* output, int32_t dtype)
 {
   if (dtype == 0) {
-    model.inference<OrtDataType::Float16_t, float>(clusterer.inputData16, size * clusterer.nnClusterizerElementSize, output);
+    model.inference<OrtDataType::Float16_t, float>(clustererNN.inputData16, size, output);
   } else {
-    model.inference<float, float>(clusterer.inputData32, size * clusterer.nnClusterizerElementSize, output);
+    model.inference<float, float>(clustererNN.inputData32, size, output);
   }
 }