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tutorials/ml: fix TMVA_SOFIE_ONNX tensor name for current PyTorch #21546

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tutorials/ml: fix TMVA_SOFIE_ONNX tensor name for current PyTorch #21546

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Binary file modified tmva/sofie/test/input_models/Linear_16.onnx
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33 changes: 15 additions & 18 deletions tutorials/machine_learning/TMVA_SOFIE_ONNX.C
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Original file line number Diff line number Diff line change
Expand Up @@ -7,44 +7,41 @@
/// \macro_code
/// \macro_output
/// \author Sanjiban Sengupta

using namespace TMVA::Experimental;

void TMVA_SOFIE_ONNX(std::string inputFile = ""){
if (inputFile.empty() )
inputFile = std::string(gROOT->GetTutorialsDir()) + "/machine_learning/Linear_16.onnx";

//Creating parser object to parse ONNX files
SOFIE::RModelParser_ONNX parser;
SOFIE::RModel model = parser.Parse(inputFile, true);

//Generating inference code
model.Generate();
// write the code in a file (by default Linear_16.hxx and Linear_16.dat
// write the code in a file (by default Linear_16.hxx and Linear_16.dat)
model.OutputGenerated();

//Printing required input tensors
model.PrintRequiredInputTensors();

//Printing initialized tensors (weights)
std::cout<<"\n\n";
model.PrintInitializedTensors();

//Printing intermediate tensors
std::cout<<"\n\n";
model.PrintIntermediateTensors();

//Checking if tensor already exist in model
std::cout<<"\n\nTensor \"16weight\" already exist: "<<std::boolalpha<<model.CheckIfTensorAlreadyExist("16weight")<<"\n\n";
std::vector<size_t> tensorShape = model.GetTensorShape("16weight");
std::cout<<"Shape of tensor \"16weight\": ";
for(auto& it:tensorShape){
std::cout<<it<<",";
const std::string tensorName = "0weight";
bool tensorExists = model.CheckIfTensorAlreadyExist(tensorName);
std::cout<<"\n\nTensor \""<<tensorName<<"\" already exist: "<<std::boolalpha<<tensorExists<<"\n\n";
if (tensorExists) {
std::vector<size_t> tensorShape = model.GetTensorShape(tensorName);
std::cout<<"Shape of tensor \""<<tensorName<<"\": ";
for(auto& it:tensorShape){
std::cout<<it<<",";
}
std::cout<<"\n\nData type of tensor \""<<tensorName<<"\": ";
SOFIE::ETensorType tensorType = model.GetTensorType(tensorName);
std::cout<<SOFIE::ConvertTypeToString(tensorType);
} else {
std::cout<<"Tensor \""<<tensorName<<"\" not found in model. Skipping shape/type queries.\n";
}
std::cout<<"\n\nData type of tensor \"16weight\": ";
SOFIE::ETensorType tensorType = model.GetTensorType("16weight");
std::cout<<SOFIE::ConvertTypeToString(tensorType);

//Printing generated inference code
std::cout<<"\n\n";
model.PrintGenerated();
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