tutorials/ml: fix TMVA_SOFIE_ONNX tensor name for current PyTorch#21546
tutorials/ml: fix TMVA_SOFIE_ONNX tensor name for current PyTorch#21546Neeraj-x0 wants to merge 1 commit intoroot-project:masterfrom
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Pull request overview
This PR updates the TMVA SOFIE ONNX tutorial and its companion test artifact to align with tensor naming produced by current PyTorch/ONNX exports (e.g., 0.weight → 0weight after SOFIE name cleaning), fixing a runtime crash when querying tensor shapes/types.
Changes:
- Updated the tutorial macro to query
0weightinstead of the obsolete16weight. - Updated tutorial print statements to match the new tensor name.
- Regenerated
tmva/sofie/test/input_models/Linear_16.onnxusing a current PyTorch export.
Reviewed changes
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| File | Description |
|---|---|
| tutorials/machine_learning/TMVA_SOFIE_ONNX.C | Updates the hardcoded tensor queried by the tutorial to match current PyTorch naming. |
| tmva/sofie/test/input_models/Linear_16.onnx | Updates the test ONNX model artifact to match current PyTorch export output. |
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| //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\": "; | ||
| std::cout<<"\n\nTensor \"0weight\" already exist: "<<std::boolalpha<<model.CheckIfTensorAlreadyExist("0weight")<<"\n\n"; | ||
| std::vector<size_t> tensorShape = model.GetTensorShape("0weight"); | ||
| std::cout<<"Shape of tensor \"0weight\": "; | ||
| for(auto& it:tensorShape){ | ||
| std::cout<<it<<","; | ||
| } | ||
| std::cout<<"\n\nData type of tensor \"16weight\": "; | ||
| SOFIE::ETensorType tensorType = model.GetTensorType("16weight"); | ||
| std::cout<<"\n\nData type of tensor \"0weight\": "; | ||
| SOFIE::ETensorType tensorType = model.GetTensorType("0weight"); |
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CheckIfTensorAlreadyExist("0weight") is only printed, but GetTensorShape("0weight")/GetTensorType("0weight") are called unconditionally. If a user passes a different ONNX file (via inputFile) that doesn’t contain this tensor, the tutorial will still throw a runtime_error and abort. Consider branching on the boolean result and either skipping the shape/type queries or emitting a clearer message / early return when the tensor is absent.
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Fixed in the latest commit ,the shape/type queries are now guarded
by the boolean result of CheckIfTensorAlreadyExist(). If the tensor is absent
(e.g. when a custom ONNX file is passed), the tutorial now prints a clear message
and skips the queries instead of throwing a runtime_error.
The tutorial hardcoded tensor name '16weight' which was generated by
an older PyTorch version. Current PyTorch Sequential modules produce
tensors named '0weight', '2weight', '4weight' (dot stripped by SOFIE).
Updated TMVA_SOFIE_ONNX.C to use '0weight' and regenerated Linear_16.onnx
using current PyTorch to keep tutorial and test model in sync.
Fixes: tutorial crash with runtime_error on GetTensorShape('16weight')
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The tutorial hardcoded tensor name '16weight' which was generated by an older
PyTorch version. Current PyTorch Sequential modules produce tensors named
'0weight', '2weight', '4weight' (dot stripped by SOFIE).
Updated TMVA_SOFIE_ONNX.C to use '0weight' and regenerated Linear_16.onnx
using current PyTorch to keep tutorial and test model in sync.
Fixes: tutorial crash with runtime_error on GetTensorShape('16weight')
This Pull request:
Changes or fixes:
16weightwith0weightin TMVA_SOFIE_ONNX.CChecklist:
This PR fixes #21545