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[tmva][sofie] Migrate SOFIE tutorials from Keras to PyTorch and ONNX #22792

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[tmva][sofie] Migrate SOFIE tutorials from Keras to PyTorch and ONNX #22792

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2 changes: 1 addition & 1 deletion tmva/sofie/README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -176,9 +176,9 @@ parser.CheckModel("example_model.ONNX");
- **Tutorials**
- [TMVA_SOFIE_Inference](https://github.com/root-project/root/blob/master/tutorials/machine_learning/TMVA_SOFIE_Inference.py)
- [TMVA_SOFIE_Keras](https://github.com/root-project/root/blob/master/tutorials/machine_learning/TMVA_SOFIE_Keras.C)
- [TMVA_SOFIE_Keras_HiggsModel](https://github.com/root-project/root/blob/master/tutorials/machine_learning/TMVA_SOFIE_Keras_HiggsModel.C)
- [TMVA_SOFIE_ONNX](https://github.com/root-project/root/blob/master/tutorials/machine_learning/TMVA_SOFIE_ONNX.C)
- [TMVA_SOFIE_PyTorch](https://github.com/root-project/root/blob/master/tutorials/machine_learning/TMVA_SOFIE_PyTorch.py)
- [TMVA_SOFIE_PyTorch_HiggsModel](https://github.com/root-project/root/blob/master/tutorials/machine_learning/TMVA_SOFIE_PyTorch_HiggsModel.py)
- [TMVA_SOFIE_RDataFrame](https://github.com/root-project/root/blob/master/tutorials/machine_learning/TMVA_SOFIE_RDataFrame.C)
- [TMVA_SOFIE_RDataFrame](https://github.com/root-project/root/blob/master/tutorials/machine_learning/TMVA_SOFIE_RDataFrame.py)
- [TMVA_SOFIE_RDataFrame_JIT](https://github.com/root-project/root/blob/master/tutorials/machine_learning/TMVA_SOFIE_RDataFrame_JIT.C)
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28 changes: 13 additions & 15 deletions tutorials/CMakeLists.txt
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Expand Up @@ -363,20 +363,20 @@ else()
# These SOFIE tutorials take models trained via PyMVA-PyKeras as input
if (NOT tmva-sofie OR NOT ROOT_KERAS_FOUND)
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_Keras.py)
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_Models.py)
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_Keras_HiggsModel.py)
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_RDataFrame.C)
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_RDataFrame_JIT.C)
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_RSofieReader.C)
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_RDataFrame.py)
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_RSofieReader.C)
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_Inference.py)
endif()
if (NOT tmva-sofie OR NOT ROOT_TORCH_FOUND)
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_PyTorch.py)
endif()
# These SOFIE tutorials take the ONNX HiggsModel trained with PyTorch as input
if (NOT tmva-sofie OR NOT ROOT_TORCH_FOUND OR NOT ROOT_ONNX_FOUND)
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_ONNX.py)
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_Models.py)
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_PyTorch_HiggsModel.py)
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_RDataFrame.C)
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_RDataFrame_JIT.C)
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_RSofieReader.C)
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_RDataFrame.py)
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_Inference.py)
endif()
#veto this tutorial since it is added directly
list(APPEND tmva_veto machine_learning/TMVA_SOFIE_GNN_Parser.py)
Expand Down Expand Up @@ -641,7 +641,7 @@ set (machine_learning-tmva004_RStandardScaler-depends tutorial-machine_learning-
set (machine_learning-pytorch-ApplicationClassificationPyTorch-depends tutorial-machine_learning-pytorch-ClassificationPyTorch-py)
set (machine_learning-pytorch-RegressionPyTorch-depends tutorial-machine_learning-pytorch-ApplicationClassificationPyTorch-py)
set (machine_learning-pytorch-ApplicationRegressionPyTorch-depends tutorial-machine_learning-pytorch-RegressionPyTorch-py)
set (machine_learning-TMVA_SOFIE_RDataFrame-depends tutorial-machine_learning-TMVA_SOFIE_Keras_HiggsModel-py)
set (machine_learning-TMVA_SOFIE_RDataFrame-depends tutorial-machine_learning-TMVA_SOFIE_PyTorch_HiggsModel-py)
set (machine_learning-TMVA_SOFIE_RDataFrame_JIT-depends tutorial-machine_learning-TMVA_SOFIE_RDataFrame)
set (machine_learning-TMVA_SOFIE_RSofieReader-depends tutorial-machine_learning-TMVA_SOFIE_RDataFrame_JIT)
set (machine_learning-TMVA_SOFIE_Inference-depends tutorial-machine_learning-TMVA_SOFIE_RSofieReader)
Expand Down Expand Up @@ -834,8 +834,8 @@ if(pyroot)
list(APPEND pyveto ${tmva_veto_py})
endif()

if (ROOT_KERAS_FOUND)
set (machine_learning-TMVA_SOFIE_RDataFrame-py-depends tutorial-machine_learning-TMVA_SOFIE_Keras_HiggsModel)
if (ROOT_TORCH_FOUND AND ROOT_ONNX_FOUND)
set (machine_learning-TMVA_SOFIE_RDataFrame-py-depends tutorial-machine_learning-TMVA_SOFIE_PyTorch_HiggsModel)
endif()

if(NOT tmva-pymva)
Expand Down Expand Up @@ -933,25 +933,23 @@ if(pyroot)
roofit/roofit/rf409_NumPyPandasToRooFit.py)

file(GLOB requires_keras RELATIVE ${CMAKE_CURRENT_SOURCE_DIR}
machine_learning/TMVA_SOFIE_Inference.py
machine_learning/TMVA_SOFIE_Models.py
machine_learning/TMVA_SOFIE_RDataFrame.py
machine_learning/keras/*.py
)
file(GLOB requires_torch RELATIVE ${CMAKE_CURRENT_SOURCE_DIR}
machine_learning/pytorch/*.py
machine_learning/ml_dataloader_PyTorch.py
machine_learning/ml_dataloader_resampling.py
machine_learning/ml_dataloader_Higgs_Classification.py
machine_learning/TMVA_SOFIE_Models.py
machine_learning/TMVA_SOFIE_PyTorch.py
machine_learning/TMVA_SOFIE_PyTorch_HiggsModel.py
)
file(GLOB requires_xgboost RELATIVE ${CMAKE_CURRENT_SOURCE_DIR}
machine_learning/tmva101_Training.py
machine_learning/tmva102_Testing.py # requires tmva101_Training.py
roofit/roofit/rf618_mixture_models.py
)
file(GLOB requires_sklearn RELATIVE ${CMAKE_CURRENT_SOURCE_DIR}
machine_learning/TMVA_SOFIE_Models.py
machine_learning/tmva101_Training.py # uses the xgboost sklearn plugin
machine_learning/tmva102_Testing.py # requires tmva101_Training.py
roofit/roofit/rf617_simulation_based_inference_multidimensional.py
Expand Down
26 changes: 11 additions & 15 deletions tutorials/machine_learning/TMVA_SOFIE_Inference.py
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@@ -1,10 +1,10 @@
### \file
### \ingroup tutorial_ml
### \notebook -nodraw
### This macro provides an example of using a trained model with Keras
### This macro provides an example of using a trained model with PyTorch
### and make inference using SOFIE directly from Numpy
### This macro uses as input a Keras model generated with the
### TMVA_Higgs_Classification.C tutorial
### This macro uses as input an ONNX model generated with the
### TMVA_SOFIE_PyTorch_HiggsModel.py tutorial
### You need to run that macro before this one.
### In this case we are parsing the input file and then run the inference in the same
### macro making use of the ROOT JITing capability
Expand All @@ -20,32 +20,28 @@
import ROOT

# check if the input file exists
modelFile = "HiggsModel.keras"
modelFile = "HiggsModel.onnx"

if not exists(modelFile):
raise FileNotFoundError("You need to run TMVA_Higgs_Classification.C to generate the Keras trained model")
raise FileNotFoundError("You need to run TMVA_SOFIE_PyTorch_HiggsModel.py to generate the ONNX trained model")


# parse the input Keras model into RModel object
model = ROOT.TMVA.Experimental.SOFIE.PyKeras.Parse(modelFile)
# parse the input ONNX model into RModel object
parser = ROOT.TMVA.Experimental.SOFIE.RModelParser_ONNX()
model = parser.Parse(modelFile)

generatedHeaderFile = modelFile.replace(".keras",".hxx")
print("Generating inference code for the Keras model from ",modelFile,"in the header ", generatedHeaderFile)
generatedHeaderFile = modelFile.replace(".onnx", ".hxx")
print("Generating inference code for the ONNX model from ", modelFile, "in the header ", generatedHeaderFile)
#Generating inference code
model.Generate()
model.OutputGenerated(generatedHeaderFile)
model.PrintGenerated()

# now compile using ROOT JIT trained model
modelName = modelFile.replace(".keras","")
modelName = modelFile.replace(".onnx", "")
print("compiling SOFIE model ", modelName)
ROOT.gInterpreter.Declare('#include "' + generatedHeaderFile + '"')


generatedHeaderFile = modelFile.replace(".keras",".hxx")
print("Generating inference code for the Keras model from ",modelFile,"in the header ", generatedHeaderFile)
#Generating inference

inputFileName = "Higgs_data.root"
inputFile = str(ROOT.gROOT.GetTutorialDir()) + "/machine_learning/data/" + inputFileName

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164 changes: 0 additions & 164 deletions tutorials/machine_learning/TMVA_SOFIE_Keras_HiggsModel.py
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