[tmva][sofie] Don't call PyMVA init functions in SOFIE tutorials

There is no need for that, and they are not available if ROOT was built
with `tmva-pymva=OFF`.

Author: guitargeek

tutorials/machine_learning/TMVA_SOFIE_Inference.py

@@ -18,9 +18,6 @@
 import numpy as np
 
 
-ROOT.TMVA.PyMethodBase.PyInitialize()
-
-
 # check if the input file exists
 modelFile = "Higgs_trained_model.h5"
 if (ROOT.gSystem.AccessPathName(modelFile)) :

tutorials/machine_learning/TMVA_SOFIE_Keras.C

@@ -40,13 +40,12 @@ model.save('KerasModel.h5')\n";
 void TMVA_SOFIE_Keras(const char * modelFile = nullptr, bool printModelInfo = true){
 
     //Running the Python script to generate Keras .h5 file
-    TMVA::PyMethodBase::PyInitialize();
 
     if (modelFile == nullptr) {
         TMacro m;
         m.AddLine(pythonSrc);
         m.SaveSource("make_keras_model.py");
-        gSystem->Exec(TMVA::Python_Executable() + " make_keras_model.py");
+        gSystem->Exec("python3 make_keras_model.py");
         modelFile = "KerasModel.h5";
     }
 

tutorials/machine_learning/TMVA_SOFIE_Models.py

@@ -16,8 +16,6 @@
 import ROOT
 from os.path import exists
 
-ROOT.TMVA.PyMethodBase.PyInitialize()
-
 
 ## generate and train Keras models with different architectures
 

tutorials/machine_learning/TMVA_SOFIE_PyTorch.C

@@ -42,12 +42,11 @@ torch.jit.save(m,'PyTorchModel.pt')\n";
 void TMVA_SOFIE_PyTorch(){
 
     //Running the Python script to generate PyTorch .pt file
-    TMVA::PyMethodBase::PyInitialize();
 
     TMacro m;
     m.AddLine(pythonSrc);
     m.SaveSource("make_pytorch_model.py");
-    gSystem->Exec(TMVA::Python_Executable() + " make_pytorch_model.py");
+    gSystem->Exec("python3 make_pytorch_model.py");
 
     //Parsing a PyTorch model requires the shape and data-type of input tensor
     //Data-type of input tensor defaults to Float if not specified

tutorials/machine_learning/TMVA_SOFIE_RDataFrame.py

@@ -13,8 +13,6 @@
 import ROOT
 from os.path import exists
 
-ROOT.TMVA.PyMethodBase.PyInitialize()
-
 
 # check if the input file exists
 modelFile = "Higgs_trained_model.h5"

tutorials/machine_learning/TMVA_SOFIE_RDataFrame_JIT.C

@@ -40,8 +40,6 @@ void CompileModelForRDF(const std::string & headerModelFile, unsigned int ninput
 
 void TMVA_SOFIE_RDataFrame_JIT(std::string modelFile = "Higgs_trained_model.h5"){
 
-    TMVA::PyMethodBase::PyInitialize();
-
     // check if the input file exists
     if (gSystem->AccessPathName(modelFile.c_str())) {
         Info("TMVA_SOFIE_RDataFrame","You need to run TMVA_Higgs_Classification.C to generate the Keras trained model");