Update to 6.24.04
New subpackages: root-roofit-common, root-roofit-dataframe-helpers, root-roofit-hs3, root-tmva-sofie and root-tmva-sofie-parser Removed subpackages: root-memstat and root-montecarlo-vmc Drop the doxygen generated root-doc package (doxygen runs out of memory) Dropped patches: 17 New patches: 22 Updated patches: 5
This commit is contained in:
Mattias Ellert
parent
65aa8a7075
commit
2f8e3d96d1
47 changed files with 2698 additions and 1782 deletions
177
root-fix-TMVA-tutorial-using-internally-python.patch
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177
root-fix-TMVA-tutorial-using-internally-python.patch
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@ -0,0 +1,177 @@
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From db974bbe72b97c798b7db52d2481aa24c2ce2b76 Mon Sep 17 00:00:00 2001
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From: moneta <lorenzo.moneta@cern.ch>
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Date: Thu, 17 Mar 2022 16:28:42 +0100
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Subject: [PATCH] Fix TMVA tutorial using internally pyton for MacOS 12.3
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With the new MacOS update python (and python2) is not existing anymore, only python3.
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Add then a new function TMVA::Python_executable() using ROOT config to determine if ROOT is using python version 2 or 3. In case of 3 returns as executable "python3".
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Fix also the correct location of the input ONNX file for TMVA_SOFIE_ONNX.C (copying the file at configure time)
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---
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tmva/pymva/inc/TMVA/PyMethodBase.h | 6 ++++++
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tmva/pymva/src/PyMethodBase.cxx | 20 ++++++++++++++++++++
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tutorials/CMakeLists.txt | 5 ++++-
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tutorials/tmva/TMVA_CNN_Classification.C | 5 +++--
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tutorials/tmva/TMVA_RNN_Classification.C | 2 +-
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tutorials/tmva/TMVA_SOFIE_Keras.C | 2 +-
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tutorials/tmva/TMVA_SOFIE_ONNX.C | 2 +-
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tutorials/tmva/TMVA_SOFIE_PyTorch.C | 2 +-
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8 files changed, 37 insertions(+), 7 deletions(-)
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diff --git a/tmva/pymva/inc/TMVA/PyMethodBase.h b/tmva/pymva/inc/TMVA/PyMethodBase.h
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index 31a5caada9..a213c3fbad 100644
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--- a/tmva/pymva/inc/TMVA/PyMethodBase.h
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+++ b/tmva/pymva/inc/TMVA/PyMethodBase.h
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@@ -53,6 +53,12 @@ namespace TMVA {
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class MethodBoost;
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class DataSetInfo;
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+ /// Function to find current Python executable
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+ /// used by ROOT
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+ /// If Python2 is installed return "python"
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+ /// Instead if "Python3" return "python3"
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+ TString Python_Executable();
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+
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class PyMethodBase : public MethodBase {
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friend class Factory;
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diff --git a/tmva/pymva/src/PyMethodBase.cxx b/tmva/pymva/src/PyMethodBase.cxx
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index 86f979e006..26b0f31135 100644
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--- a/tmva/pymva/src/PyMethodBase.cxx
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+++ b/tmva/pymva/src/PyMethodBase.cxx
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@@ -19,6 +19,9 @@
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#include "TMVA/MsgLogger.h"
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#include "TMVA/Results.h"
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#include "TMVA/Timer.h"
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+#include "TMVA/Tools.h"
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+
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+#include "TSystem.h"
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#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
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#include <numpy/arrayobject.h>
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@@ -37,6 +40,23 @@ public:
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~PyGILRAII() { PyGILState_Release(m_GILState); }
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};
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} // namespace Internal
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+
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+/// get current Python executable used by ROOT
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+TString Python_Executable() {
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+ TString python_version = gSystem->GetFromPipe("root-config --python-version");
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+ if (python_version.IsNull()) {
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+ TMVA::gTools().Log() << kFATAL << "Can't find a valid Python version used to build ROOT" << Endl;
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+ return nullptr;
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+ }
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+ if(python_version[0] == '2')
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+ return "python";
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+ else if (python_version[0] == '3')
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+ return "python3";
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+
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+ TMVA::gTools().Log() << kFATAL << "Invalid Python version used to build ROOT : " << python_version << Endl;
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+ return nullptr;
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+}
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+
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} // namespace TMVA
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ClassImp(PyMethodBase);
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diff --git a/tutorials/CMakeLists.txt b/tutorials/CMakeLists.txt
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index de77aaa787..f1f1abda71 100644
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--- a/tutorials/CMakeLists.txt
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+++ b/tutorials/CMakeLists.txt
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@@ -281,8 +281,11 @@ else()
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endif()
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if (NOT tmva-sofie)
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list(APPEND tmva_veto tmva/TMVA_SOFIE_ONNX.C)
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+ else()
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+ #copy ONNX file needed for the tutorial
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+ configure_file(${CMAKE_SOURCE_DIR}/tmva/sofie/test/input_models/Linear_16.onnx ${CMAKE_BINARY_DIR}/tutorials/tmva/Linear_16.onnx COPYONLY)
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endif()
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-
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+
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endif()
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if (NOT ROOT_pythia6_FOUND)
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diff --git a/tutorials/tmva/TMVA_CNN_Classification.C b/tutorials/tmva/TMVA_CNN_Classification.C
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index fa03562a8f..31172bb729 100644
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--- a/tutorials/tmva/TMVA_CNN_Classification.C
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+++ b/tutorials/tmva/TMVA_CNN_Classification.C
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@@ -145,6 +145,7 @@ void TMVA_CNN_Classification(std::vector<bool> opt = {1, 1, 1, 1, 1})
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TMVA::PyMethodBase::PyInitialize();
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#else
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useKerasCNN = false;
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+ usePyTorchCNN = false;
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#endif
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TFile *outputFile = nullptr;
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@@ -445,7 +446,7 @@ void TMVA_CNN_Classification(std::vector<bool> opt = {1, 1, 1, 1, 1})
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m.SaveSource("make_cnn_model.py");
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// execute
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- gSystem->Exec("python make_cnn_model.py");
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+ gSystem->Exec(TMVA::Python_Executable() + " make_cnn_model.py");
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if (gSystem->AccessPathName("model_cnn.h5")) {
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Warning("TMVA_CNN_Classification", "Error creating Keras model file - skip using Keras");
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@@ -465,7 +466,7 @@ void TMVA_CNN_Classification(std::vector<bool> opt = {1, 1, 1, 1, 1})
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Info("TMVA_CNN_Classification", "Using Convolutional PyTorch Model");
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TString pyTorchFileName = gROOT->GetTutorialDir() + TString("/tmva/PyTorch_Generate_CNN_Model.py");
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// check that pytorch can be imported and file defining the model and used later when booking the method is existing
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- if (gSystem->Exec("python -c 'import torch'") || gSystem->AccessPathName(pyTorchFileName) ) {
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+ if (gSystem->Exec(TMVA::Python_Executable() + " -c 'import torch'") || gSystem->AccessPathName(pyTorchFileName) ) {
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Warning("TMVA_CNN_Classification", "PyTorch is not installed or model building file is not existing - skip using PyTorch");
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}
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else {
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diff --git a/tutorials/tmva/TMVA_RNN_Classification.C b/tutorials/tmva/TMVA_RNN_Classification.C
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index eb26d03a2f..b49e4d91c4 100644
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--- a/tutorials/tmva/TMVA_RNN_Classification.C
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+++ b/tutorials/tmva/TMVA_RNN_Classification.C
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@@ -431,7 +431,7 @@ the option string
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m.SaveSource("make_rnn_model.py");
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// execute
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- gSystem->Exec("python make_rnn_model.py");
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+ gSystem->Exec(TMVA::Python_Executable() + " make_rnn_model.py");
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if (gSystem->AccessPathName(modelName)) {
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Warning("TMVA_RNN_Classification", "Error creating Keras recurrent model file - Skip using Keras");
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diff --git a/tutorials/tmva/TMVA_SOFIE_Keras.C b/tutorials/tmva/TMVA_SOFIE_Keras.C
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index e9fdbba21a..a87269f7f4 100644
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--- a/tutorials/tmva/TMVA_SOFIE_Keras.C
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+++ b/tutorials/tmva/TMVA_SOFIE_Keras.C
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@@ -45,7 +45,7 @@ void TMVA_SOFIE_Keras(){
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TMacro m;
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m.AddLine(pythonSrc);
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m.SaveSource("make_keras_model.py");
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- gSystem->Exec("python make_keras_model.py");
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+ gSystem->Exec(TMVA::Python_Executable() + " make_keras_model.py");
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//Parsing the saved Keras .h5 file into RModel object
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SOFIE::RModel model = SOFIE::PyKeras::Parse("KerasModel.h5");
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diff --git a/tutorials/tmva/TMVA_SOFIE_ONNX.C b/tutorials/tmva/TMVA_SOFIE_ONNX.C
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index 30148db4fa..bf66c38896 100644
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--- a/tutorials/tmva/TMVA_SOFIE_ONNX.C
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+++ b/tutorials/tmva/TMVA_SOFIE_ONNX.C
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@@ -13,7 +13,7 @@ using namespace TMVA::Experimental;
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void TMVA_SOFIE_ONNX(){
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//Creating parser object to parse ONNX files
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SOFIE::RModelParser_ONNX Parser;
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- SOFIE::RModel model = Parser.Parse("../../tmva/sofie/test/input_models/Linear_16.onnx");
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+ SOFIE::RModel model = Parser.Parse(std::string(gROOT->GetTutorialsDir()) + "/tmva/Linear_16.onnx");
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//Generating inference code
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model.Generate();
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diff --git a/tutorials/tmva/TMVA_SOFIE_PyTorch.C b/tutorials/tmva/TMVA_SOFIE_PyTorch.C
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index b208b042d7..580787cae1 100644
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--- a/tutorials/tmva/TMVA_SOFIE_PyTorch.C
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+++ b/tutorials/tmva/TMVA_SOFIE_PyTorch.C
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@@ -47,7 +47,7 @@ void TMVA_SOFIE_PyTorch(){
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TMacro m;
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m.AddLine(pythonSrc);
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m.SaveSource("make_pytorch_model.py");
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- gSystem->Exec("python make_pytorch_model.py");
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+ gSystem->Exec(TMVA::Python_Executable() + " make_pytorch_model.py");
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//Parsing a PyTorch model requires the shape and data-type of input tensor
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//Data-type of input tensor defaults to Float if not specified
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--
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2.35.1
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