[tmva][sofie] New SOFIE Keras Parser - Fixing Conv2D test failures #30
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…ers and added tests for them. Imported Keras within the required functions. Created new CMakeLists.txt file for the keras parser. Made changes in the pythonization CMake file to build the keras parser files
…aced import keras_version with get_keras_version and called it in necessary files
… directory. Used import numpy statements within the parser functions to avoid slowing down the import of ROOT.
Do not use anymore .h5 files but .keras since .h5 is not anymore supported in keras3
the algorithm option is not anymore supported from scikit versions 1.6 Remove it in the MethodAdaBoost The SOFIE tutorials which require pymva need also a valid Keras parser, so exclude them if Keras is an unsupported version
… Keras3 Sequential In Keras3 Sequential output of a layer can have a different name than input of the next layer. Since in sequnrial model each layer has a single input/output use as output names the layer name (which is unique) and set as input name for the next layer
…d C++ parser - use new python keras parser for parsing a model into SOFIE. Since new parser is only Python base, move some tutorials from C++ to Python Remove also tutorial dependency on TMVA_Higgs_Classification by creating and training a model in tutorial TMVA_SOFIE_Keras_HiggsModel.py Adapt also RSofieReader for using new Python Keras parser
…ndency to test Fix also an issue in a SOFIE tutorial
…ils to train, it's test will be skipped. If model's file path is not found, the test will be skipped. Enabled Conv2d and GlobalAveragePooling2d tests
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This Pull request:
This pull request implements fixes during testing the New SOFIE Keras Parser.
The tests included Functional and Sequential models which comprised of
Conv2D,GlobalAveragePool2DandAveragePool2Dfor which Keras doesn't yet supportchannels_firstparameter while training it on CPU, on platforms such as mac beta 26, mac 14 and 15. Note that this error is generated during the training phase of the models and not while testing the models. There seems to be no fix for this but to usechannels_lastparameter during training. Since only some of the platforms face these issues, there's no need to disable the tests completely. I'll create an issue on Keras repository as well mentioning this and will add it in this PR as a reference.Changes or fixes:
During the training of these types of models we'll use a
try-exceptblock and check if there's any error generated during training, it would print a statement saying "Error while traning the keras model". While generating the inference code we'll then see if the model file exists, if not skip the test. Though this works, it makes the tests fail silently.Checklist:
This PR fixes #