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Created with Raphaël 2.2.09Nov843229Oct28272625222120191815141312118765427Sep241413987632131Aug30272625242322212019181716141312119643227Jul26232221201918161587542130Jun2928232221181728May27262522212019181764329Apr282721201918161514131211109876131Mar302926252322print statements for version testing in model classupdate UNet to TF2do_pca_reduction enabled by default and printed in main and logging.info with durationmerged latest 331-upgrade-code-to-tensorflow-v2 changesdask==2021.3.0, because afterwards support for python 3.6 was dropped.changed dask version, hopefully importable in gitlab now.calculate_pca_reduction() in data handler changed to a multiprocessing workflow using dask with every 1e3th values claculation stepspython3.8/site-packages: path changed from python3.6 in create_runscripts_HPC.shadditional netcdf4 version install removed for setup_venv_hdfml.sh and reactivated ml Jupyter/... for mlt_modules_juwels.shdeactivated additional package updates in setup_venv_*.shadded pydot to requirements.txtreadded dask and added tabulate==0.8.9 to requirements.txtdo now load model properlytest if pipeline finishes now successfullyMerge branch 'lukas_issue337_bug_ci-pipeline-fails-for-docs' into 'lukas_issue331_test_tf2_on_local_system_and_hdfml'Merge branch 'lukas_issue331_test_tf2_on_local_system_and_hdfml' into 'lukas_issue337_bug_ci-pipeline-fails-for-docs'fix issue if checkpoint has no modeltests should pass now, at least for training run modulepipreqs does not return all required packages. added requirements_tf2.txt with all dependencies. Check on other platforms for compatibilityMerge remote-tracking branch 'origin/331-upgrade-code-to-tensorflow-v2' into felix_TF2_merge_testfixes to test_inception_model.py and test_model_class.py mostly keras importings and some tower.name difference related.in 'test_abstract_model_class.py' test_compile_options_setter_as_dict() needed to be disabled until AbstractModelClass.__compare_keras_optimizers() works againtest_compile_options_setter_as_mix_attr_dict_valid_duplicates_optimizer() needed to be disabled until AbstractModelClass.__compare_keras_optimizers() works againchanged assertions to be compatible with new tf2 outputs'import keras' changed to 'import tensorflow.keras as keras' in test_abstract_model_class.pyChanged assertion comparisment containing old keras declarations. Disabled testing '_compare_keras_optimizers' since it is disabledremoved dask from requirements.txt since it does not load in GitLab. Removed __init__.py in keras_legacy, because it was unnecessary and wrong. Changed string to rawstring in PyTestRegex() calls.Plot Oversampling plots with bin_edges_retransformedvincent_issue30…vincent_issue309_feat_class-based-oversampling-techniquetrying a new requirements.txt list that was generated using pipreqs (an automated requirements.txt generator based on import statements)trying a new requirements.txt list that was generated using pipreqs (an automated requirements.txt generator based on import statements)trying a new requirements.txt list that was generated using pipreqs (an automated requirements.txt generator based on import statements)trying with the local venv on a ubuntu-vm systemtrying with the local venv on a ubuntu-vm systemtrying with the local venv on a ubuntu-vm systemdeactivated psycopg2==2.8.5 (now unversioned in requirements.txt)requirements.txt from venv_juwels without 'ml Jupyter/2021.3.1-Python-3.8.5'Merge branch 'lukas_issue335_refac_feature-importance-use-unaggregated-results' into 'develop'fix calculation of feature importance, add new title method for the plot. /close #335unversioned dask in requirements.txt, because it does not load in pipelineupdated requirements.txt to all modules that are loaded with an fully loaded venv_juwels