Mercurial > repos > bgruening > sklearn_stacking_ensemble_models
diff keras_train_and_eval.py @ 11:2b679bb676be draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 208a8d348e7c7a182cfbe1b6f17868146428a7e2"
author | bgruening |
---|---|
date | Tue, 13 Apr 2021 22:50:20 +0000 |
parents | ac40a2fe5750 |
children | b8378d4791b7 |
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--- a/keras_train_and_eval.py Tue Apr 13 17:21:05 2021 +0000 +++ b/keras_train_and_eval.py Tue Apr 13 22:50:20 2021 +0000 @@ -1,32 +1,32 @@ import argparse -import joblib import json -import numpy as np import os -import pandas as pd import pickle import warnings from itertools import chain -from scipy.io import mmread -from sklearn.pipeline import Pipeline -from sklearn.metrics.scorer import _check_multimetric_scoring -from sklearn.model_selection._validation import _score -from sklearn.model_selection import _search, _validation -from sklearn.utils import indexable, safe_indexing +import joblib +import numpy as np +import pandas as pd from galaxy_ml.externals.selene_sdk.utils import compute_score -from galaxy_ml.model_validations import train_test_split from galaxy_ml.keras_galaxy_models import _predict_generator +from galaxy_ml.model_validations import train_test_split from galaxy_ml.utils import ( - SafeEval, + clean_params, + get_main_estimator, + get_module, get_scoring, load_model, read_columns, + SafeEval, try_get_attr, - get_module, - clean_params, - get_main_estimator, ) +from scipy.io import mmread +from sklearn.metrics.scorer import _check_multimetric_scoring +from sklearn.model_selection import _search, _validation +from sklearn.model_selection._validation import _score +from sklearn.pipeline import Pipeline +from sklearn.utils import indexable, safe_indexing _fit_and_score = try_get_attr("galaxy_ml.model_validations", "_fit_and_score") @@ -104,7 +104,7 @@ rval = train_test_split(*new_arrays, **kwargs) for pos in nones: - rval[pos * 2 : 2] = [None, None] + rval[pos * 2: 2] = [None, None] return rval