Mercurial > repos > goeckslab > pycaret_predict
changeset 14:7d78a6afc958 draft default tip
planemo upload for repository https://github.com/goeckslab/gleam commit 1ffd143e57fa952ee9dd84fc141771520aea0791
| author | goeckslab |
|---|---|
| date | Wed, 26 Nov 2025 17:49:50 +0000 |
| parents | f07850192bc2 |
| children | |
| files | base_model_trainer.py pycaret_macros.xml pycaret_train.py test-data/expected_best_model_classification.csv test-data/expected_model_classification.h5 |
| diffstat | 5 files changed, 23 insertions(+), 3 deletions(-) [+] |
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--- a/base_model_trainer.py Sat Nov 08 14:20:33 2025 +0000 +++ b/base_model_trainer.py Wed Nov 26 17:49:50 2025 +0000 @@ -175,6 +175,7 @@ "feature_interaction", "feature_ratio", "fix_imbalance", + "n_jobs", ]: val = getattr(self, attr, None) if val is not None:
--- a/pycaret_macros.xml Sat Nov 08 14:20:33 2025 +0000 +++ b/pycaret_macros.xml Wed Nov 26 17:49:50 2025 +0000 @@ -1,7 +1,7 @@ <macros> - <token name="@TABULAR_LEARNER_VERSION@">0.1.1</token> + <token name="@TABULAR_LEARNER_VERSION@">0.1.2</token> <token name="@PYCARET_VERSION@">3.3.2</token> - <token name="@SUFFIX@">1</token> + <token name="@SUFFIX@">2</token> <token name="@PYCARET_PREDICT_VERSION@">@PYCARET_VERSION@+@SUFFIX@</token> <token name="@PROFILE@">21.05</token> <xml name="python_requirements">
--- a/pycaret_train.py Sat Nov 08 14:20:33 2025 +0000 +++ b/pycaret_train.py Wed Nov 26 17:49:50 2025 +0000 @@ -1,5 +1,6 @@ import argparse import logging +import os from pycaret_classification import ClassificationModelTrainer from pycaret_regression import RegressionModelTrainer @@ -115,6 +116,13 @@ help="Random seed for PyCaret setup", ) parser.add_argument( + "--n-jobs", + dest="n_jobs", + type=int, + default=None, + help="Number of parallel jobs; defaults to GALAXY_SLOTS or 1 if unset/invalid.", + ) + parser.add_argument( "--probability_threshold", type=float, default=None, @@ -129,6 +137,16 @@ args = parser.parse_args() + # Derive n_jobs from CLI or GALAXY_SLOTS env var + if args.n_jobs is not None: + n_jobs = args.n_jobs + else: + slots_str = os.environ.get("GALAXY_SLOTS") + try: + n_jobs = int(slots_str) if slots_str is not None else 1 + except ValueError: + n_jobs = 1 + # Normalize cross-validation flags: --no_cross_validation overrides --cross_validation if args.no_cross_validation: args.cross_validation = False @@ -149,6 +167,7 @@ "feature_ratio": args.feature_ratio, "fix_imbalance": args.fix_imbalance, "tune_model": args.tune_model, + "n_jobs": n_jobs, "probability_threshold": args.probability_threshold, "best_model_metric": args.best_model_metric, }
--- a/test-data/expected_best_model_classification.csv Sat Nov 08 14:20:33 2025 +0000 +++ b/test-data/expected_best_model_classification.csv Wed Nov 26 17:49:50 2025 +0000 @@ -9,7 +9,7 @@ min_child_weight,0.001 min_split_gain,0.0 n_estimators,100 -n_jobs,-1 +n_jobs,1 num_leaves,31 objective, random_state,42