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+ bugbug-train backout --limit 30000 --no-download
2023-12-05 17:34:09,725:INFO:scripts.trainer:Skipping download of the databases
2023-12-05 17:34:09,725:INFO:scripts.trainer:Training *backout* model
2023-12-05 17:34:09,781:INFO:bugbug.models.backout:157 commits were backed out
2023-12-05 17:34:09,781:INFO:bugbug.models.backout:299 commits were not backed out
2023-12-05 17:34:09,866:INFO:bugbug.model:X: (456, 3), y: (456,)
Traceback (most recent call last):
File "/usr/local/bin/bugbug-train", line 8, in <module>
sys.exit(main())
File "/usr/local/lib/python3.10/site-packages/scripts/trainer.py", line 141, in main
retriever.go(args)
File "/usr/local/lib/python3.10/site-packages/scripts/trainer.py", line 41, in go
metrics = model_obj.train(limit=args.limit)
File "/usr/local/lib/python3.10/site-packages/bugbug/model.py", line 399, in train
scores = cross_validate(
File "/usr/local/lib/python3.10/site-packages/sklearn/model_selection/_validation.py", line 285, in cross_validate
_warn_or_raise_about_fit_failures(results, error_score)
File "/usr/local/lib/python3.10/site-packages/sklearn/model_selection/_validation.py", line 367, in _warn_or_raise_about_fit_failures
raise ValueError(all_fits_failed_message)
ValueError:
All the 5 fits failed.
It is very likely that your model is misconfigured.
You can try to debug the error by setting error_score='raise'.
Below are more details about the failures:
--------------------------------------------------------------------------------
5 fits failed with the following error:
Traceback (most recent call last):
File "/usr/local/lib/python3.10/site-packages/sklearn/model_selection/_validation.py", line 686, in _fit_and_score
estimator.fit(X_train, y_train, **fit_params)
File "/usr/local/lib/python3.10/site-packages/sklearn/pipeline.py", line 378, in fit
Xt = self._fit(X, y, **fit_params_steps)
File "/usr/local/lib/python3.10/site-packages/sklearn/pipeline.py", line 316, in _fit
self._validate_steps()
File "/usr/local/lib/python3.10/site-packages/sklearn/pipeline.py", line 207, in _validate_steps
raise TypeError(
TypeError: All intermediate steps should be transformers and implement fit and transform or be the string 'passthrough' 'RandomUnderSampler(random_state=0)' (type <class 'imblearn.under_sampling._prototype_selection._random_under_sampler.RandomUnderSampler'>) doesn't
The text was updated successfully, but these errors were encountered:
Failing on bugbug integration test:
The text was updated successfully, but these errors were encountered: