[python-package] add type hints on cv() #5271
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jameslamb
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StrikerRUS,
shiyu1994 and
jmoralez
as code owners
jameslamb
commented
Jun 7, 2022
| params: Dict[str, Any], | ||
| train_set: Dataset, | ||
| num_boost_round: int = 100, | ||
| folds: Optional[Union[Iterable[Tuple[np.ndarray, np.ndarray]], _LGBMBaseCrossValidator]] = None, |
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according to https://docs.python.org/3/library/typing.html#typing.Generator, it's ok to use Iterable[return_type] to document a generator or iterator. So it isn't necessary to use typing.Generator or typing.Iterator.
jameslamb
commented
Jun 7, 2022
| @@ -75,9 +75,9 @@ def __init__(self, *args, **kwargs): | |||
| from sklearn.utils.validation import assert_all_finite, check_array, check_X_y | |||
| try: | |||
| from sklearn.exceptions import NotFittedError | |||
| from sklearn.model_selection import GroupKFold, StratifiedKFold | |||
| from sklearn.model_selection import BaseCrossValidator, GroupKFold, StratifiedKFold | |||
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sklearn.model_selection.BaseCrossValidator has been in scikit-learn for at least 7 years, so I don't think this will cause any portability issues.
jmoralez
approved these changes
Jun 9, 2022
Co-authored-by: Nikita Titov <[email protected]>
40 tasks
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This pull request has been automatically locked since there has not been any recent activity since it was closed. To start a new related discussion, open a new issue at https://github.com/microsoft/LightGBM/issues including a reference to this. |
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Contributes to #3756.
This PR proposes adding type hints to
lightgbm.cv(), to improvemypy's ability to catch issues.