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[dask] Fixed Dask type annotation (#4558)
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@StrikerRUS
StrikerRUS authored Aug 29, 2021
1 parent 846e895 commit 053e888
Showing 1 changed file with 25 additions and 25 deletions.
50 changes: 25 additions & 25 deletions python-package/lightgbm/dask.py
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Original file line number Diff line number Diff line change
Expand Up @@ -396,10 +396,10 @@ def _train(
group: Optional[_DaskVectorLike] = None,
eval_set: Optional[List[Tuple[_DaskMatrixLike, _DaskCollection]]] = None,
eval_names: Optional[List[str]] = None,
eval_sample_weight: Optional[List[_DaskCollection]] = None,
eval_sample_weight: Optional[List[_DaskVectorLike]] = None,
eval_class_weight: Optional[List[Union[dict, str]]] = None,
eval_init_score: Optional[List[_DaskCollection]] = None,
eval_group: Optional[List[_DaskCollection]] = None,
eval_init_score: Optional[List[_DaskVectorLike]] = None,
eval_group: Optional[List[_DaskVectorLike]] = None,
eval_metric: Optional[Union[Callable, str, List[Union[Callable, str]]]] = None,
eval_at: Optional[Iterable[int]] = None,
**kwargs: Any
Expand Down Expand Up @@ -435,13 +435,13 @@ def _train(
of evals_result_ and best_score_ will be 'not_evaluated'.
eval_names : list of str, or None, optional (default=None)
Names of eval_set.
eval_sample_weight : list of Dask Arrays, Dask Series or None, optional (default=None)
eval_sample_weight : list of Dask Arrays or Dask Series, or None, optional (default=None)
Weights for each validation set in eval_set.
eval_class_weight : list of dict or str, or None, optional (default=None)
Class weights, one dict or str for each validation set in eval_set.
eval_init_score : list of Dask Arrays, Dask Series or None, optional (default=None)
eval_init_score : list of Dask Arrays or Dask Series, or None, optional (default=None)
Initial model score for each validation set in eval_set.
eval_group : list of Dask Arrays, Dask Series or None, optional (default=None)
eval_group : list of Dask Arrays or Dask Series, or None, optional (default=None)
Group/query for each validation set in eval_set.
eval_metric : str, callable, list or None, optional (default=None)
If str, it should be a built-in evaluation metric to use.
Expand Down Expand Up @@ -1025,10 +1025,10 @@ def _lgb_dask_fit(
group: Optional[_DaskVectorLike] = None,
eval_set: Optional[List[Tuple[_DaskMatrixLike, _DaskCollection]]] = None,
eval_names: Optional[List[str]] = None,
eval_sample_weight: Optional[List[_DaskCollection]] = None,
eval_sample_weight: Optional[List[_DaskVectorLike]] = None,
eval_class_weight: Optional[List[Union[dict, str]]] = None,
eval_init_score: Optional[List[_DaskCollection]] = None,
eval_group: Optional[List[_DaskCollection]] = None,
eval_init_score: Optional[List[_DaskVectorLike]] = None,
eval_group: Optional[List[_DaskVectorLike]] = None,
eval_metric: Optional[Union[Callable, str, List[Union[Callable, str]]]] = None,
eval_at: Optional[Iterable[int]] = None,
early_stopping_rounds: Optional[int] = None,
Expand Down Expand Up @@ -1162,9 +1162,9 @@ def fit(
init_score: Optional[_DaskVectorLike] = None,
eval_set: Optional[List[Tuple[_DaskMatrixLike, _DaskCollection]]] = None,
eval_names: Optional[List[str]] = None,
eval_sample_weight: Optional[List[_DaskCollection]] = None,
eval_sample_weight: Optional[List[_DaskVectorLike]] = None,
eval_class_weight: Optional[List[Union[dict, str]]] = None,
eval_init_score: Optional[List[_DaskCollection]] = None,
eval_init_score: Optional[List[_DaskVectorLike]] = None,
eval_metric: Optional[Union[Callable, str, List[Union[Callable, str]]]] = None,
early_stopping_rounds: Optional[int] = None,
**kwargs: Any
Expand Down Expand Up @@ -1194,9 +1194,9 @@ def fit(
sample_weight_shape="Dask Array or Dask Series of shape = [n_samples] or None, optional (default=None)",
init_score_shape="Dask Array or Dask Series of shape = [n_samples] or None, optional (default=None)",
group_shape="Dask Array or Dask Series or None, optional (default=None)",
eval_sample_weight_shape="list of Dask Arrays or Dask Series or None, optional (default=None)",
eval_init_score_shape="list of Dask Arrays or Dask Series or None, optional (default=None)",
eval_group_shape="list of Dask Arrays or Dask Series or None, optional (default=None)"
eval_sample_weight_shape="list of Dask Arrays or Dask Series, or None, optional (default=None)",
eval_init_score_shape="list of Dask Arrays or Dask Series, or None, optional (default=None)",
eval_group_shape="list of Dask Arrays or Dask Series, or None, optional (default=None)"
)

# DaskLGBMClassifier does not support group, eval_group, early_stopping_rounds.
Expand Down Expand Up @@ -1341,8 +1341,8 @@ def fit(
init_score: Optional[_DaskVectorLike] = None,
eval_set: Optional[List[Tuple[_DaskMatrixLike, _DaskCollection]]] = None,
eval_names: Optional[List[str]] = None,
eval_sample_weight: Optional[List[_DaskCollection]] = None,
eval_init_score: Optional[List[_DaskCollection]] = None,
eval_sample_weight: Optional[List[_DaskVectorLike]] = None,
eval_init_score: Optional[List[_DaskVectorLike]] = None,
eval_metric: Optional[Union[Callable, str, List[Union[Callable, str]]]] = None,
early_stopping_rounds: Optional[int] = None,
**kwargs: Any
Expand Down Expand Up @@ -1371,9 +1371,9 @@ def fit(
sample_weight_shape="Dask Array or Dask Series of shape = [n_samples] or None, optional (default=None)",
init_score_shape="Dask Array or Dask Series of shape = [n_samples] or None, optional (default=None)",
group_shape="Dask Array or Dask Series or None, optional (default=None)",
eval_sample_weight_shape="list of Dask Arrays or Dask Series or None, optional (default=None)",
eval_init_score_shape="list of Dask Arrays or Dask Series or None, optional (default=None)",
eval_group_shape="list of Dask Arrays or Dask Series or None, optional (default=None)"
eval_sample_weight_shape="list of Dask Arrays or Dask Series, or None, optional (default=None)",
eval_init_score_shape="list of Dask Arrays or Dask Series, or None, optional (default=None)",
eval_group_shape="list of Dask Arrays or Dask Series, or None, optional (default=None)"
)

# DaskLGBMRegressor does not support group, eval_class_weight, eval_group, early_stopping_rounds.
Expand Down Expand Up @@ -1503,9 +1503,9 @@ def fit(
group: Optional[_DaskVectorLike] = None,
eval_set: Optional[List[Tuple[_DaskMatrixLike, _DaskCollection]]] = None,
eval_names: Optional[List[str]] = None,
eval_sample_weight: Optional[List[_DaskCollection]] = None,
eval_init_score: Optional[List[_DaskCollection]] = None,
eval_group: Optional[List[_DaskCollection]] = None,
eval_sample_weight: Optional[List[_DaskVectorLike]] = None,
eval_init_score: Optional[List[_DaskVectorLike]] = None,
eval_group: Optional[List[_DaskVectorLike]] = None,
eval_metric: Optional[Union[Callable, str, List[Union[Callable, str]]]] = None,
eval_at: Iterable[int] = (1, 2, 3, 4, 5),
early_stopping_rounds: Optional[int] = None,
Expand Down Expand Up @@ -1538,9 +1538,9 @@ def fit(
sample_weight_shape="Dask Array or Dask Series of shape = [n_samples] or None, optional (default=None)",
init_score_shape="Dask Array or Dask Series of shape = [n_samples] or None, optional (default=None)",
group_shape="Dask Array or Dask Series or None, optional (default=None)",
eval_sample_weight_shape="list of Dask Arrays or Dask Series or None, optional (default=None)",
eval_init_score_shape="list of Dask Arrays or Dask Series or None, optional (default=None)",
eval_group_shape="list of Dask Arrays or Dask Series or None, optional (default=None)"
eval_sample_weight_shape="list of Dask Arrays or Dask Series, or None, optional (default=None)",
eval_init_score_shape="list of Dask Arrays or Dask Series, or None, optional (default=None)",
eval_group_shape="list of Dask Arrays or Dask Series, or None, optional (default=None)"
)

# DaskLGBMRanker does not support eval_class_weight or early stopping
Expand Down

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