make new early stopping parameters keyword-only

microsoft · Dec 18, 2024 · 44316d7 · 44316d7
1 parent a61726f
commit 44316d7
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Showing 2 changed files with 8 additions and 4 deletions.
diff --git a/python-package/lightgbm/dask.py b/python-package/lightgbm/dask.py
@@ -1134,10 +1134,11 @@ def __init__(
         random_state: Optional[Union[int, np.random.RandomState, "np.random.Generator"]] = None,
         n_jobs: Optional[int] = None,
         importance_type: str = "split",
+        client: Optional[Client] = None,
+        *,
         early_stopping: bool = False,
         n_iter_no_change: int = 10,
         validation_fraction: Optional[float] = 0.1,
-        client: Optional[Client] = None,
         **kwargs: Any,
     ):
         """Docstring is inherited from the lightgbm.LGBMClassifier.__init__."""
@@ -1340,10 +1341,11 @@ def __init__(
         random_state: Optional[Union[int, np.random.RandomState, "np.random.Generator"]] = None,
         n_jobs: Optional[int] = None,
         importance_type: str = "split",
+        client: Optional[Client] = None,
+        *,
         early_stopping: bool = False,
         n_iter_no_change: int = 10,
         validation_fraction: Optional[float] = 0.1,
-        client: Optional[Client] = None,
         **kwargs: Any,
     ):
         """Docstring is inherited from the lightgbm.LGBMRegressor.__init__."""
@@ -1510,10 +1512,11 @@ def __init__(
         random_state: Optional[Union[int, np.random.RandomState, "np.random.Generator"]] = None,
         n_jobs: Optional[int] = None,
         importance_type: str = "split",
+        client: Optional[Client] = None,
+        *,
         early_stopping: bool = False,
         n_iter_no_change: int = 10,
         validation_fraction: Optional[float] = 0.1,
-        client: Optional[Client] = None,
         **kwargs: Any,
     ):
         """Docstring is inherited from the lightgbm.LGBMRanker.__init__."""

diff --git a/python-package/lightgbm/sklearn.py b/python-package/lightgbm/sklearn.py
@@ -507,10 +507,11 @@ def __init__(
         random_state: Optional[Union[int, np.random.RandomState, np.random.Generator]] = None,
         n_jobs: Optional[int] = None,
         importance_type: str = "split",
+        *,
         early_stopping: bool = False,
         n_iter_no_change: int = 10,
         validation_fraction: Optional[float] = 0.1,
-        **kwargs,
+        **kwargs: Any,
     ):
         r"""Construct a gradient boosting model.