--- /home/runner/work/scikit-learn/scikit-learn/sklearn/multioutput.py	2024-08-16 13:16:56.829798+00:00
+++ /home/runner/work/scikit-learn/scikit-learn/sklearn/multioutput.py	2024-08-16 13:17:16.886115+00:00
@@ -642,11 +642,18 @@
             None,
         ],
     }
 
     def __init__(
-        self, estimator, *, order=None, cv=None, random_state=None, verbose=False, base_estimator="deprecated"
+        self,
+        estimator,
+        *,
+        order=None,
+        cv=None,
+        random_state=None,
+        verbose=False,
+        base_estimator="deprecated",
     ):
         self.estimator = estimator
         self.order = order
         self.cv = cv
         self.random_state = random_state
@@ -695,11 +702,11 @@
         inv_order = np.empty_like(self.order_)
         inv_order[self.order_] = np.arange(len(self.order_))
         Y_output = Y_output_chain[:, inv_order]
 
         return Y_output
-    
+
     def _validate_estimator(self, default=None):
         """Check the base estimator.
 
         Sets the `estimator_` attributes.
         """
@@ -736,11 +743,11 @@
     #     return self._estimator
 
     # # TODO: remove in 1.8
     # @property
     # def estimator_(self):
-    #     return self._estimator    
+    #     return self._estimator
 
     @abstractmethod
     def fit(self, X, Y, **fit_params):
         """Fit the model to data matrix X and targets Y.
 
@@ -761,11 +768,11 @@
         -------
         self : object
             Returns a fitted instance.
         """
         self._validate_estimator()
-        
+
         X, Y = self._validate_data(X, Y, multi_output=True, accept_sparse=True)
 
         random_state = check_random_state(self.random_state)
         self.order_ = self.order
         if isinstance(self.order_, tuple):
@@ -1038,22 +1045,21 @@
         order=None,
         cv=None,
         chain_method="predict",
         random_state=None,
         verbose=False,
-        base_estimator="deprecated"
+        base_estimator="deprecated",
     ):
         super().__init__(
             estimator,
             order=order,
             cv=cv,
             random_state=random_state,
             verbose=verbose,
-            base_estimator=base_estimator
+            base_estimator=base_estimator,
         )
         self.chain_method = chain_method
-        
 
     @_fit_context(
         # ClassifierChain.estimator is not validated yet
         prefer_skip_nested_validation=False
     )
@@ -1172,11 +1178,11 @@
 
     Parameters
     ----------
     estimator : estimator
         The base estimator from which the regressor chain is built.
-        
+
     base_estimator : estimator
         The base estimator from which the classifier chain is built.
 
         .. deprecated:: x.x
             `base_estimator` is deprecated and will be removed in x.x.
would reformat /home/runner/work/scikit-learn/scikit-learn/sklearn/multioutput.py

Oh no! 💥 💔 💥
1 file would be reformatted, 923 files would be left unchanged.

sklearn/multioutput.py:12:1: I001 [*] Import block is un-sorted or un-formatted
   |
12 | / from abc import ABCMeta, abstractmethod
13 | | from numbers import Integral
14 | | 
15 | | import numpy as np
16 | | import scipy.sparse as sp
17 | | import warnings
18 | | 
19 | | from .base import (
20 | |     BaseEstimator,
21 | |     ClassifierMixin,
22 | |     MetaEstimatorMixin,
23 | |     RegressorMixin,
24 | |     _fit_context,
25 | |     clone,
26 | |     is_classifier,
27 | | )
28 | | from .model_selection import cross_val_predict
29 | | from .utils import Bunch, check_random_state
30 | | from .utils._param_validation import HasMethods, StrOptions
31 | | from .utils._response import _get_response_values
32 | | from .utils._user_interface import _print_elapsed_time
33 | | from .utils.metadata_routing import (
34 | |     MetadataRouter,
35 | |     MethodMapping,
36 | |     _raise_for_params,
37 | |     _routing_enabled,
38 | |     process_routing,
39 | | )
40 | | from .utils.metaestimators import available_if
41 | | from .utils.multiclass import check_classification_targets
42 | | from .utils.parallel import Parallel, delayed
43 | | from .utils.validation import (
44 | |     _check_method_params,
45 | |     _check_response_method,
46 | |     check_is_fitted,
47 | |     has_fit_parameter,
48 | | )
49 | | 
50 | | __all__ = [
   | |_^ I001
51 |       "MultiOutputRegressor",
52 |       "MultiOutputClassifier",
   |
   = help: Organize imports

sklearn/multioutput.py:647:89: E501 Line too long (110 > 88)
    |
646 |     def __init__(
647 |         self, estimator, *, order=None, cv=None, random_state=None, verbose=False, base_estimator="deprecated"
    |                                                                                         ^^^^^^^^^^^^^^^^^^^^^^ E501
648 |     ):
649 |         self.estimator = estimator
    |

sklearn/multioutput.py:700:1: W293 [*] Blank line contains whitespace
    |
699 |         return Y_output
700 |     
    | ^^^^ W293
701 |     def _validate_estimator(self, default=None):
702 |         """Check the base estimator.
    |
    = help: Remove whitespace from blank line

sklearn/multioutput.py:731:89: E501 Line too long (90 > 88)
    |
729 |     # # mypy error: Decorated property not supported
730 |     # @deprecated(  # type: ignore
731 |     #     "Attribute `base_estimator_` was deprecated in version 1.6 and will be removed "
    |                                                                                         ^^ E501
732 |     #     "in 1.8. Use `estimator_` instead."
733 |     # )
    |

sklearn/multioutput.py:741:33: W291 [*] Trailing whitespace
    |
739 |     # @property
740 |     # def estimator_(self):
741 |     #     return self._estimator    
    |                                 ^^^^ W291
742 | 
743 |     @abstractmethod
    |
    = help: Remove trailing whitespace

sklearn/multioutput.py:766:1: W293 [*] Blank line contains whitespace
    |
764 |         """
765 |         self._validate_estimator()
766 |         
    | ^^^^^^^^ W293
767 |         X, Y = self._validate_data(X, Y, multi_output=True, accept_sparse=True)
    |
    = help: Remove whitespace from blank line

sklearn/multioutput.py:898:1: W293 Blank line contains whitespace
    |
896 |     estimator : estimator
897 |         The base estimator from which the classifier chain is built.
898 |             
    | ^^^^^^^^^^^^ W293
899 |     order : array-like of shape (n_outputs,) or 'random', default=None
900 |         If `None`, the order will be determined by the order of columns in
    |
    = help: Remove whitespace from blank line

sklearn/multioutput.py:952:1: W293 Blank line contains whitespace
    |
951 |         .. versionadded:: 1.2
952 |     
    | ^^^^ W293
953 |     base_estimator : object, default="deprecated"
954 |          Use `estimator` instead.
    |
    = help: Remove whitespace from blank line

sklearn/multioutput.py:1054:1: W293 [*] Blank line contains whitespace
     |
1052 |         )
1053 |         self.chain_method = chain_method
1054 |         
     | ^^^^^^^^ W293
1055 | 
1056 |     @_fit_context(
     |
     = help: Remove whitespace from blank line

sklearn/multioutput.py:1177:1: W293 Blank line contains whitespace
     |
1175 |     estimator : estimator
1176 |         The base estimator from which the regressor chain is built.
1177 |         
     | ^^^^^^^^ W293
1178 |     base_estimator : estimator
1179 |         The base estimator from which the classifier chain is built.
     |
     = help: Remove whitespace from blank line

Found 10 errors.
[*] 5 fixable with the `--fix` option (3 hidden fixes can be enabled with the `--unsafe-fixes` option).

sklearn/externals/_arff.py:782: note: By default the bodies of untyped functions are not checked, consider using --check-untyped-defs  [annotation-unchecked]
sklearn/utils/_testing.py:1038: note: By default the bodies of untyped functions are not checked, consider using --check-untyped-defs  [annotation-unchecked]
sklearn/utils/_testing.py:1039: note: By default the bodies of untyped functions are not checked, consider using --check-untyped-defs  [annotation-unchecked]
sklearn/utils/_testing.py:1040: note: By default the bodies of untyped functions are not checked, consider using --check-untyped-defs  [annotation-unchecked]
sklearn/multioutput.py:618: error: Name "_available_if_estimator_has" already defined on line 81  [no-redef]
Found 1 error in 1 file (checked 551 source files)