sklearn/metrics/_scorer.py:41:5: F401 [*] `..utils.metadata_routing.process_routing` imported but unused
   |
39 |     _routing_enabled,
40 |     get_routing_for_object,
41 |     process_routing,
   |     ^^^^^^^^^^^^^^^ F401
42 | )
43 | from ..utils.validation import _check_response_method
   |
   = help: Remove unused import: `..utils.metadata_routing.process_routing`

sklearn/metrics/_scorer.py:616:89: E501 Line too long (91 > 88)
    |
614 |         return Bunch(
615 |             score={
616 |                 k: kwargs[k] for k in self.get_metadata_routing().consumes("score", kwargs)
    |                                                                                         ^^^ E501
617 |             }
618 |         )
    |

Found 2 errors.
[*] 1 fixable with the `--fix` option.

--- sklearn/metrics/_scorer.py
+++ sklearn/metrics/_scorer.py
@@ -551,9 +551,7 @@
 
         self._metadata_request = MetadataRequest(owner=self.__class__.__name__)
         estimator_request = getattr(
-            estimator,
-            "_metadata_request",
-            estimator._get_default_requests()
+            estimator, "_metadata_request", estimator._get_default_requests()
         )
         if hasattr(estimator_request, "score"):
             self._metadata_request.score = copy.deepcopy(estimator_request.score)
@@ -613,7 +611,8 @@
     def _route_scorer_metadata(self, estimator, kwargs):
         return Bunch(
             score={
-                k: kwargs[k] for k in self.get_metadata_routing().consumes("score", kwargs)
+                k: kwargs[k]
+                for k in self.get_metadata_routing().consumes("score", kwargs)
             }
         )
 

--- sklearn/model_selection/_validation.py
+++ sklearn/model_selection/_validation.py
@@ -363,16 +363,20 @@
                 estimator=estimator,
                 # TODO(SLEP6): also pass metadata to the predict method for
                 # scoring?
-                method_mapping=MethodMapping().add(caller="fit", callee="fit")
+                method_mapping=MethodMapping().add(caller="fit", callee="fit"),
             )
         )
         try:
             routed_params = process_routing(router, "fit", **params)
             scorer_router = scorers._route_scorer_metadata(estimator, params)
-            routed_params.scorer = Bunch(score={
-                k: v for step in scorer_router.values()
-                for params in step.values() for k, v in params.items()
-            })
+            routed_params.scorer = Bunch(
+                score={
+                    k: v
+                    for step in scorer_router.values()
+                    for params in step.values()
+                    for k, v in params.items()
+                }
+            )
         except UnsetMetadataPassedError as e:
             # The default exception would mention `fit` since in the above
             # `process_routing` code, we pass `fit` as the caller. However,

2 files would be reformatted, 922 files already formatted