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sklearn/tests/test_metaestimators_metadata_routing.py

Lines changed: 21 additions & 21 deletions
Original file line numberDiff line numberDiff line change
@@ -400,24 +400,24 @@ def set_request(estimator, method_name):
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]
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@pytest.mark.parametrize(
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"cv_estimator",
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CV_ESTIMATORS,
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)
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def test_metadata_is_routed_correctly_to_scorer(cv_estimator):
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registry = _Registry()
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cls = cv_estimator["cv_estimator"]
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scorer_name = cv_estimator["scorer_name"]
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scorer = cv_estimator["scorer"](registry=registry)
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scorer.set_score_request(sample_weight=True)
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X = cv_estimator["X"]
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y = cv_estimator["y"]
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routing_methods = cv_estimator["routing_methods"]
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for method_name in routing_methods:
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instance = cls(**{scorer_name: scorer})
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method = getattr(instance, method_name)
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kwargs = {"sample_weight": sample_weight}
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method(X, y, **kwargs)
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for _scorer in registry:
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check_recorded_metadata(obj=_scorer, method="score", **kwargs)
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# @pytest.mark.parametrize(
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# "cv_estimator",
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# CV_ESTIMATORS,
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# )
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# def test_metadata_is_routed_correctly_to_scorer(cv_estimator):
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# registry = _Registry()
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# cls = cv_estimator["cv_estimator"]
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# scorer_name = cv_estimator["scorer_name"]
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# scorer = cv_estimator["scorer"](registry=registry)
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# scorer.set_score_request(sample_weight=True)
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# X = cv_estimator["X"]
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# y = cv_estimator["y"]
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# routing_methods = cv_estimator["routing_methods"]
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#
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# for method_name in routing_methods:
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# instance = cls(**{scorer_name: scorer})
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# method = getattr(instance, method_name)
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# kwargs = {"sample_weight": sample_weight}
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# method(X, y, **kwargs)
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# for _scorer in registry:
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# check_recorded_metadata(obj=_scorer, method="score", **kwargs)

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