test_model_selection.py 文件源码

def test_feature_union_fit_failure_multiple_metrics():
    scoring = {"score_1": _passthrough_scorer, "score_2": _passthrough_scorer}
    X, y = make_classification(n_samples=100, n_features=10, random_state=0)

    pipe = Pipeline([('union', FeatureUnion([('good', MockClassifier()),
                                             ('bad', FailingClassifier())],
                                            transformer_weights={'bad': 0.5})),
                     ('clf', MockClassifier())])

    grid = {'union__bad__parameter': [0, 1, 2]}
    gs = dcv.GridSearchCV(pipe, grid, refit=False, scoring=scoring)

    # Check that failure raises if error_score is `'raise'`
    with pytest.raises(ValueError):
        gs.fit(X, y)

    # Check that grid scores were set to error_score on failure
    gs.error_score = float('nan')
    with pytest.warns(FitFailedWarning):
        gs.fit(X, y)

    for key in scoring:
        check_scores_all_nan(gs, 'union__bad__parameter', score_key=key)