a68ba97309512f691feb25e6a07af7561fc56e3b,sklearn/inspection/_permutation_importance.py,,permutation_importance,#Any#Any#Any#Any#Any#Any#Any#,45

Before Change

    scorer = check_scoring(estimator, scoring=scoring)

    baseline_score = scorer(estimator, X, y)
    scores = np.zeros((X.shape[1], n_repeats))

    scores = Parallel(n_jobs=n_jobs)(delayed(_calculate_permutation_scores)(
        estimator, X, y, col_idx, random_state, n_repeats, scorer
    ) for col_idx in range(X.shape[1]))

After Change

    // the fact that variables are shared or not depending on the active
    // joblib backend (sequential, thread-based or process-based).
    random_state = check_random_state(random_state)
    random_seed = random_state.randint(np.iinfo(np.int32).max + 1)

    scorer = check_scoring(estimator, scoring=scoring)
    baseline_score = scorer(estimator, X, y)

Instances