def _parallel_build_trees(tree, forest, X, y, sample_weight, tree_idx, n_trees,
                          verbose=0, class_weight=None):
    if verbose > 1:
        print("building tree %d of %d" % (tree_idx + 1, n_trees))

    if forest.bootstrap:
        n_samples = X.shape[0]
        if sample_weight is None:
            curr_sample_weight = np.ones((n_samples,), dtype=np.float64)
        else:
            curr_sample_weight = sample_weight.copy()

        indices = _generate_sample_indices(tree.random_state, n_samples)
        sample_counts = bincount(indices, minlength=n_samples)
        curr_sample_weight *= sample_counts

        if class_weight == 'subsample':
            with warnings.catch_warnings():
                warnings.simplefilter('ignore', DeprecationWarning)
                curr_sample_weight *= compute_sample_weight('auto', y, indices)
        elif class_weight == 'balanced_subsample':
            curr_sample_weight *= compute_sample_weight('balanced', y, indices)

        tree.fit(X, y, sample_weight=curr_sample_weight, check_input=False)
    else:
        tree.fit(X, y, sample_weight=sample_weight, check_input=False)

    return tree
Check if the format of the hotkey is correct or not
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/ensemble/forest.py/_parallel_build_trees--crossover with--dataset/ETHPy150Open JT5D/Alfred-Popclip-Sublime/Sublime Text 2/Browser Refresh/win/pywinauto/tests/asianhotkey.py/_IsAsianHotkeyFormatIncorrect