def multitask_sequence_accuracy(*args) -> float:
    """
    Accuracy for multiple simultaneous sequence labeling (tagging) tasks.
    For each sequence the model checks whether all its elements
    are labeled correctly for all the individual taggers.

    Args:
        *args: a list of `2n` inputs. The first `n` inputs are the correct answers for `n` tasks,
            and the last `n` are the predicted ones. For each task an

    Returns:
        The percentage of sequences where all the items has correct answers for all `n` tasks.

    """
    n = len(args)
    y_true_by_tasks, y_predicted_by_tasks = args[:n // 2], args[n // 2:]
    y_true_by_sents = list(zip(*y_true_by_tasks))
    y_predicted_by_sents = list(zip(*y_predicted_by_tasks))
    y_true = list(list(zip(*elem)) for elem in y_true_by_sents)
    y_predicted = list(list(zip(*elem)) for elem in y_predicted_by_sents)
    return accuracy(y_true, y_predicted)

    Accuracy for multiple simultaneous sequence labeling (tagging) tasks.
    For each sequence the model checks whether all its elements
    are labeled correctly for all the individual taggers.

    Args:
        *args: a list of `2n` inputs. The first `n` inputs are the correct answers for `n` tasks,
            and the last `n` are the predicted ones. For each task an

    Returns:
        The percentage of sequences where all the items has correct answers for all `n` tasks.

    
deeppavlov/metrics/accuracy.py