def METHOD_NAME(metrics: Dict[str, Metric], dataset: VisionData) -> Dict[str, float]:
    """Calculate a list of ignite metrics on a given model and dataset.
    Returns
    -------
    t.Dict[str, float]
        Dictionary of metrics with the metric name as key and the metric value as value
    """
    def process_function(_, batch):
        return sequence_to_numpy(batch['predictions']), sequence_to_numpy(batch['labels'])
    engine = Engine(process_function)
    for name, metric in metrics.items():
        metric.reset()
        metric.attach(engine, name)
    state = engine.run(dataset.batch_loader)
    return state.metrics