cale: 75

            >>> # Example plotting multiple values
            >>> import torch
            >>> from torchmetrics.clustering import MutualInfoScore
            >>> metric = MutualInfoScore()
            >>> values = [ ]
            >>> for _ in range(10):
            ...     values.append(metric(torch.randint(0, 4, (10,)), torch.randint(0, 4, (10,))))
            >>> fig_, ax_ = metric.plot(values)

        )