tiple values from the metric.

        Args:
            val: Either a single result from calling `metric.forward` or `metric.compute` or a list of these results.
                If no value is provided, will automatically call `metric.compute` and plot that result.
            ax: An matplotlib axis object. If provided will add plot to that axis

        Returns:
            Figure object and Axes object

        Raises:
            ModuleNotFoundError:
                If `matplotlib` is not installed

        .. plot::
            :scale: 75

            >>> from torch import randint
            >>> # Example plotting a single value per class
            >>> from torchmetrics.classification import MulticlassMatthewsCorrCoef
            >>> metric = MulticlassMatthewsCorrCoef(num_classes=3)
            >>> metric.update(randint(3, (20,)), randint(3, (20,)))
            >>> fig_, ax_ = metric.plot()

        .. plot::
            :scale: 75

            >>> from torch import randint
            >>> # Example plotting a multiple values per class
            >>> from torchmetrics.classification import MulticlassMatthewsCorrCoef
            >>> metric = MulticlassMatthewsCorrCoef(num_classes=3)
            >>> values = []
            >>> for _ in range(20):
            ...     values.append(metric(randint(3, (20,)), randint(3, (20,))))
            >>> fig_, ax_ = metric.plot(values)

        r8