def METHOD_NAME(self, val: Union[Tensor, Sequence[Tensor], None] = None, ax: Optional[_AX_TYPE] = None) -> _PLOT_OUT_TYPE:
    """Plot a single or multiple 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 and Axes object
    Raises:
        ModuleNotFoundError:
            If `matplotlib` is not installed
    .. plot::
        :scale: 75
        >>> # Example plotting a single value
        >>> import torch
        >>> from torchmetrics.clustering import FowlkesMallowsIndex
        >>> metric = FowlkesMallowsIndex()
        >>> metric.update(torch.randint(0, 4, (10,)), torch.randint(0, 4, (10,)))
        >>> fig_, ax_ = metric.plot(metric.compute())
    .. plot::
        :scale: 75
        >>> # Example plotting multiple values
        >>> import torch
        >>> from torchmetrics.clustering import FowlkesMallowsIndex
        >>> metric = FowlkesMallowsIndex()
        >>> for _ in range(10):
        ...     metric.update(torch.randint(0, 4, (10,)), torch.randint(0, 4, (10,)))
        >>> fig_, ax_ = metric.plot(metric.compute())
    """
    return self._plot(val, ax)