> # Example plotting a single value
            >>> import torch
            >>> from torchmetrics.image import PeakSignalNoiseRatioWithBlockedEffect
            >>> metric = PeakSignalNoiseRatioWithBlockedEffect()
            >>> metric.update(torch.rand(2, 1, 10, 10), torch.rand(2, 1, 10, 10))
            >>> fig_, ax_ = metric.plot()

        .. plot::
            :scale: 75

            >>> # Example plotting multiple values
            >>> import torch
            >>> from torchmetrics.image import PeakSignalNoiseRatioWithBlockedEffect
            >>> metric = PeakSignalNoiseRatioWithBlockedEffect()
            >>> values = [ ]
            >>> for _ in range(10):
            ...     values.append(metric(torch.rand(2, 1, 10, 10), torch.rand(2, 1, 10, 10)))
            >>> fig_, ax_ = metric.plot(values)

        )