~float` or :class:`~torch.Tensor`): a single float or an tensor of float values with
      arbitrary shape ``(...,)``.

    As output of `forward` and `compute` the metric returns the following output

    - ``agg`` (:class:`~torch.Tensor`): scalar float tensor with aggregated maximum value over all inputs received

    Args:
        nan_strategy: options:
            - ``'error'``: if any `nan` values are encountered will give a RuntimeError
            - ``'warn'``: if any `nan` values are encountered will give a warning and continue
            - ``'ignore'``: all `nan` values are silently removed
            - a float: if a float is provided will impute any `nan` values with this value

        kwargs: Additional keyword arguments, see :ref:`Metric kwargs` for more info.

    Raises:
        ValueError:
            If ``nan_strategy`` is not one of ``error``, ``warn``, ``ignore`` or a float

    Example:
        >>> from torch import tensor
        >>> from torchmetrics.aggregation import MaxMetric
        >>> metric = MaxMetric()
        >>> metric.update(1)
        >>> metric.update(tensor([2, 3]))
        >>> metric.compute()
        tensor(3.)

    Tr