, ``ignore`` or a float

    Example:
        >>> from torch import tensor
        >>> from torchmetrics.aggregation import RunningSum
        >>> metric = RunningSum(window=3)
        >>> for i in range(6):
        ...     current_val = metric(tensor([i]))
        ...     running_val = metric.compute()
        ...     total_val = tensor(sum(list(range(i+1))))  # total sum over all samples
        ...     print(f"{current_val=}, {running_val=}, {total_val=}")
        current_val=tensor(0.), running_val=tensor(0.), total_val=tensor(0)
        current_val=tensor(1.), running_val=tensor(1.), total_val=tensor(1)
        current_val=tensor(2.), running_val=tensor(3.), total_val=tensor(3)
        current_val=tensor(3.), running_val=tensor(6.), total_val=tensor(6)
        current_val=tensor(4.), running_val=tensor(9.), total_val=tensor(10)
        current_val=tensor(5.), running_val=tensor(12.), total_val=tensor(15)

    rs