values.
Raises:
      RuntimeError -- If any of the dimensions to compute the
      values over has size 0.
Note:
 NaN values are propagated to the output if at least one value is
 NaN.

See also:
 "torch.amin()" computes just the minimum value "torch.amax()"
 computes just the maximum value

Example:
  >>> torch.aminmax(torch.tensor([1, -3, 5]))
  torch.return_types.aminmax(
  min=tensor(-3),
  max=tensor(5))

  >>> # aminmax propagates NaNs
  >>> torch.aminmax(torch.tensor([1, -3, 5, torch.nan]))
  torch.return_types.aminmax(
  min=tensor(nan),
  max=tensor(nan))

  >>> t = torch.arange(10).view(2, 5)
  >>> t
  tensor([[0, 1, 2, 3, 4],
          [5, 6, 7, 8, 9]])
  >>> t.aminmax(dim=0, keepdim=True)
  torch.return_types.aminmax(
  min=tensor([[0, 1, 2, 3, 4]]),
  max=tensor([[5, 6, 7, 8, 9]]))
