
keepdim (bool) -- whether the output tensor has "dim"
        retained or not.

Keyword Arguments:
      out ((Tensor, Tensor), optional) -- The first
      tensor will be populated with the median values and the second
      tensor, which must have dtype long, with their indices in the
      dimension "dim" of "input".
Example:
  >>> a = torch.randn(4, 5)
  >>> a
  tensor([[ 0.2505, -0.3982, -0.9948,  0.3518, -1.3131],
          [ 0.3180, -0.6993,  1.0436,  0.0438,  0.2270],
          [-0.2751,  0.7303,  0.2192,  0.3321,  0.2488],
          [ 1.0778, -1.9510,  0.7048,  0.4742, -0.7125]])
  >>> torch.median(a, 1)
  torch.return_types.median(values=tensor([-0.3982,  0.2270,  0.2488,  0.4742]), indices=tensor([1, 4, 4, 3]))
