All of the dims of "self" must be named in order to use this
      method. The resulting tensor is a view on the original tensor.
  All dimension names of "self" must be present in "names".
  "names" may contain additional names that are not in
  "self.names"; the output tensor has a size-one dimension for
  each of those new names.

  "names" may contain up to one Ellipsis ("..."). The Ellipsis is
  expanded to be equal to all dimension names of "self" that are
  not mentioned in "names", in the order that they appear in
  "self".

  Python 2 does not support Ellipsis but one may use a string
  literal instead ("'...'").

  Parameters:
     **names** (*iterable of str*) -- The desired dimension
     ordering of the output tensor. May contain up to one Ellipsis
     that is expanded to all unmentioned dim names of "self".

  Examples:

     >>> tensor = torch.randn(2, 2, 2, 2, 2, 2)
