torch.min
torch.min(input) -> Tensor
Returns the minimum value of all elements in the "input" tensor.
Warning:
 This function produces deterministic (sub)gradients unlike
 "min(dim=0)"

Parameters:
      input (Tensor) -- the input tensor.
Example:
  >>> a = torch.randn(1, 3)
  >>> a
  tensor([[ 0.6750,  1.0857,  1.7197]])
  >>> torch.min(a)
  tensor(0.6750)

torch.min(input, dim, keepdim=False, *, out=None)
Returns a namedtuple "(values, indices)" where "values" is the
   minimum value of each row of the "input" tensor in the given
   dimension "dim". And "indices" is the index location of each
   minimum value found (argmin).
If "keepdim" is "True", the output tensors are of the same size as
   "input" except in the dimension "dim" where they are of size 1.
   Otherwise, "dim" is squeezed (see "torch.squeeze()"), resulting in
   the output tensors having 1 fewer dimension than "input".
Note: