torch.cummin
torch.cummin(input, dim, *, out=None)
Returns a namedtuple "(values, indices)" where "values" is the
   cumulative minimum of elements of "input" in the dimension "dim".
   And "indices" is the index location of each maximum value found in
   the dimension "dim".
  y_i = min(x_1, x_2, x_3, \dots, x_i)

Parameters:
      * input (Tensor) -- the input tensor.
  * **dim** (*int*) -- the dimension to do the operation over

Keyword Arguments:
      out (tuple, optional) -- the result tuple of two
      output tensors (values, indices)
Example:
  >>> a = torch.randn(10)
  >>> a
  tensor([-0.2284, -0.6628,  0.0975,  0.2680, -1.3298, -0.4220, -0.3885,  1.1762,
       0.9165,  1.6684])
  >>> torch.cummin(a, dim=0)
  torch.return_types.cummin(
      values=tensor([-0.2284, -0.6628, -0.6628, -0.6628, -1.3298, -1.3298, -1.3298, -1.3298,
      -1.3298, -1.3298]),
      indices=tensor([0, 1, 1, 1, 4, 4, 4, 4, 4, 4]))
