torch.hsplit
torch.hsplit(input, indices_or_sections) -> List of Tensors
Splits "input", a tensor with one or more dimensions, into multiple
   tensors horizontally according to "indices_or_sections". Each split
   is a view of "input".
If "input" is one dimensional this is equivalent to calling
   torch.tensor_split(input, indices_or_sections, dim=0) (the split
   dimension is zero), and if "input" has two or more dimensions it's
   equivalent to calling torch.tensor_split(input,
   indices_or_sections, dim=1) (the split dimension is 1), except that
   if "indices_or_sections" is an integer it must evenly divide the
   split dimension or a runtime error will be thrown.
This function is based on NumPy's "numpy.hsplit()".
Parameters:
      * input (Tensor) -- tensor to split.
  * **indices_or_sections** (*int** or **list** or **tuple of
    ints*) -- See argument in "torch.tensor_split()".

Example::
      >>> t = torch.arange(16.0).reshape(4,4)
      >>> t