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# torch.split

torch.split(tensor, split_size_or_sections, dim=0)

  Splits the tensor into chunks. Each chunk is a view of the original tensor.

  If `split_size_or_sections` is an integer type, then `tensor` will be split into equally sized chunks (if possible). Last chunk will be smaller if the tensor size along the given dimension `dim` is not divisible by `split_size`.

  If `split_size_or_sections` is a list, then `tensor` will be split into `len(split_size_or_sections)` chunks with sizes in `dim` according to `split_size_or_sections`.

  Parameters:

    - tensor (Tensor) – tensor to split.

    - split_size_or_sections (int) or (list(int)) – size of a single chunk or list of sizes for each chunk

    - dim (int) – dimension along which to split the tensor.

  Return type:

    Tuple[Tensor, …]

  Example:

      >>> a = torch.arange(10).reshape(5, 2)
      >>> a
      tensor([[0, 1],
              [2, 3],
              [4, 5],
              [6, 7],
              [8, 9]])
      >>> torch.split(a, 2)
      (tensor([[0, 1],
               [2, 3]]),
       tensor([[4, 5],
               [6, 7]]),
       tensor([[8, 9]]))
      >>> torch.split(a, [1, 4])
      (tensor([[0, 1]]),
       tensor([[2, 3],
               [4, 5],
               [6, 7],
               [8, 9]]))

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