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# torch.chunk

torch.chunk(input, chunks, dim=0) → List of Tensors

  Attempts to split a tensor into the specified number of chunks. Each chunk is a view of the input tensor.

  Note

  This function may return fewer than the specified number of chunks!

  See also

  `torch.tensor_split()` a function that always returns exactly the specified number of chunks

  If the tensor size along the given dimension `dim` is divisible by `chunks`, all returned chunks will be the same size. If the tensor size along the given dimension `dim` is not divisible by `chunks`, all returned chunks will be the same size, except the last one. If such division is not possible, this function may return fewer than the specified number of chunks.

  Parameters:

    - input (Tensor) – the tensor to split

    - chunks (int) – number of chunks to return

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

  Example

      >>> torch.arange(11).chunk(6)
      (tensor([0, 1]),
       tensor([2, 3]),
       tensor([4, 5]),
       tensor([6, 7]),
       tensor([8, 9]),
       tensor([10]))
      >>> torch.arange(12).chunk(6)
      (tensor([0, 1]),
       tensor([2, 3]),
       tensor([4, 5]),
       tensor([6, 7]),
       tensor([8, 9]),
       tensor([10, 11]))
      >>> torch.arange(13).chunk(6)
      (tensor([0, 1, 2]),
       tensor([3, 4, 5]),
       tensor([6, 7, 8]),
       tensor([ 9, 10, 11]),
       tensor([12]))

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