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# torch.roll

torch.roll(input, shifts, dims=None) → Tensor

  Roll the tensor `input` along the given dimension(s). Elements that are shifted beyond the last position are re-introduced at the first position. If `dims` is None, the tensor will be flattened before rolling and then restored to the original shape.

  Parameters:

    - input (Tensor) – the input tensor.

    - shifts (int or tuple of ints) – The number of places by which the elements of the tensor are shifted. If shifts is a tuple, dims must be a tuple of the same size, and each dimension will be rolled by the corresponding value

    - dims (int or tuple of ints) – Axis along which to roll

  Example:

      >>> x = torch.tensor([1, 2, 3, 4, 5, 6, 7, 8]).view(4, 2)
      >>> x
      tensor([[1, 2],
              [3, 4],
              [5, 6],
              [7, 8]])
      >>> torch.roll(x, 1)
      tensor([[8, 1],
              [2, 3],
              [4, 5],
              [6, 7]])
      >>> torch.roll(x, 1, 0)
      tensor([[7, 8],
              [1, 2],
              [3, 4],
              [5, 6]])
      >>> torch.roll(x, -1, 0)
      tensor([[3, 4],
              [5, 6],
              [7, 8],
              [1, 2]])
      >>> torch.roll(x, shifts=(2, 1), dims=(0, 1))
      tensor([[6, 5],
              [8, 7],
              [2, 1],
              [4, 3]])

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