constant divisor).
Warning:
 Currently, only unbatched (3D) or batched (4D) image-like output
 tensors are supported.

Shape:
      * Input: (N, C \times \prod(\text{kernel_size}), L) or (C
        \times \prod(\text{kernel_size}), L)
  * Output: (N, C, \text{output\_size}[0], \text{output\_size}[1],
    \dots) or (C, \text{output\_size}[0], \text{output\_size}[1],
    \dots) as described above

Examples:
  >>> fold = nn.Fold(output_size=(4, 5), kernel_size=(2, 2))
  >>> input = torch.randn(1, 3 * 2 * 2, 12)
  >>> output = fold(input)
  >>> output.size()
  torch.Size([1, 3, 4, 5])
