PixelUnshuffle
class torch.nn.PixelUnshuffle(downscale_factor)
Reverses the "PixelShuffle" operation by rearranging elements in a
   tensor of shape (, C, H \times r, W \times r) to a tensor of shape
   (, C \times r^2, H, W), where r is a downscale factor.
See the paper: Real-Time Single Image and Video Super-Resolution
   Using an Efficient Sub-Pixel Convolutional Neural Network by Shi
   et. al (2016) for more details.
Parameters:
      downscale_factor (int) -- factor to decrease spatial
      resolution by
Shape:
      * Input: (*, C_{in}, H_{in}, W_{in}), where * is zero or more
        batch dimensions
  * Output: (*, C_{out}, H_{out}, W_{out}), where

  C_{out} = C_{in} \times \text{downscale\_factor}^2

  H_{out} = H_{in} \div \text{downscale\_factor}

  W_{out} = W_{in} \div \text{downscale\_factor}

Examples:
  >>> pixel_unshuffle = nn.PixelUnshuffle(3)
  >>> input = torch.randn(1, 1, 12, 12)
