Shortcuts

PixelUnshuffle

class torch.nn.PixelUnshuffle(downscale_factor)[source]

Reverses the PixelShuffle operation by rearranging elements in a tensor of shape (,C,H×r,W×r)(*, C, H \times r, W \times r) to a tensor of shape (,C×r2,H,W)(*, 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: (,Cin,Hin,Win)(*, C_{in}, H_{in}, W_{in}) , where * is zero or more batch dimensions

  • Output: (,Cout,Hout,Wout)(*, C_{out}, H_{out}, W_{out}) , where

Cout=Cin×downscale_factor2C_{out} = C_{in} \times \text{downscale\_factor}^2
Hout=Hin÷downscale_factorH_{out} = H_{in} \div \text{downscale\_factor}
Wout=Win÷downscale_factorW_{out} = W_{in} \div \text{downscale\_factor}

Examples:

>>> pixel_unshuffle = nn.PixelUnshuffle(3)
>>> input = torch.randn(1, 1, 12, 12)
>>> output = pixel_unshuffle(input)
>>> print(output.size())
torch.Size([1, 9, 4, 4])

Docs

Access comprehensive developer documentation for PyTorch

View Docs

Tutorials

Get in-depth tutorials for beginners and advanced developers

View Tutorials

Resources

Find development resources and get your questions answered

View Resources