PixelShuffle
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class torch.nn.PixelShuffle(upscale_factor)
[source] -
Rearranges elements in a tensor of shape to a tensor of shape , where r is an upscale factor.
This is useful for implementing efficient sub-pixel convolution with a stride of .
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
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upscale_factor (int) – factor to increase spatial resolution by
- Shape:
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- Input: , where * is zero or more batch dimensions
- Output: , where
Examples:
>>> pixel_shuffle = nn.PixelShuffle(3) >>> input = torch.randn(1, 9, 4, 4) >>> output = pixel_shuffle(input) >>> print(output.size()) torch.Size([1, 1, 12, 12])
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Licensed under the 3-clause BSD License.
https://pytorch.org/docs/1.8.0/generated/torch.nn.PixelShuffle.html