torch / nn / torch.nn
PixelShuffle¶
-
class
torch.nn.
PixelShuffle
(upscale_factor: int)[source]¶ Rearranges elements in a tensor of shape to a tensor of shape .
This is useful for implementing efficient sub-pixel convolution with a stride of .
Look at 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
upscale_factor (int) – factor to increase spatial resolution by
- Shape:
Input: where
Output: where and
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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