mindscience.common.PixelUnshuffle

class mindscience.common.PixelUnshuffle(downscale_factor)[source]

Applies a pixelunshuffle operation over an input signal composed of several input planes. For more details, refer to Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network .

Typically, the input is of shape \((*, C, H \times r, W \times r)\) , and the output is of shape \((*, C \times r^2, H, W)\) , where r is a downscale factor and * is zero or more batch dimensions.

Parameters: downscale_factor (int) – factor to decrease spatial resolution by, and is a positive integer.

Inputs:

x (Tensor) - Tensor of shape \((*, C, H \times r, W \times r)\) . The dimension of x is larger than 2, and the length of second to last dimension and last dimension can be divisible by downscale_factor .

Outputs:

output (Tensor) - Tensor of shape \((*, C \times r^2, H, W)\) .

Raises

ValueError – If downscale_factor is not a positive integer.
ValueError – If the length of second to last dimension or last dimension is not divisible by downscale_factor .
TypeError – If the dimension of x is less than 3.