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mindspore.nn.PixelUnshuffle

class mindspore.nn.PixelUnshuffle(downscale_factor)

Applies the PixelUnshuffle operation over input which is the inverse of PixelShuffle. 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 $(\ast ,C,H\times r,W\times r)$ , and the output is of shape $(\ast ,C\times r^2,H,W)$ , where $r$ is a downscale factor and $\ast$ is zero or more batch dimensions.

Parameters

downscale_factor (int) – factor to unshuffle the input, and is a positive integer. downscale_factor is the above-mentioned $r$.

Inputs:

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

Outputs:

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

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 .

• ValueError – If the dimension of input is less than 3.

• TypeError – If input is not a Tensor.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore as ms
>>> import numpy as np
>>> pixel_unshuffle = ms.nn.PixelUnshuffle(2)
>>> input_x = np.arange(8 * 8).reshape((1, 1, 8, 8))
>>> input_x = ms.Tensor(input_x, ms.dtype.int32)
>>> output = pixel_unshuffle(input_x)
>>> print(output.shape)
(1, 4, 4, 4)