mindspore.mint.nn.functional.pixel_shuffle

mindspore.mint.nn.functional.pixel_shuffle(input, upscale_factor) → Tensor

Rearrange elements in a tensor according to an upscaling factor.

Rearranges elements in a tensor of shape $(\ast ,C\times r^2,H,W)$ to a tensor of shape $(\ast ,C,H\times r,W\times r)$, where r is an upscale factor.

This is useful for implementing efficient sub-pixel convolution with a stride of $1/r$.

For detailed introduction to the pixel_shuffle algorithm, refer to Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network .

Warning

This is an experimental API that is subject to change or deletion.

Parameters

• input (Tensor) – Tensor of shape $(\ast ,C\times r^2,H,W)$ . The dimension of input is larger than 2, and the length of third to last dimension can be divisible by the square of upscale_factor.

• upscale_factor (int) – factor to shuffle the input Tensor, and is a positive integer. upscale_factor is the above-mentioned $r$.

Returns

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

Raises

• ValueError – If upscale_factor is not a positive integer.

• ValueError – If the length of third to last dimension is not divisible by the square of upscale_factor.

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

Supported Platforms:

Ascend

Examples

>>> from mindspore import mint
>>> input = mint.randn(1, 9, 4, 4)
>>> output = mint.nn.functional.pixel_shuffle(input, 3)
>>> print(output.shape)
    (1, 1, 12, 12)