ChannelShuffle

class torch.nn.ChannelShuffle(groups)

Divide the channels in a tensor of shape $(*, C , H, W)$ into g groups and rearrange them as $(*, C \frac g, g, H, W)$, while keeping the original tensor shape.

Parameters:

groups (int) – number of groups to divide channels in.

Examples:

>>> channel_shuffle = nn.ChannelShuffle(2)
>>> input = torch.randn(1, 4, 2, 2)
>>> print(input)
[[[[1, 2],
   [3, 4]],
  [[5, 6],
   [7, 8]],
  [[9, 10],
   [11, 12]],
  [[13, 14],
   [15, 16]],
 ]]
>>> output = channel_shuffle(input)
>>> print(output)
[[[[1, 2],
   [3, 4]],
  [[9, 10],
   [11, 12]],
  [[5, 6],
   [7, 8]],
  [[13, 14],
   [15, 16]],
 ]]