'}hDddlmZddlmZddlmZdgZGddeZy) )Module) functional)TensorChannelShufflecZeZdZUdZdgZeed<deddffd ZdedefdZ de fdZ xZ S) raDivides and rearranges the channels in a tensor. This operation divides the channels in a tensor of shape :math:`(*, C , H, W)` into g groups and rearranges them as :math:`(*, \frac{C}{g}, g, H, W)`, while keeping the original tensor shape. Args: groups (int): number of groups to divide channels in. Examples:: >>> # xdoctest: +IGNORE_WANT("FIXME: incorrect want") >>> 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]], ]] groupsreturnNc0t|||_yN)super__init__r )selfr __class__s ^/var/www/html/test/engine/venv/lib/python3.12/site-packages/torch/nn/modules/channelshuffle.pyrzChannelShuffle.__init__1s  inputcBtj||jSr )Fchannel_shuffler )rrs rforwardzChannelShuffle.forward5s   44rc d|jS)Nzgroups=)r )rs r extra_reprzChannelShuffle.extra_repr8s &&r) __name__ __module__ __qualname____doc__ __constants__int__annotations__rrrstrr __classcell__)rs@rrrsI#JJM Kst5V55'C'rN) modulerrrtorchr__all__rrrr)s"  1'V1'r