U ‰dã@s8ddlmZddlmZddlmZGdd„deƒZdS) é)ÚModuleé)Ú functionalé)ÚTensorcsVeZdZUdZdgZeed<eddœ‡fdd„ Zeedœdd „Z e d œd d „Z ‡Z S) ÚChannelShufflea/Divide the channels in a tensor of shape :math:`(*, C , H, W)` into g groups and rearrange them as :math:`(*, C \frac g, g, H, W)`, while keeping the original tensor shape. Args: 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]], ]] ÚgroupsN)rÚreturncstt|ƒ ¡||_dS©N)ÚsuperrÚ__init__r)Úselfr©Ú __class__©úC/tmp/pip-unpacked-wheel-ua33x9lu/torch/nn/modules/channelshuffle.pyr ,szChannelShuffle.__init__)Úinputr cCst ||j¡Sr )ÚFZchannel_shuffler)r rrrrÚforward0szChannelShuffle.forward)r cCs d |j¡S)Nz groups={})Úformatr)r rrrÚ extra_repr3szChannelShuffle.extra_repr) Ú__name__Ú __module__Ú __qualname__Ú__doc__Z __constants__ÚintÚ__annotations__r rrÚstrrÚ __classcell__rrrrrs !rN)ÚmodulerÚrrZtorchrrrrrrÚs