U Mh@s>ddlmZddlmZddlmZdgZGdddeZdS) )Module) functional)TensorChannelShufflecsVeZdZUdZdgZeed<eddfdd Zeeddd Z e d d d Z Z S) ra.Divides and rearranges the channels in a tensor. This operation divides the channels in a tensor of shape :math:`(*, C , H, W)` into g groups as :math:`(*, \frac{C}{g}, g, H, W)` and shuffles them, while retaining the original tensor shape in the final output. Args: groups (int): number of groups to divide channels in. Examples:: >>> channel_shuffle = nn.ChannelShuffle(2) >>> input = torch.arange(1, 17, dtype=torch.float32).view(1, 4, 2, 2) >>> input tensor([[[[ 1., 2.], [ 3., 4.]], [[ 5., 6.], [ 7., 8.]], [[ 9., 10.], [11., 12.]], [[13., 14.], [15., 16.]]]]) >>> output = channel_shuffle(input) >>> output tensor([[[[ 1., 2.], [ 3., 4.]], [[ 9., 10.], [11., 12.]], [[ 5., 6.], [ 7., 8.]], [[13., 14.], [15., 16.]]]]) groupsN)rreturncst||_dSN)super__init__r)selfr __class__Q/var/www/html/venv/lib/python3.8/site-packages/torch/nn/modules/channelshuffle.pyr .s zChannelShuffle.__init__)inputr cCst||jSr )FZchannel_shuffler)r rrrrforward2szChannelShuffle.forward)r cCs d|jS)Nzgroups=)r)r rrr extra_repr5szChannelShuffle.extra_repr) __name__ __module__ __qualname____doc__Z __constants__int__annotations__r rrstrr __classcell__rrrrrs "N) modulerrrZtorchr__all__rrrrrs