58 lines
1.4 KiB
Python
58 lines
1.4 KiB
Python
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from .module import Module
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from .. import functional as F
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from torch import Tensor
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__all__ = ['ChannelShuffle']
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class ChannelShuffle(Module):
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r"""Divides and rearranges the channels in a tensor.
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This operation divides the channels in a tensor of shape :math:`(*, C , H, W)`
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into g groups and rearranges them as :math:`(*, \frac{C}{g}, g, H, W)`,
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while keeping the original tensor shape.
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Args:
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groups (int): number of groups to divide channels in.
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Examples::
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>>> # xdoctest: +IGNORE_WANT("FIXME: incorrect want")
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>>> channel_shuffle = nn.ChannelShuffle(2)
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>>> input = torch.randn(1, 4, 2, 2)
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>>> print(input)
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[[[[1, 2],
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[3, 4]],
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[[5, 6],
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[7, 8]],
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[[9, 10],
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[11, 12]],
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[[13, 14],
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[15, 16]],
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]]
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>>> output = channel_shuffle(input)
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>>> print(output)
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[[[[1, 2],
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[3, 4]],
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[[9, 10],
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[11, 12]],
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[[5, 6],
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[7, 8]],
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[[13, 14],
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[15, 16]],
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]]
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"""
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__constants__ = ['groups']
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groups: int
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def __init__(self, groups: int) -> None:
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super().__init__()
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self.groups = groups
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def forward(self, input: Tensor) -> Tensor:
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return F.channel_shuffle(input, self.groups)
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def extra_repr(self) -> str:
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return f'groups={self.groups}'
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