lama

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import torch.nn as nn
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class SELayer(nn.Module):
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    def __init__(self, channel, reduction=16):
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        super(SELayer, self).__init__()
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        self.avg_pool = nn.AdaptiveAvgPool2d(1)
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        self.fc = nn.Sequential(
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            nn.Linear(channel, channel // reduction, bias=False),
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            nn.ReLU(inplace=True),
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            nn.Linear(channel // reduction, channel, bias=False),
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            nn.Sigmoid()
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        )
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    def forward(self, x):
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        b, c, _, _ = x.size()
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        y = self.avg_pool(x).view(b, c)
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        y = self.fc(y).view(b, c, 1, 1)
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        res = x * y.expand_as(x)
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        return res
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