20 lines
653 B
Python
20 lines
653 B
Python
import torch.nn as nn
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import torch
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__all__ = ['SE3d']
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class Swish(nn.Module):
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def forward(self,x):
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return x * torch.sigmoid(x)
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class SE3d(nn.Module):
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def __init__(self, channel, reduction=8, use_relu=False):
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super().__init__()
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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(True) if use_relu else Swish() ,
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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, inputs):
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return inputs * self.fc(inputs.mean(-1).mean(-1).mean(-1)).view(inputs.shape[0], inputs.shape[1], 1, 1, 1)
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