(self, channels, reduction=16)
| 6 | |
| 7 | class SEWeightModule(nn.Module): |
| 8 | def __init__(self, channels, reduction=16): |
| 9 | super(SEWeightModule, self).__init__() |
| 10 | self.avg_pool = nn.AdaptiveAvgPool2d(1) |
| 11 | self.fc1 = nn.Conv2d(channels, channels//reduction, kernel_size=1, padding=0) |
| 12 | self.relu = nn.ReLU(inplace=True) |
| 13 | self.fc2 = nn.Conv2d(channels//reduction, channels, kernel_size=1, padding=0) |
| 14 | self.sigmoid = nn.Sigmoid() |
| 15 | |
| 16 | def forward(self, x): |
| 17 | out = self.avg_pool(x) |