时间：2021-01-03 15:35:35 | 栏目：Python代码 | 点击：次
以channel Attention Block为例子
class CAB(nn.Module):
def __init__(self, in_channels, out_channels):
super(CAB, self).__init__()
self.global_pooling = nn.AdaptiveAvgPool2d(output_size=1)
self.conv1 = nn.Conv2d(in_channels, out_channels, kernel_size=1, stride=1, padding=0)
self.relu = nn.ReLU()
self.conv2 = nn.Conv2d(out_channels, out_channels, kernel_size=1, stride=1, padding=0)
self.sigmod = nn.Sigmoid()
def forward(self, x):
x1, x2 = x # high, low
x = torch.cat([x1,x2],dim=1)
x = self.global_pooling(x)
x = self.conv1(x)
x = self.relu(x)
x = self.conv2(x)
x = self.sigmod(x)
x2 = x * x2
res = x2 + x1
return res