colornet.py 文件源码

def forward(self, x1, x2):
        x1 = F.relu(self.bn1(self.conv1(x1)))
        x1 = F.relu(self.bn2(self.conv2(x1)))
        x1 = F.relu(self.bn3(self.conv3(x1)))
        x1 = F.relu(self.bn4(self.conv4(x1)))
        x1 = F.relu(self.bn5(self.conv5(x1)))
        x1 = F.relu(self.bn6(self.conv6(x1)))
        if self.training:
            x2 = x1.clone()
        else:
            x2 = F.relu(self.bn1(self.conv1(x2)))
            x2 = F.relu(self.bn2(self.conv2(x2)))
            x2 = F.relu(self.bn3(self.conv3(x2)))
            x2 = F.relu(self.bn4(self.conv4(x2)))
            x2 = F.relu(self.bn5(self.conv5(x2)))
            x2 = F.relu(self.bn6(self.conv6(x2)))
        return x1, x2