pnasnet.py 文件源码

def forward(self, x):
        # Left branch
        y1 = self.sep_conv1(x)
        y2 = self.sep_conv2(x)
        # Right branch
        y3 = F.max_pool2d(x, kernel_size=3, stride=self.stride, padding=1)
        if self.stride==2:
            y3 = self.bn1(self.conv1(y3))
        y4 = self.sep_conv3(x)
        # Concat & reduce channels
        b1 = F.relu(y1+y2)
        b2 = F.relu(y3+y4)
        y = torch.cat([b1,b2], 1)
        return F.relu(self.bn2(self.conv2(y)))