wideresnet.py 文件源码

def forward(self, x):
        if not self.equalInOut:
            x = self.relu1(self.bn1(x))
        else:
            out = self.relu1(self.bn1(x))
        out = self.conv1(self.equalInOut and out or x)
        if self.droprate > 0:
            out = F.dropout(out, p=self.droprate, training=self.training)
        out = self.conv2(self.relu2(self.bn2(out)))
        return torch.add((not self.equalInOut) and self.convShortcut(x) or x, out)