densenet.py 文件源码

def forward(self, x):
        # x = x.clone()
        x[:, 0] = (x[:, 0] - 0.485) / 0.229
        x[:, 1] = (x[:, 1] - 0.456) / 0.224
        x[:, 2] = (x[:, 2] - 0.406) / 0.225
        features = self.features(x)
        # temp_size = features.size(0)
        out = F.relu(features, inplace=True)
        out = F.avg_pool2d(out, kernel_size=7).view(features.size(0), -1)
        ft = out.clone()
        out = self.classifier(out)
        return out,ft