710b9ac1a28d418bddc41aeeda320ab4de4d17fe,torchreid/models/resnet.py,ResNet101,forward,#ResNet101#Any#,47

Before Change

    def forward(self, x):
        x = self.base(x)
        x = F.avg_pool2d(x, x.size()[2:])
        f = x.view(x.size(0), -1)
        if not self.training:
            return f
        y = self.classifier(f)

        if self.loss == {"xent"}:
            return y

After Change

        residual = x

        out = self.conv1(x)
        out = self.bn1(out)
        out = self.relu(out)

        out = self.conv2(out)
        out = self.bn2(out)

        if self.downsample is not None:
            residual = self.downsample(x)

        out += residual
        out = self.relu(out)

        return out


class Bottleneck(nn.Module):
    expansion = 4

Instances