2e5b28b3d9dde5865ffbdedceead869fccad9e93,models/SqueezeNet.py,SqueezeNet,forward,#SqueezeNet#Any#,87

Before Change

        x10 = self.conv10(x9)
        f = F.avg_pool2d(x10, x10.size()[2:]).view(x10.size(0), -1)

        if not self.training:
            return f

        y = self.classifier(f)

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

After Change

        x9 = self.fire9(x8)
        if self.bypass:
            x9 = x9 + x8
        x9 = F.dropout(x9, training=self.training)
        x10 = F.relu(self.conv10(x9))
        f = F.avg_pool2d(x10, x10.size()[2:]).view(x10.size(0), -1)

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

Instances