f4c14d1daf86c6c05d8d36c53bc8e7587f00c206,implementations/ccgan/models.py,UNetDown,__init__,#UNetDown#,10

Before Change

                    nn.LeakyReLU(0.2, inplace=True) ]

        if normalize:
            model += [nn.BatchNorm2d(out_size, 0.8)]

        if dropout:
            model += [nn.Dropout(dropout)]

        self.model = nn.Sequential(*model)

    def forward(self, x):
        return self.model(x)

After Change

        super(UNetDown, self).__init__()
        model = [nn.Conv2d(in_size, out_size, 4, stride=2, padding=1, bias=False)]
        if normalize:
            model.append(nn.BatchNorm2d(out_size, 0.8))
        model.append(nn.LeakyReLU(0.2))
        if dropout:
            model.append(nn.Dropout(dropout))

Instances