61228f3243eaee39cba31a9abd2afc6ead9612a8,implementations/discogan/models.py,UNetUp,__init__,#UNetUp#,27

Before Change

        model = [   nn.Upsample(scale_factor=2),
                    nn.Conv2d(in_size, out_size, 3, stride=1, padding=1),
                    nn.LeakyReLU(0.2, inplace=True),
                    nn.InstanceNorm2d(out_size) ]

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

        self.model = nn.Sequential(*model)

    def forward(self, x, skip_input):

After Change

    def __init__(self, in_size, out_size, dropout=0.0):
        super(UNetUp, self).__init__()
        layers = [  nn.ConvTranspose2d(in_size, out_size, 4, 2, 1),
                    nn.InstanceNorm2d(out_size),
                    nn.ReLU(inplace=True)]
        if dropout:
            layers.append(nn.Dropout(dropout))

Instances