Method forward

wan/models/wan_vae.py:55–58

(self, x)

        self.bias = nn.Parameter(torch.zeros(shape)) if bias else 0.

    def forward(self, x):
        return F.normalize(
            x, dim=(1 if self.channel_first else
                    -1)) * self.scale * self.gamma + self.bias


class Upsample(nn.Upsample):