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from torch import nn | |
class LatentCodesDiscriminator(nn.Module): | |
def __init__(self, style_dim, n_mlp): | |
super().__init__() | |
self.style_dim = style_dim | |
layers = [] | |
for i in range(n_mlp-1): | |
layers.append( | |
nn.Linear(style_dim, style_dim) | |
) | |
layers.append(nn.LeakyReLU(0.2)) | |
layers.append(nn.Linear(512, 1)) | |
self.mlp = nn.Sequential(*layers) | |
def forward(self, w): | |
return self.mlp(w) | |