a4697d7e45e66a3264eb56dcf489d67d4df40d23,implementations/cgan/cgan.py,Discriminator,forward,#Discriminator#,98

Before Change

        label_emb = nn.Embedding(opt.n_classes, opt.img_size**2)(labels)
        label_emb = label_emb.view(label_emb.shape[0], 1, opt.img_size, opt.img_size)
        // Concatenate label embedding and image by channels
        d_input = torch.cat((label_emb, img), 1)
        feature_repr = self.model(d_input)
        feature_repr = feature_repr.view(feature_repr.shape[0], -1)
        validity = self.adv_layer(feature_repr)

After Change

    def forward(self, img, labels):
        // Concatenate label embedding and image by channels
        d_input = torch.cat((img.view(img.size(0), -1), self.label_embedding(labels)), -1)
        validity = self.model(d_input)

        return validity

Instances