Fix #12 app.py

app.py

@@ -102,8 +102,8 @@ class MappingNetwork(nn.Module):
         for layer in self.unshared:
             out += [layer(h)]
         out = torch.stack(out, dim=1) # (batch, num_domains, style_dim)
-        idx = torch.LongTensor(range(y.size(0))).unsqueeze(1).to(y.device)
-        s = torch.gather(out, 1, idx.unsqueeze(2).expand(-1, -1, out.size(2))).squeeze(1)
+        idx = torch.arange(y.size(0)).to(y.device)
+        s = out[idx, y]
         return s
 
 class StyleEncoder(nn.Module):
@@ -170,8 +170,8 @@ class Generator(nn.Module):
 
 # FUNCIÓN PARA CARGAR EL MODELO
 def load_pretrained_model(ckpt_path, img_size=256, style_dim=64, num_domains=3, device='cpu'):
-    num_domains_mappin = 2
-    latent_dim_for_mapping = 14
+    num_domains_mappin = 3
+    latent_dim_for_mapping = 13
     G = Generator(img_size, style_dim).to(device)
     M = MappingNetwork(latent_dim_for_mapping, style_dim, num_domains).to(device)
     S = StyleEncoder(img_size, style_dim, num_domains).to(device)
@@ -228,7 +228,7 @@ if __name__ == '__main__':
     checkpoint_path = 'iter/12500_nets_ema.ckpt'
     img_size = 128
     style_dim = 64
-    num_domains = 2
+    num_domains = 3
     device = 'cuda' if torch.cuda.is_available() else 'cpu'
 
     try: