Update app.py

app.py

@@ -66,13 +66,13 @@ class MLP(nn.Module):
         probs = F.softmax(logits, dim=1)
         return torch.multinomial(probs, num_samples=1).item()
     
-mlp = MLP(config['num_char'], 
-          config['hidden_nodes'], 
-          config['embeddings'], 
-          config['window'], 
-          config['num_layers'])
+mlp = MLP(mlp_config['num_char'], 
+          mlp_config['hidden_nodes'], 
+          mlp_config['embeddings'], 
+          mlp_config['window'], 
+          mlp_config['num_layers'])
 
-mlp.load_state_dict(torch.load(weights_path))
+mlp.load_state_dict(torch.load(mlp_weights_path))
 mlp.eval()
 
 class WaveNet(nn.Module):