minor

app.py

@@ -76,7 +76,7 @@ def infer(cfg_scale, top_k, top_p, temperature, class_label, seed):
     print(f"gpt sampling takes about {sampling_time:.2f} seconds.")    
 
     index_sample = torch.tensor([output.outputs[0].token_ids for output in outputs], device=device)
-    if args.cfg_scale > 1.0:
+    if cfg_scale > 1.0:
         index_sample = index_sample[:len(class_labels)]
     t2 = time.time()
     samples = vq_model.decode_code(index_sample, qzshape) # output value is between [-1, 1]