Update app.py

app.py

@@ -36,21 +36,15 @@ class model:
     def __init__(self):
         self.model = None
         self.model_name = None
-        self.model_dict = {}
 
     def gradio_demo(self, model_name, sequence_input, image):
         device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
         if self.model_name != model_name:
             self.model_name = model_name
-            del self.model
-            if self.model_name not in self.model_dict.keys():
-                model_ckpt_path = hf_hub_download(repo_id=f"HuangLab/{model_name}", filename="model.ckpt")
-                model_config_path = hf_hub_download(repo_id=f"HuangLab/{model_name}", filename="config.yaml")
-                hf_hub_download(repo_id=f"HuangLab/{model_name}", filename="nucleus_vqgan.yaml")
-                hf_hub_download(repo_id=f"HuangLab/{model_name}", filename="threshold_vqgan.yaml")
-                self.model_dict.update({self.model_name:[model_ckpt_path, model_config_path]})
-            else:
-                model_ckpt_path, model_config_path = self.model_dict[self.model_name]
+            model_ckpt_path = hf_hub_download(repo_id=f"HuangLab/{model_name}", filename="model.ckpt")
+            model_config_path = hf_hub_download(repo_id=f"HuangLab/{model_name}", filename="config.yaml")
+            hf_hub_download(repo_id=f"HuangLab/{model_name}", filename="nucleus_vqgan.yaml")
+            hf_hub_download(repo_id=f"HuangLab/{model_name}", filename="threshold_vqgan.yaml")
 
             # Load model config and set ckpt_path if not provided in config
             config = OmegaConf.load(model_config_path)