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)