code: def adapt(model_path, save_path):
      model = torch.load(model_path)
      model_dict = model["model"]
      new_model_dict = model_dict.copy()
  
      for k, v in model_dict.items():
          for old_prefix, new_prefix in prefix_mapping.items():
              if k.startswith(old_prefix):
                  new_k = k.replace(old_prefix, new_prefix)
                  new_model_dict[new_k] = v
                  del new_model_dict[k]
                  break
      model["state_dict"] = new_model_dict
      del model["model"]
      torch.save(model, save_path)
  
imports: import argparse
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: adapt(model_path, save_path) without return types