code: def update_finetune_config(task, pretrain_config, path):
      finetune_config = load_yaml(path)
      default_config = get_easy_task(task).get_default_config()
  
      # update pretrain_config with finetune_config
      # and update distributed related configs to the default.
      for k in list(pretrain_config.keys()):
          if "dist_" in k or "_rank" in k:
              pretrain_config[k] = default_config[k]
          elif (
              k in finetune_config.keys()
              and pretrain_config[k] != finetune_config[k]
          ):
              pretrain_config[k] = finetune_config[k]
  
      for k in list(default_config.keys()):
          if k not in pretrain_config.keys():
              pretrain_config[k] = default_config[k]
  
      if "preprocessor_conf" in pretrain_config.keys():
          pretrain_config["preprocessor_conf"] = finetune_config.get(
              "preprocessor_conf", {}
          )
  
      return pretrain_config
  
label_desc: Use image node_id 2 for calling a global function with example usage: update_finetune_config(task, pretrain_config, path) and returns: pretrain_config