code: def get_pretrained_ckpt_path(
      download_directory: str, config_file: str
  ) -> Tuple[Any, Any]:
      """
      If the config_file has an associated pretrained checkpoint,
      return path to downloaded checkpoint and preloaded checkpoint
  
      Arguments:
          download_directory: path to download checkpoints to
          config_file: mmdet config file path for which to find and load pretrained weights
      Returns:
          checkpoint path, loaded checkpoint
      """
      config_file = config_file.split("/")[-1]
      if config_file in CONFIG_TO_PRETRAINED:
          ckpt_path = model_hub.utils.download_url(
              download_directory, CONFIG_TO_PRETRAINED[config_file]
          )
          return ckpt_path, torch.load(ckpt_path)  # type: ignore
      return None, None
  
file_path: determined/model_hub/model_hub/mmdetection/utils.py
imports: import os
  from typing import Any, Dict, Tuple
  import mmcv
  import torch
  import model_hub.utils
label_desc: Use image node_id 2 for calling a global function with example usage: get_pretrained_ckpt_path(download_directory, config_file) and returns: None,  None, ckpt_path,  torch