code: def find_tb_files(base_dir: pathlib.Path) -> List[pathlib.Path]:
      """
      Recursively searches through base_dir and subdirectories to find files
      needed by Tensorboard, currently matching by filenames and extensions.
      This method is used to sync files generated during training to persistent storage.
  
      :param base_dir: starting directory path
      :return: list of filepaths within base_dir that are relevant Tensorboard files
      """
  
      if not base_dir.exists():
          logger.warning(f"{base_dir} directory does not exist.")
          return []
  
      return [
          file
          for filetype in tb_file_types
          for file in base_dir.rglob(filetype)
      ]
  
file_path: determined/harness/determined/tensorboard/util.py
imports: import logging
  import pathlib
  import re
  from typing import List, Optional
label_desc: Use image node_id 1 for calling a global function with example usage: find_tb_files(base_dir) and returns: unknown, list