code: def _collect_path_to_url_infos() -> (
      Dict[tfds.core.Path, Dict[Url, checksums.UrlInfo]]
  ):
      """Collect checksums paths to url_infos."""
      # Collect legacy checksums paths
      url_info_paths = list(
          checksums._checksum_paths().values()
      )  # pylint: disable=protected-access
  
      # Collect dataset-as-folder checksums path
      for name in tfds.list_builders(with_community_datasets=False):
          url_info_path = tfds.builder_cls(
              name
          )._checksums_path  # pylint: disable=protected-access
          if url_info_path.exists():
              url_info_paths.append(url_info_path)
  
      url_info_paths = [
          tfds.core.utils.to_write_path(p) for p in url_info_paths
      ]
      return {
          path: typing.cast(
              Dict[Url, checksums.UrlInfo],
              checksums.load_url_infos(path),
          )
          for path in url_info_paths
      }
  
file_path: datasets/tensorflow_datasets/scripts/cleanup/url_filename_recorder.py
imports: from concurrent import futures
  import dataclasses
  import itertools
  import typing
  from typing import Dict, NewType, Optional
  import urllib
  from absl import app
  from absl import logging
  import requests
  import tensorflow_datasets
  from tensorflow_datasets.core.download import checksums
  import tqdm
label_desc: Use image node_id 1 for calling a global function with example usage: _collect_path_to_url_infos() and returns: unknown