code: def main(_):
      # Legacy datasets
      urls = set(
          tfds.core.download.checksums.get_all_url_infos().keys()
      )
  
      # Dataset-as-folder datasets
      # Could keep track of the dataset name, so the report clearly indicates which
      # dataset should be updated.
      url_infos = {
          name: tfds.builder_cls(name).url_infos
          for name in tfds.list_builders(with_community_datasets=False)
      }
      for url_info in url_infos.values():
          if url_info:
              urls |= url_info.keys()
  
      urls = sorted(urls)
  
      with futures.ThreadPoolExecutor(max_workers=100) as executor:
          all_codes = executor.map(_get_status_code, urls)
  
      print("\n************ Summary ************\n")
      total_errors = 0
      for url, code in zip(urls, all_codes):
          if code == requests.codes.ok:
              continue
          total_errors += 1
          print(f"{url} - status code: {code}")
      print(f"{total_errors} URLs had issues")
  
imports: from concurrent import futures
  from absl import app
  import requests
  import tensorflow_datasets
label_desc: Use image node_id 2 for calling a global function with example usage: main(_) without return types