code: def store_checksums(dataset_name, sizes_checksums):
    
    path = _get_path(dataset_name)
    original_data = _get_sizes_checksums(path)
    new_data = original_data.copy()
    new_data.update(sizes_checksums)
    if original_data == new_data:
      return
    with tf.io.gfile.GFile(path, 'w') as f:
      for url, (size, checksum) in sorted(new_data.items()):
        f.write('%s %s %s\n' % (url, size, checksum))
docs: Store given checksums and sizes for specific dataset.
  
    Content of file is never disgarded, only updated. This is to ensure that if
    process is killed right after first download finishes, checksums registered
    during previous runs aren't lost.
  
    It is the responsibility of the caller not to call function multiple times in
    parallel for a given dataset.
  
    Only original file content is updated. This means the entire set of new sizes
    and checksums must be given at every call.
  
    Args:
      dataset_name: string.
      sizes_checksums: dict, {url: (size_in_bytes, checksum)}.