code: def _wiki_articles(shard_id, wikis_dir=None):
    
    if not wikis_dir:
      wikis_dir = WIKI_CONTENT_DIR
    with tf.Graph().as_default():
      dataset = tf.data.TFRecordDataset(
          cc_utils.readahead(
              os.path.join(wikis_dir, WIKI_CONTENT_FILE % shard_id)),
          buffer_size=16 * 1000 * 1000)
  
      def _parse_example(ex_ser):
        """Parse serialized Example containing Wikipedia article content."""
        features = {
            "url": tf.VarLenFeature(tf.string),
            "title": tf.VarLenFeature(tf.string),
            "section_titles": tf.VarLenFeature(tf.string),
            "section_texts": tf.VarLenFeature(tf.string),
        }
        ex = tf.parse_single_example(ex_ser, features)
        for k in ex.keys():
          ex[k] = ex[k].values
        ex["url"] = ex["url"][0]
        ex["title"] = ex["title"][0]
        return ex
  
      dataset = dataset.map(_parse_example, num_parallel_calls=32)
      dataset = dataset.prefetch(100)
      record_it = dataset.make_one_shot_iterator().get_next()
  
      with tf.Session() as sess:
        while True:
          try:
            ex = sess.run(record_it)
          except tf.errors.OutOfRangeError:
            break
  
          sections = [
              WikipediaSection(title=text_encoder.to_unicode(title),
                               text=text_encoder.to_unicode(text))
              for title, text in zip(ex["section_titles"], ex["section_texts"])
          ]
          yield WikipediaArticle(
              url=text_encoder.to_unicode(ex["url"]),
              title=text_encoder.to_unicode(ex["title"]),
              sections=sections)
docs: Generates WikipediaArticles from GCS that are part of shard shard_id.