import tensorflow as tf

    If the mapping does not exist or `vocab_filename` is not present within it,
    we will default to sanitizing `vocab_filename` and searching for files
    matching it within the assets directory.

    In either case, if the constructed path does not point to an existing file
    within the assets subdirectory, we will return a None.

    Args:
      vocab_filename: The vocabulary name to lookup.
    """
    mapping_path = os.path.join(self._transformed_metadata_dir, self.ASSET_MAP)

    mapping = {}
    if tf.io.gfile.exists(mapping_path):
      with tf.io.gfile.GFile(mapping_path) as f:
        mapping = json.loads(f.read())
        if vocab_filename in mapping:
          vocab_path = os.path.join(self.transform_savedmodel_dir,
                                    tf.saved_model.ASSETS_DIRECTORY,
                                    mapping[vocab_filename])
          if tf.io.gfile.exists(vocab_path):
            return vocab_path

    prefix = os.path.join(self.transform_savedmodel_dir,
                          tf.saved_model.ASSETS_DIRECTORY,
                          sanitized_vocab_filename(filename=vocab_filename))
    files = tf.io.gfile.glob(prefix) + tf.io.gfile.glob(
        '{}.tfrecord.gz'.format(prefix))
