docs: def to_human_readable(self, data, label_batch_entries=True, indices=None,
                          sep="\n"):
      """Returns a human-readable version of a one-hot encoding of words.
  
      Args:
        data: (numpy.ndarray S x B x OH). One-hot encoding of words. S is
            sequence length, B is batch size, OH is one hot dimensionality.
        label_batch_entries: (bool). Whether to add numerical label before each
            batch element in the output string.
        indices: (list(int) or None). Used to select a subset of minibatch indices
            to print. None will print the whole minibatch.
        sep: (str) separator which separates the output for each batch. Defaults
            to the newline character.
  
      Returns:
        String composed from the data.
      """
      batch_size = data.shape[1]
      result = []
      indices = indices or six.moves.range(batch_size)
      for b in indices:
        index_seq = np.argmax(data[:, b], axis=1)
        prefix = "b_{}: ".format(b) if label_batch_entries else ""
        result.append(prefix + self._data_source.decode_to_string(index_seq))
      return sep.join(result)