def snli_token_generator(tmp_dir, train, vocab_size):
  """Generate example dicts."""
  _download_and_parse_dataset(tmp_dir, train)

  symbolizer_vocab = _get_or_generate_vocab(
      tmp_dir, 'vocab.subword_text_encoder', vocab_size)

  file_name = 'train' if train else 'dev'
  data_file = os.path.join(tmp_dir, file_name + '.txt')
  with tf.gfile.GFile(data_file, mode='r') as f:
    for line in f:
      sent1, sent2, label = line.strip().split('\t')
      sent1_enc = symbolizer_vocab.encode(sent1)
      sent2_enc = symbolizer_vocab.encode(sent2)

      inputs = sent1_enc + [_SEP] + sent2_enc + [_EOS]
      yield {
          'inputs': inputs,
          'targets': [_LABEL_TO_ID[label]],
      }