code: def snli_token_generator(tmp_dir, train, vocab_size):
    
    _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]],
        }
docs: Generate example dicts.