class_docstr: Summarize CNN and Daily Mail articles to their summary highlights.
class_docstr_tok: ["Summarize","CNN","and","Daily","Mail","articles","to","their","summary","highlights","."]
code: def generate_text_for_vocab(self, data_dir, tmp_dir):
      del data_dir
      all_files, urls_path = _maybe_download_corpora(
          tmp_dir, problem.DatasetSplit.TRAIN
      )
      return example_generator(all_files, urls_path, sum_token=False)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import hashlib
  import io
  import os
  import random
  import tarfile
  from tensor2tensor.data_generators import generator_utils
  from tensor2tensor.data_generators import problem
  from tensor2tensor.data_generators import text_encoder
  from tensor2tensor.data_generators import text_problems
  from tensor2tensor.data_generators import wiki_lm
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 1 for calling the SummarizeCnnDailymail32k obj's underlying member method code with example usage: obj.generate_text_for_vocab(data_dir, tmp_dir) and returns: example_generator