class_docstr: MSCOCO, 8k tokens vocab.
code: def generator(self, data_dir, tmp_dir, is_training):
      # We use the translate vocab file as the vocabulary for captions.
      # This requires having the vocab file present in the data_dir for the
      # generation pipeline to succeed.
      vocab_filename = self.vocab_problem.vocab_filename
      if is_training:
          return mscoco_generator(
              data_dir,
              tmp_dir,
              True,
              80000,
              vocab_filename=vocab_filename,
          )
      else:
          return mscoco_generator(
              data_dir,
              tmp_dir,
              False,
              40000,
              vocab_filename=vocab_filename,
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import io
  import json
  import os
  import random
  import zipfile
  from tensor2tensor.data_generators import generator_utils
  from tensor2tensor.data_generators import image_utils
  from tensor2tensor.data_generators import imagenet
  from tensor2tensor.data_generators import problem
  from tensor2tensor.data_generators import text_encoder
  from tensor2tensor.data_generators import translate_ende
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 6 for calling the ImageMsCocoTokens32k obj's underlying member method code with example usage: obj.generator(data_dir, tmp_dir, is_training) and returns: mscoco_generator, mscoco_generator