class_docstr: Base class for bAbi question answering problems.
class_docstr_tok: ["Base","class","for","bAbi","question","answering","problems","."]
code: def generate_text_for_vocab(self, data_dir, tmp_dir):
      # NOTE: for babi, we create the vocab from both train and test data.
      for dataset_split in [
          problem.DatasetSplit.TRAIN,
          problem.DatasetSplit.EVAL,
      ]:
          for example in _babi_parser(
              tmp_dir,
              self.babi_task_id,
              self.babi_subset,
              dataset_split,
              self.joint_training,
          ):
              context = " ".join(example[FeatureNames.STORY])
              yield " ".join(context.split())
              yield " ".join(example[FeatureNames.QUESTION].split())
              yield example[FeatureNames.ANSWER]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import os
  import shutil
  import tarfile
  import requests
  import six
  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 tokenizer
  from tensor2tensor.layers import modalities
  from tensor2tensor.utils import metrics
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 14 for calling the BabiQa obj's underlying member method code with example usage: obj.generate_text_for_vocab(data_dir, tmp_dir) without return types