class_docstr: Abstract class for dialog problems.
docstr: Save the vocabulary to a file.
  
  Args:
    vocab: dict
docstr_tok: ["Save","the","vocabulary","to","a","file",".","Args",":","vocab",":","dict"]
code: def save_vocab(self, vocab):
      """Save the vocabulary to a file.
  
      Args:
        vocab: dict
      """
      voc_file = open(
          os.path.join(self._data_dir, self.vocab_file), "w"
      )
  
      # Put the reserved tokens in.
      voc_file.write("<pad>\n")
      voc_file.write("<EOS>\n")
      for word, _ in vocab.most_common(self.targeted_vocab_size - 3):
          voc_file.write(word + "\n")
      voc_file.write("<unk>")
  
      voc_file.close()
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import re
  import tarfile
  import zipfile
  import requests
  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.text_problems import VocabType
  from tensor2tensor.layers import modalities
  from tensor2tensor.utils import metrics
  import tensorflow.compat.v1
label_desc: Use image node_id 32 for calling the DialogAbstract obj's underlying member method code with example usage: obj.save_vocab(vocab) without return types