class_docstr: Implements the chatbot problem with Cornell Movie Dialog dataset.
  
  https://www.cs.cornell.edu/~cristian/Cornell_Movie-Dialogs_Corpus.html
class_docstr_tok: ["Implements","the","chatbot","problem","with","Cornell","Movie","Dialog","dataset",".","https",":","\/\/www.cs.cornell.edu\/~cristian\/Cornell_Movie-Dialogs_Corpus.html"]
code: def extract_dialog_ids(self):
      dialogs = open(
          os.path.join(self._raw_data, "movie_conversations.txt"),
          errors="ignore",
      )
  
      dialog_list = []
      # Each line contains a dialog.
      for line in dialogs:
          line = line.split(" +++$+++ ")
          line = line[3].split(",")
  
          i = 0
          for item in line:
              line[i] = re.sub("[^A-Z0-9]", "", item)
              i += 1
          dialog_list.append(line)
  
      dialogs.close()
      return dialog_list
  
file_path: tensor2tensor/tensor2tensor/data_generators/dialog_cornell.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import os
  import re
  from tensor2tensor.data_generators import dialog_abstract
  from tensor2tensor.data_generators import text_encoder
  from tensor2tensor.utils import registry
label_desc: Use image node_id 4 for calling the DialogCornell32k obj's underlying member method code with example usage: obj.extract_dialog_ids() and returns: dialog_list