class_docstr: Teacher for written two-person dialogues with labels being responses for the
  previous statement.
  
  The data is traversed twice (doubled), once for modelling USER replies and once for
  modelling ASSISTANT replies.
class_docstr_tok: ["Teacher","for","written","two-person","dialogues","with","labels","being","responses","for","the","previous","statement",".","The","data","is","traversed","twice","(","doubled",")",",","once","for","modelling","USER","replies","and","once","for","modelling","ASSISTANT","replies","."]
code: def __init__(self, opt, shared=None):
      super().__init__(opt)
      opt["fn"] = "self-dialogs.json"
  
      if shared and "convos" in shared:
          # another instance was set up already, just reference its data
          self.convos = shared["convos"]
          self.ep_cheat_sheet = shared["ep_cheat_sheet"]
          self.num_ex = shared["num_ex"]
      else:
          # need to set up data from scratch
          self.ep_cheat_sheet = (
              {}
          )  # Stores imp. info. about each episode
          data_path = tm_utils._path(opt)
          self.num_ex = 0
          self._setup_data(data_path, opt)
  
      self.reset()
  
imports: from parlai.core.params import ParlaiParser
  import os
  import pandas
  from parlai.core.opt import Opt
  import parlai.core.tod.tod_core
  from typing import Optional
  from parlai.utils.data import DatatypeHelper
  from parlai.utils.io import PathManager
  import parlai.tasks.taskmaster.build
  import parlai.core.tod.tod_agents
  from parlai.core.teachers import FixedDialogTeacher
  from .None import tm_utils
  import json
label_desc: Use image node_id 1 to create a new SelfDialogueTeacher object from inherited base classes: FixedDialogTeacher with example: obj = SelfDialogueTeacher(opt, shared)