class_docstr: Generates a controllable_gen version of a ParlAI task, i.e., for tasks with multi-
  turn dialogues (episodes), this will generate a task with single example episodes,
  in which we append to the context a special classification token.
class_docstr_tok: ["Generates","a","controllable_gen","version","of","a","ParlAI","task",",","i.e.",",","for","tasks","with","multi-","turn","dialogues","(","episodes",")",",","this","will","generate","a","task","with","single","example","episodes",",","in","which","we","append","to","the","context","a","special","classification","token","."]
docstr: Load list of explicitly gendered words.
  
  Words taken from <https://github.com/uclanlp/gn_glove/blob/main/wordlist/>.
  
  Examples include brother, girl, actress, husbands, etc.
docstr_tok: ["Load","list","of","explicitly","gendered","words",".","Words","taken","from","<","https",":","\/\/github.com\/uclanlp\/gn_glove\/blob\/main\/wordlist\/",">",".","Examples","include","brother",",","girl",",","actress",",","husbands",",","etc","."]
code: def build_wordlists(cls, opt: Opt) -> Tuple[List[str], List[str]]:
      """
      Load list of explicitly gendered words.
  
      Words taken from <https://github.com/uclanlp/gn_glove/blob/main/wordlist/>.
  
      Examples include brother, girl, actress, husbands, etc.
      """
      build(opt["datapath"])
      folder = os.path.join(opt["datapath"], "genderation_bias")
      male_words = os.path.join(folder, "male_word_file.txt")
      female_words = os.path.join(folder, "female_word_file.txt")
  
      with open(male_words, "r") as f:
          male = f.read().splitlines()
  
      with open(female_words, "r") as f:
          female = f.read().splitlines()
  
      return male, female
  
imports: from parlai.core.params import ParlaiParser
  from parlai.core.message import Message
  from parlai.core.opt import Opt
  from parlai.core.teachers import FixedDialogTeacher
  from parlai.utils.io import PathManager
  import parlai.utils.logging
  from parlai.utils.typing import TShared
  from parlai.tasks.genderation_bias.build import build
  from parlai.tasks.genderation_bias.utils import flatten_and_classify, get_original_task_module
  from copy import deepcopy
  import datetime
  import glob
  import json
  import os
  from tqdm import tqdm
  from typing import List, Optional, Tuple
label_desc: Use image node_id 6 for calling the ControllableTaskTeacher obj's underlying member method code with example usage: obj.build_wordlists(cls, opt) and returns: male,  female