class_docstr: Tests for the Genderation Bias Teacher.
  
  For now, just test the flatten_and_classify utility function.
code: def test_flatten_and_classify(self):
      word_lists = ControllableTaskTeacher.build_wordlists(
          ParlaiParser().parse_args([])
      )
      utterances = [
          "hello there",
          "hi there dad, what's up",
          "not much, do you know where your sister is?",
          "I have not seen her, I thought she was with grandpa",
          "well, if you see her, let me know",
          "will do!",
          "ok, have a good day",
          "bye bye! tell mom I say hello",
      ]
      tokens = ["f0m1", "f1m1", "f0m0", "f1m0"]
      episode = [
          Message(
              {
                  "text": utterances[i],
                  "labels": [utterances[i + 1]],
                  "episode_done": False,
              }
          )
          for i in range(0, len(utterances) - 1, 2)
      ]
      episode[-1].force_set("episode_done", True)
      new_episode = flatten_and_classify(episode, -1, word_lists)
      assert len(new_episode) == 4
      assert all(
          ex["text"].endswith(tok)
          for ex, tok in zip(new_episode, tokens)
      ), f"new episode: {new_episode}"
  
file_path: ParlAI/tests/tasks/test_genderation_bias.py
imports: import unittest
  from parlai.core.message import Message
  from parlai.core.params import ParlaiParser
  from parlai.tasks.genderation_bias.agents import ControllableTaskTeacher
  from parlai.tasks.genderation_bias.utils import flatten_and_classify
label_desc: Use image node_id 1 for calling the TestGenderationBiasTeacher obj's underlying member method code with example usage: obj.test_flatten_and_classify() without return types