code: def test_generated_context(self):
      datatypes_seeds_and_desired_contexts = [
          (
              "train",
              0,
              {
                  "context_dataset": "wizard_of_wikipedia",
                  "persona_1_strings": [
                      "i am a vegetarian.",
                      "i live on a pig farm.",
                  ],
                  "persona_2_strings": [
                      "my wife hates me , she thinks i'm lazy and poor.",
                      "i won a lottery 6 years ago but nobody knows.",
                  ],
                  "additional_context": "Vegetarianism",
                  "person1_seed_utterance": "What reasons would a person become a vegetarian?",
                  "person2_seed_utterance": "religion is one, it is strongly linked with a number of religions that originated in ancient India ",
              },
          ),
          (
              "valid",
              1,
              {
                  "context_dataset": "convai2",
                  "persona_1_strings": [
                      "my parents were also teachers.",
                      "for vacation i enjoy time at the beach.",
                  ],
                  "persona_2_strings": [
                      "i love to go to disney world every year.",
                      "i am in the third grade.",
                  ],
                  "additional_context": None,
                  "person1_seed_utterance": "you have your whole life in front of you i am sure you'll",
                  "person2_seed_utterance": "maybe i will meet him at disney world ! 3",
              },
          ),
          (
              "test",
              2,
              {
                  "context_dataset": "wizard_of_wikipedia",
                  "persona_1_strings": [
                      "i like to dance.",
                      "my aunt helped me escape when i was of.",
                  ],
                  "persona_2_strings": [
                      "my bedroom is purple and lime green.",
                      "i am a vegan.",
                  ],
                  "additional_context": "Dance",
                  "person1_seed_utterance": "I love to dance too!  What kind do you do?",
                  "person2_seed_utterance": "I love choreography dance, Dance can be categorized and described by its choreography, by its repertoire of movements",
              },
          ),
      ]
      for (
          datatype,
          seed,
          desired_context,
      ) in datatypes_seeds_and_desired_contexts:
          parser = ParlaiParser(False, False)
          parser.add_parlai_data_path()
          context_opt = parser.parse_args([])
          context_generator = ContextGenerator(
              context_opt, datatype=datatype, seed=seed
          )
          actual_context = context_generator.get_context()
          self.assertEqual(desired_context, actual_context)
  
imports: import unittest
  from unittest.mock import patch
  import parlai.utils.testing
  from parlai.agents.repeat_label.repeat_label import RepeatLabelAgent
  from parlai.core.opt import Opt
  from parlai.core.params import ParlaiParser
  from parlai.core.worlds import create_task
  from parlai.scripts.display_data import setup_args
  from parlai.tasks.blended_skill_talk.agents import ContextGenerator
  from parlai.tasks.blended_skill_talk.worlds import InteractiveWorld, _load_personas
label_desc: Use image node_id 1 for calling the TestContextGenerator obj's underlying member method code with example usage: obj.test_generated_context() without return types