class_docstr: Mutator that takes safety data with __ok__ and __notok__ labels and converts to
  "pos" and "neg" which we use elsewhere.
  
  It assumes the last line of 'text' is the last dialogue utterance, and splits that
  by word for the left-to-right classifier.
code: def many_episode_mutation(
      self, episode: List[Message]
  ) -> List[Message]:
      new_episodes = []
      for message in episode:
          new_message = message.copy()
          label = message["labels"][0]
          if label == "__notok__":
              label = "neg"
          else:
              label = "pos"
          new_message.force_set("labels", [label])
          text = "\n".join(message["text"].split("\n")[:-1])
          label_words = message["text"].split("\n")[-1].split()
          if len(label_words) < 2:
              continue
          for i in range(1, len(label_words) + 1):
              new_message2 = new_message.copy()
              label = " ".join(label_words[:i])
              new_text = text + "\n" + label
              new_message2.force_set("text", new_text)
              new_episodes.append([new_message2])
      return new_episodes
  
imports: from typing import List, Tuple
  from typing import Optional
  from parlai.core.agents import Agent, create_agent_from_model_file, create_agent_from_shared
  from parlai.core.params import ParlaiParser
  from parlai.core.message import Message
  from parlai.core.opt import Opt
  from parlai.core.mutators import register_mutator, ManyEpisodeMutator, EpisodeMutator
  import parlai.tasks.bot_adversarial_dialogue.agents
  import parlai.tasks.dialogue_safety.agents
  import parlai.utils.logging
  from parlai.core.metrics import AverageMetric
label_desc: Use image node_id 1 for calling the SafetyLTRMutator obj's underlying member method code with example usage: obj.many_episode_mutation(episode) and returns: new_episodes