code: def __init__(self, opt, shared=None):
      super().__init__(opt, shared)
      if opt["limit_classifier_examples_at"] > 0:
          self.data = self.data[: opt["limit_classifier_examples_at"]]
      self.include_label_cand_only = opt["include_label_cand_only"]
      self.truncate_prediction_at = opt["truncate_prediction_at"]
      assert (
          "eval_classifier_model_file" in opt
          and opt["eval_classifier_model_file"] is not None
      ), "You must provide --eval-classifier-model-file for ClassifierMetricTeacher."
      if not shared:
          self.classifier = create_agent_from_model_file(
              opt["eval_classifier_model_file"],
              opt_overrides={
                  "datatype": "valid",
                  "no_cuda": not opt["eval_classifier_use_cuda"],
              },
          )
          self.classifier.opt.log()
      else:
          logging.info("Load the classifier from shared")
          self.classifier = create_agent_from_shared(
              shared["classifier"]
          )
      self.context = []
      DEFAULT_DELIM = "\n"
      self.delimiter = opt.get("delimiter", DEFAULT_DELIM)
  
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 2 to create a new ClassifierMetricTeacher object from inherited base classes: bibifi with example: obj = ClassifierMetricTeacher(opt, shared)