class_docstr: This teacher examines model responses and classifies whether the model responded as
  the correct character.
  
  Evaluation is entirely dependent on the classifier specified.
class_docstr_tok: ["This","teacher","examines","model","responses","and","classifies","whether","the","model","responded","as","the","correct","character",".","Evaluation","is","entirely","dependent","on","the","classifier","specified","."]
code: def __init__(self, opt, shared=None):
      from projects.light_whoami.agents.rpa_rerank import RPAReranker
  
      assert opt.get("predictor_model_file") and os.path.exists(
          modelzoo_path(opt["datapath"], opt["predictor_model_file"])
      ), f"must specify a proper RPA predictor to use this teacher, file path invalid: {opt['predictor_model_file']}"
  
      if not shared:
          self.classifier = RPAReranker(opt)
      else:
          self.classifier = shared["classifier"]
      self.context = []
      self.delimiter = opt.get("delimiter", DEFAULT_DELIM)
  
      super().__init__(opt, shared)
  
imports: from abc import ABC
  from collections import deque
  import re
  from typing import Optional
  from parlai.core.build_data import modelzoo_path
  from parlai.core.message import Message
  from parlai.core.metrics import AverageMetric
  from parlai.core.opt import Opt
  from parlai.core.params import ParlaiParser
  from parlai.tasks.light_dialog.agents import SimpleMultiTeacher
  from parlai.utils.data import DatatypeHelper
  import parlai.utils.logging
  import copy
  import os
  import random
  import torch
  import torch.nn
  import torch.nn.functional
  from typing import List, Dict, Tuple
  from projects.light_whoami.task.utils import DEFAULT_DELIM, CONTEXT_KEYS, extract_characters, WHO_AM_I, WHO_ARE_YOU, SELF, PARTNER, WHO_IS_THIS, maybe_annotate
  import projects.light_whoami.task.mutators
label_desc: Use image node_id 2 to create a new ResponseClassifierTeacher object from inherited base classes: SimpleMultiTeacher with example: obj = ResponseClassifierTeacher(opt, shared)