code: def add_cmdline_args(
      cls, parser: ParlaiParser, partial_opt: Optional[Opt] = None
  ) -> ParlaiParser:
      super().add_cmdline_args(parser, partial_opt=partial_opt)
      parser.add_argument(
          "--eval-classifier-model-file",
          required=False,
          type=str,
          help="Filepath for evaluation classifier to evaluate the model generation.",
      )
      parser.add_argument(
          "--include-label-cand-only",
          type="bool",
          default=True,
          help="When passing inputs to the classifier, use only the label targets if set to True.",
      )
      parser.add_argument(
          "--truncate-prediction-at",
          type=int,
          default=-1,
          help="Truncate the prediction of the model after n words before feeding it to the classifier.",
      )
      parser.add_argument(
          "--limit-classifier-examples-at",
          type=int,
          default=-1,
          help="Limit the amount of classifier examples (used during training).",
      )
      parser.add_argument(
          "--eval-classifier-use-cuda",
          type=bool,
          default=False,
          help="Use the gpu for the eval classifier. This does not work during distributed training.",
      )
      return parser
  
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 ClassifierMetricTeacher obj's underlying member method code with example usage: obj.add_cmdline_args(cls, parser, partial_opt) and returns: parser