code: def add_cmdline_args(
      cls, parser: ParlaiParser, partial_opt: Optional[Opt] = None
  ) -> ParlaiParser:
      TransformerGeneratorAgent.add_cmdline_args(
          parser, partial_opt=partial_opt
      )
      # This method will add arguments specific to fused classifier architecture
      # like num_layers classifier, etc.
      group = parser.add_argument_group("Director Group")
      group.add_argument(
          "--explicit-classifier-norm",
          type=bool,
          default=False,
          help="If we should explictly try to set non-target tokens to 0.5 during training.",
      )
      group.add_argument(
          "--explicit-classifier-norm-coeff",
          type=float,
          default=1,
          help="If we should explictly try to set non-target tokens to 0.5 during training.",
      )
      group.add_argument(
          "--freeze-decoder",
          type=bool,
          default=False,
          help="Freeze decoder for training only classifier head.",
      )
      group.add_argument(
          "--train-gamma",
          type=float,
          default=0.5,
          help="Implementing Sainaa's suggestion of keeping generator weight fixed (to 1) and "
          "using \alpha (hopefully <1) to weight classifier.",
      )
      group.add_argument(
          "--infer-gamma",
          type=float,
          default=None,
          help="Implementing Sainaa's suggestion of keeping generator weight fixed (to 1) and "
          "using \alpha (hopefully <1) to weight classifier.",
      )
      group.add_argument(
          "--train-generator-with-pos-feedback-examples",
          type=bool,
          default=False,
          help="Train the generation head with the positive examples from the feedback data.",
      )
      group.add_argument(
          "--director-use-shared-embedding",
          type=bool,
          default=False,
          help="Use a shared final embedding for the generator and classifier head of the director.",
      )
      return parser
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from typing import Optional, Any, Dict, Tuple, Union
  from parlai.agents.transformer.modules import TransformerGeneratorModel
  from parlai.agents.transformer.transformer import TransformerGeneratorAgent
  from parlai.core.dict import DictionaryAgent
  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.core.torch_generator_agent import PPLMetric
  import parlai.utils.logging
label_desc: Use image node_id 1 for calling the DirectorAgent obj's underlying member method code with example usage: obj.add_cmdline_args(cls, parser, partial_opt) and returns: parser