class_docstr: TransformerGeneratorAgent.
  
  Implementation of TorchGeneratorAgent, where the model is a Transformer
class_docstr_tok: ["TransformerGeneratorAgent",".","Implementation","of","TorchGeneratorAgent",",","where","the","model","is","a","Transformer"]
docstr: Add command-line arguments specifically for this agent.
docstr_tok: ["Add","command-line","arguments","specifically","for","this","agent","."]
code: def add_cmdline_args(
      cls, parser: ParlaiParser, partial_opt: Optional[Opt] = None
  ) -> ParlaiParser:
      """
      Add command-line arguments specifically for this agent.
      """
      agent = parser.add_argument_group("Transformer Arguments")
      add_common_cmdline_args(agent)
      cls.dictionary_class().add_cmdline_args(
          parser, partial_opt=partial_opt
      )
  
      super().add_cmdline_args(parser, partial_opt=partial_opt)
      return agent
  
imports: from typing import Optional
  from parlai.core.params import ParlaiParser
  from parlai.core.opt import Opt
  from parlai.core.agents import Agent
  from parlai.utils.torch import padded_3d
  from parlai.core.torch_classifier_agent import TorchClassifierAgent
  from parlai.core.torch_ranker_agent import TorchRankerAgent
  from parlai.core.torch_generator_agent import TorchGeneratorAgent
  from parlai.utils.misc import recursive_getattr, warn_once
  from parlai.utils.logging import logging
  from parlai.utils.fsdp import should_use_fsdp
  from .modules import TransformerMemNetModel, TransformerGeneratorModel, TransformerLinearWrapper
  import torch
label_desc: Use image node_id 1 for calling the TransformerGeneratorAgent obj's underlying member method code with example usage: obj.add_cmdline_args(cls, parser, partial_opt) and returns: agent