class_docstr: Model described in (https://arxiv.org/abs/1811.00945).
  
  A model for producing engaging captions about an image. Given an image and
  this model will attempt to predict an appropriate
  next utterance in the dialog, in the context of a given personality.
  
  See the paper linked above for more information.
class_docstr_tok: ["Model","described","in","(","https",":","\/\/arxiv.org\/abs\/1811.00945",")",".","A","model","for","producing","engaging","captions","about","an","image",".","Given","an","image","and","this","model","will","attempt","to","predict","an","appropriate","next","utterance","in","the","dialog",",","in","the","context","of","a","given","personality",".","See","the","paper","linked","above","for","more","information","."]
docstr: Add command line args.
docstr_tok: ["Add","command","line","args","."]
code: def add_cmdline_args(
      cls, parser: ParlaiParser, partial_opt: Optional[Opt] = None
  ) -> ParlaiParser:
      """
      Add command line args.
      """
      arg_group = parser.add_argument_group("Transresnet Arguments")
      TransresnetModel.add_cmdline_args(parser, partial_opt=partial_opt)
      parser.add_argument(
          "--freeze-patience",
          type=int,
          default=-1,
          help="How long to freeze text encoders",
      )
      parser.add_argument(
          "--one-cand-set",
          type="bool",
          default=False,
          help="True if each example has one set of shared "
          "label candidates",
      )
      parser.add_argument(
          "--fixed-cands-path",
          type=str,
          default=None,
          help="path to text file with candidates",
      )
      parser.add_argument(
          "--pretrained",
          type="bool",
          default=False,
          help="True if pretrained model",
      )
      cls.dictionary_class().add_cmdline_args(
          parser, partial_opt=partial_opt
      )
      return arg_group
  
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.core.dict import DictionaryAgent
  from parlai.utils.misc import round_sigfigs
  from .modules import TransresnetModel
  from parlai.tasks.personality_captions.build import build
  from parlai.utils.io import PathManager
  import parlai.utils.torch
  import os
  import random
  import json
  import numpy
  import torch
  import tqdm
label_desc: Use image node_id 1 for calling the TransresnetAgent obj's underlying member method code with example usage: obj.add_cmdline_args(cls, parser, partial_opt) and returns: arg_group