code: def add_cmdline_args(
      cls, parser: ParlaiParser, partial_opt: Optional[Opt] = None
  ) -> ParlaiParser:
      super().add_cmdline_args(parser, partial_opt)
      agent = parser.add_argument_group("LIGHT Dialogue options")
      agent.add_argument(
          "--light_use_repeat",
          type=str,
          default="none",
          choices=["self_last", "partner_last", "none", "both_last"],
      )
      agent.add_argument(
          "--light_use_taskname", type="bool", default=True
      )
      agent.add_argument(
          "--light_use_setting", type="bool", default=True
      )
      agent.add_argument(
          "--light_use_unseen_test", type="bool", default=False
      )
      agent.add_argument(
          "--light_use_person_names", type="bool", default=True
      )
      agent.add_argument(
          "--light_use_persona",
          type=str,
          default="self",
          choices=["partner", "self", "all", "none"],
      )
      agent.add_argument(
          "--light_use_emote",
          type=str,
          default="none",
          choices=["partner", "self", "all", "none"],
      )
      agent.add_argument(
          "--light_use_speech",
          type=str,
          default="partner",
          choices=["partner", "self", "all", "none"],
      )
      agent.add_argument(
          "--light_use_action",
          type=str,
          default="none",
          choices=["partner", "self", "all", "none"],
      )
      agent.add_argument(
          "--light_use_affordances", type="bool", default=False
      )
      agent.add_argument(
          "--light_use_current_self_output",
          type=str,
          default="none",
          choices=[
              "none",
              "all",
              "all_filtered",
              "all_filtered_remove",
          ],
      )
      agent.add_argument(
          "--light_label_type",
          type=str,
          default="speech",
          choices=["speech", "action", "emote"],
          help="type of target in light dialogues",
      )
      agent.add_argument("--light_use_cands", type=int, default=20)
      agent.add_argument(
          "--light_use_clip_cands", type=int, default=10000
      )
      agent.add_argument(
          "--light_use_speech_prefix", type="bool", default=False
      )
      agent.add_argument(
          "--light_use_score_cutoff", type=int, default=1
      )
      agent.add_argument(
          "--light_use_max_score_cutoff", type=int, default=-1
      )
      agent.add_argument(
          "--light_use_hard_score_cutoff",
          type="bool",
          default=False,
          help="Specify True to **only** include examples with the specified "
          "score cutoff. E.g., if `--light-use-score-cutoff 3`, will only "
          "supply dialogues with scores of 3.",
      )
      agent.add_argument(
          "--light-model-name",
          type=str,
          default=None,
          help="if specified, the model from which chats should be saved",
      )
      agent.add_argument(
          "--light-use-continue-type",
          type=str,
          default="all",
          choices=["all", "continue", "exit"],
          help="only use dialogues that had a specific continue outcome, default use all",
      )
      agent.add_argument(
          "--light-use-date-cutoff",
          type=str,
          default=None,
          help=(
              "If specified, only include hobbot conversations that were collected "
              "before this date. Format YYYY-MM-DD."
          ),
      )
      agent.add_argument(
          "--light-use-person-names-prefix",
          type="bool",
          default=False,
          help="If specified, prefix text with character name",
      )
      agent.add_argument(
          "--light_percent_train_exs", type=float, default=1.0
      )
      return parser
  
imports: from typing import Optional
  from parlai.core.params import ParlaiParser
  from parlai.core.opt import Opt
  from parlai.core.teachers import ParlAIDialogTeacher
  from .build import build, get_fpath
  import copy
  import os
  import random
label_desc: Use image node_id 1 for calling the SimpleTeacher obj's underlying member method code with example usage: obj.add_cmdline_args(cls, parser, partial_opt) and returns: parser