docstr: Add criterion-specific arguments to the parser.
docstr_tok: ["Add","criterion-specific","arguments","to","the","parser","."]
code: def add_args(parser):
      """Add criterion-specific arguments to the parser."""
      rescore_add_args(parser)
      parser.add_argument(
          "--rl-weight",
          type=float,
          default=0.1,
          help="trade-off coefficient of rl loss",
      )
      parser.add_argument(
          "--rl-num-trajectory",
          type=int,
          default=3,
          help="num trajectory in rl training",
      )
      parser.add_argument(
          "--topk-words",
          type=int,
          default=8,
          help="match topk words at each time step",
      )
      parser.add_argument(
          "--word-weight",
          type=float,
          default=1.0,
          help="weight for word level",
      )
      parser.add_argument(
          "--word-model",
          type=str,
          default="cloze_model",
          help="word-level teacher model",
      )
  
file_path: translate/pytorch_translate/research/rescore/rescoring_criterion.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import math
  import torch
  from fairseq import utils
  from fairseq.criterions import LegacyFairseqCriterion, register_criterion
  from pytorch_translate import generate, utils
  from pytorch_translate.rescoring.model_scorers import SimpleModelScorer
  from pytorch_translate.rescoring.rescorer import add_args, combine_weighted_scores, Rescorer
label_desc: Use image node_id 2 for calling the RescoringCriterion obj's underlying member method code with example usage: obj.add_args(parser) without return types