code: def add_tuning_args(parser):
      group = parser.add_argument_group("Tuning")
  
      group.add_argument(
          "--lower-bound",
          default=[-0.7],
          nargs="+",
          type=float,
          help="lower bound of search space",
      )
      group.add_argument(
          "--upper-bound",
          default=[3],
          nargs="+",
          type=float,
          help="upper bound of search space",
      )
      group.add_argument(
          "--tune-param",
          default=["lenpen"],
          nargs="+",
          choices=["lenpen", "weight1", "weight2", "weight3"],
          help="the parameter(s) to tune",
      )
      group.add_argument(
          "--tune-subset",
          default="valid",
          choices=["valid", "test", "train"],
          help="the subset to tune on ",
      )
      group.add_argument(
          "--num-trials",
          default=1000,
          type=int,
          help="number of trials to do for random search",
      )
      group.add_argument(
          "--share-weights",
          action="store_true",
          help="share weight2 and weight 3",
      )
      return group
  
imports: from fairseq import options
label_desc: Use image node_id 4 for calling a global function with example usage: add_tuning_args(parser) and returns: group