code: def add_tune_args(parser):
      group = parser.add_argument_group("Tune parameter parser.")
      group.add_argument(
          "--n-grid",
          default=6,
          type=int,
          metavar="N",
          help="how many grid added to tune for each weight.",
      )
      group.add_argument(
          "--weight-lower-bound",
          default=0.0,
          type=float,
          help="lower bound for each weight.",
      )
      group.add_argument(
          "--weight-upper-bound",
          default=1.0,
          type=float,
          help="upper bound for each weight.",
      )
      group.add_argument(
          "--num-trails-ax-opt",
          default=5,
          type=int,
          help="number of trials in AX optimization.",
      )
      group.add_argument(
          "--output-json-best-parameters",
          default="best_parameters.json",
          type=str,
          help="name of output file for the best parameters.",
      )
      group.add_argument(
          "--output-json-best-value",
          default="best_value.json",
          type=str,
          help="name of output file for the best value of the evaluation function.",
      )
      return parser
  
imports: import json
  from ax.service.managed_loop import optimize
  from fairseq import options
  from pytorch_translate import generate
  from pytorch_translate.constants import CHECKPOINT_PATHS_DELIMITER
label_desc: Use image node_id 1 for calling a global function with example usage: add_tune_args(parser) and returns: parser