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(
          "--output-file-name",
          default="output.csv",
          type=str,
          help="name of output file.",
      )
      return parser
  
imports: import itertools
  import numpy
  import pandas
  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