code: def get_loss_landscape_args(args: Optional[List[str]] = None):
      parser = get_training_arguments(parse_args=False)
  
      group = parser.add_argument_group(
          "Loss landscape related arguments"
      )
      group.add_argument(
          "--loss-landscape.n-points",
          type=int,
          default=11,
          help="No. of grid points. Default is 11, so we have 11x11 grid",
      )
      group.add_argument(
          "--loss-landscape.min-x",
          type=float,
          default=-1.0,
          help="Min. value along x-axis",
      )
      group.add_argument(
          "--loss-landscape.max-x",
          type=float,
          default=1.0,
          help="Max. value along x-axis",
      )
      group.add_argument(
          "--loss-landscape.min-y",
          type=float,
          default=-1.0,
          help="Min. value along y-axis",
      )
      group.add_argument(
          "--loss-landscape.max-y",
          type=float,
          default=1.0,
          help="Max. value along y-axis",
      )
  
      # parse args
      return parser_to_opts(parser, args=args)
  
imports: import argparse
  from typing import List, Optional
  from common import SUPPORTED_MODALITIES
  from cvnets import modeling_arguments
  from data.collate_fns import arguments_collate_fn
  from data.datasets import arguments_dataset
  from data.sampler import add_sampler_arguments
  from data.text_tokenizer import arguments_tokenizer
  from data.transforms import arguments_augmentation
  from data.video_reader import arguments_video_reader
  from loss_fn import add_loss_fn_arguments
  from metrics import METRICS_REGISTRY, arguments_stats
  from optim import arguments_optimizer
  from optim.scheduler import arguments_scheduler
  from options.utils import load_config_file
  from utils import logger
label_desc: Use image node_id 8 for calling a global function with example usage: get_loss_landscape_args(args) and returns: parser_to_opts