code: def get_args():
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "--dataset_yaml",
          type=str,
          default="examples/pytorch/semantic_parsing/graph2seq/config/new_dependency_gat_bi_sep.yaml",
          help="",
      )
      # default="examples/pytorch/semantic_parsing/graph2seq/config/new_dynamic_refine.yaml", help="")
      # default = "examples/pytorch/semantic_parsing/graph2seq/config/new_dynamic.yaml", help = "")
  
      # default="examples/pytorch/semantic_parsing/graph2seq/config/new_constituency.yaml", help="")
  
      parser.add_argument(
          "--word-emb-size", type=int, default=300, help=""
      )
      parser.add_argument(
          "--log-file",
          type=str,
          default="examples/pytorch/semantic_parsing/graph2seq/log/ggnn.txt",
      )
      parser.add_argument(
          "--checkpoint-save-path",
          type=str,
          default="examples/pytorch/semantic_parsing/graph2seq/save",
      )
  
      parser.add_argument(
          "--learning-rate", type=float, default=1e-3, help=""
      )
      parser.add_argument(
          "--loss-display-step", type=int, default=3, help=" "
      )
      parser.add_argument(
          "--eval-display-number", type=int, default=3, help=""
      )
      parser.add_argument(
          "--lr-start-decay-epoch", type=int, default=20, help=""
      )
      parser.add_argument("--lr-decay-rate", type=float, default=0.9)
      parser.add_argument(
          "--lr-decay-per-epoch", type=int, default=5, help=""
      )
      parser.add_argument("--min-lr", type=float, default=1e-3, help="")
      parser.add_argument(
          "--use-gpu",
          type=float,
          default=1,
          help="0 for don't use cuda, 1 for using cuda",
      )
      parser.add_argument(
          "--num_works",
          type=int,
          default=0,
          help="The number of works for Dataloader.",
      )
      parser.add_argument("--gpu", type=int, default=0, help="gpu id")
      parser.add_argument("--seed", type=int, default=1236, help="")
  
      # dataset config
      parser.add_argument(
          "--batch_size",
          type=int,
          default=24,
          help="the size of one mini-batch",
      )
      parser.add_argument(
          "--share-vocab",
          type=bool,
          default=True,
          help="whether to share vocab",
      )
      parser.add_argument(
          "--val_split_ratio", type=float, default=0, help=""
      )
  
      parser.add_argument(
          "--pretrained_word_emb_name", type=str, default="6B", help=""
      )
      parser.add_argument(
          "--pretrained_word_emb_url", type=str, default=None, help=""
      )
      parser.add_argument(
          "--pretrained_word_emb_cache_dir",
          type=str,
          default=".vector_cache",
          help="",
      )
  
      parser.add_argument(
          "--beam-size",
          type=int,
          default=4,
          help="the beam size of beam search",
      )
  
      cfg = parser.parse_args()
  
      our_args = get_yaml_config(cfg.dataset_yaml)
      template = get_basic_args(
          graph_construction_name=our_args["graph_construction_name"],
          graph_embedding_name=our_args["graph_embedding_name"],
          decoder_name=our_args["decoder_name"],
      )
      update_values(
          to_args=template, from_args_list=[our_args, vars(cfg)]
      )
      return template
  
label_desc: Use image node_id 1 for calling a global function with example usage: get_args() and returns: template