code: def argument():
      parser = argparse.ArgumentParser(description="InfoGraphS")
  
      # data source params
      parser.add_argument(
          "--target",
          type=str,
          default="mu",
          help="Choose regression task",
      )
      parser.add_argument(
          "--train_num",
          type=int,
          default=5000,
          help="Size of training set",
      )
  
      # training params
      parser.add_argument(
          "--gpu",
          type=int,
          default=-1,
          help="GPU index, default:-1, using CPU.",
      )
      parser.add_argument(
          "--epochs", type=int, default=200, help="Training epochs."
      )
      parser.add_argument(
          "--batch_size",
          type=int,
          default=20,
          help="Training batch size.",
      )
      parser.add_argument(
          "--val_batch_size",
          type=int,
          default=100,
          help="Validation batch size.",
      )
  
      parser.add_argument(
          "--lr", type=float, default=0.001, help="Learning rate."
      )
      parser.add_argument(
          "--wd", type=float, default=0, help="Weight decay."
      )
  
      # model params
      parser.add_argument(
          "--hid_dim",
          type=int,
          default=64,
          help="Hidden layer dimensionality",
      )
      parser.add_argument(
          "--reg",
          type=float,
          default=0.001,
          help="Regularization coefficient",
      )
  
      args = parser.parse_args()
  
      # check cuda
      if args.gpu != -1 and th.cuda.is_available():
          args.device = "cuda:{}".format(args.gpu)
      else:
          args.device = "cpu"
  
      return args
  
file_path: dgl/examples/pytorch/infograph/semisupervised.py
imports: import argparse
  import dgl
  import numpy
  import torch
  import torch.nn.functional
  from dgl.data import QM9EdgeDataset
  from dgl.data.utils import Subset
  from dgl.dataloading import GraphDataLoader
  from model import InfoGraphS
label_desc: Use image node_id 1 for calling a global function with example usage: argument() and returns: args