code: def parse_args():
      parser = argparse.ArgumentParser(description="Run NGCF.")
      parser.add_argument(
          "--weights_path",
          nargs="?",
          default="model/",
          help="Store model path.",
      )
      parser.add_argument(
          "--data_path",
          nargs="?",
          default="../Data/",
          help="Input data path.",
      )
      parser.add_argument(
          "--model_name",
          type=str,
          default="NGCF.pkl",
          help="Saved model name.",
      )
  
      parser.add_argument(
          "--dataset",
          nargs="?",
          default="gowalla",
          help="Choose a dataset from {gowalla, yelp2018, amazon-book}",
      )
      parser.add_argument(
          "--verbose",
          type=int,
          default=1,
          help="Interval of evaluation.",
      )
      parser.add_argument(
          "--epoch", type=int, default=400, help="Number of epoch."
      )
  
      parser.add_argument(
          "--embed_size", type=int, default=64, help="Embedding size."
      )
      parser.add_argument(
          "--layer_size",
          nargs="?",
          default="[64,64,64]",
          help="Output sizes of every layer",
      )
      parser.add_argument(
          "--batch_size", type=int, default=1024, help="Batch size."
      )
  
      parser.add_argument(
          "--regs", nargs="?", default="[1e-5]", help="Regularizations."
      )
      parser.add_argument(
          "--lr", type=float, default=0.0001, help="Learning rate."
      )
  
      parser.add_argument(
          "--gpu",
          type=int,
          default=0,
          help="0 for NAIS_prod, 1 for NAIS_concat",
      )
  
      parser.add_argument(
          "--mess_dropout",
          nargs="?",
          default="[0.1,0.1,0.1]",
          help="Keep probability w.r.t. message dropout (i.e., 1-dropout_ratio) for each deep layer. 1: no dropout.",
      )
  
      parser.add_argument(
          "--Ks",
          nargs="?",
          default="[20, 40]",
          help="Output sizes of every layer",
      )
  
      parser.add_argument(
          "--save_flag",
          type=int,
          default=1,
          help="0: Disable model saver, 1: Activate model saver",
      )
  
      parser.add_argument(
          "--test_flag",
          nargs="?",
          default="part",
          help="Specify the test type from {part, full}, indicating whether the reference is done in mini-batch",
      )
  
      parser.add_argument(
          "--report",
          type=int,
          default=0,
          help="0: Disable performance report w.r.t. sparsity levels, 1: Show performance report w.r.t. sparsity levels",
      )
      return parser.parse_args()
  
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: parser