code: def arg_parse():
      parser = argparse.ArgumentParser(
          description="Pagerank arguments."
      )
      parser.add_argument(
          "--device", type=str, help="CPU / GPU device."
      )
      parser.add_argument(
          "--netlib",
          type=str,
          help="Backend network library, nx or sx.",
      )
      parser.add_argument("--batch_size", type=int, help="Batch size.")
      parser.add_argument(
          "--num_runs", type=int, help="Number of runs averaged on."
      )
      parser.add_argument("--dataset", type=str, help="Dataset.")
      parser.add_argument(
          "--print_run",
          action="store_true",
          help="Print out current run.",
      )
      parser.add_argument(
          "--bench_task", type=str, help="Either page or cluster."
      )
  
      parser.set_defaults(
          device="cuda:0",
          netlib="nx",
          batch_size=1,
          num_runs=100,
          dataset="COX2",
          print_run=False,
          bench_task="page",
      )
      return parser.parse_args()
  
file_path: deepsnap/benchmark/transform/pagerank_clustering.py
imports: import time
  import torch
  import argparse
  import deepsnap
  import numpy
  from deepsnap.dataset import GraphDataset
  from torch_geometric.datasets import TUDataset
label_desc: Use image node_id 1 for calling a global function with example usage: arg_parse() and returns: parser