code: def parse_args():
      parser = argparse.ArgumentParser(
          description="Benchmark for OpenML pipelines"
      )
      parser.add_argument(
          "-pipedir",
          default=os.path.join(
              ROOT_PATH, "benchmarks/pipelines/openml-cc18/"
          ),
          type=str,
          help=("The root folder containing all pipelines"),
      )
      parser.add_argument(
          "-backend",
          default="torch",
          type=str,
          help=(
              "Comma-separated list of Hummingbird's backends to run"
          ),
      )
      parser.add_argument(
          "-gpu",
          default=False,
          action="store_true",
          help=("Whether to run scoring on GPU or not"),
      )
      parser.add_argument(
          "-output",
          default=None,
          type=str,
          help="Output json file with runtime stats",
      )
      parser.add_argument(
          "-niters",
          default=5,
          type=int,
          help=("Number of iterations for each experiment"),
      )
      parser.add_argument(
          "-validate",
          default=False,
          help="Validate prediction output and fails accordigly.",
      )
  
      args = parser.parse_args()
      # default value for output json file
      if not args.output:
          args.output = "result-{}.json".format(
              "gpu" if args.gpu else "cpu"
          )
      return args
  
imports: import os
  import sys
  import argparse
  import json
  import ast
  import psutil
  from pathlib import Path
  import signal
  import time
  import numpy
  import sklearn
  import joblib
  import torch
  from scipy import stats
  import gc
  import benchmarks.pipelines.score
  from benchmarks.timer import Timer
label_desc: Use image node_id 5 for calling a global function with example usage: parse_args() and returns: args