code: def run_benchmark():
      if is_workflow(execution_params["url"]):
          execution_params[
              "inference_model_url"
          ] = "wfpredict/benchmark"
  
      click.secho(
          "\n\nExecuting inference performance tests ...", fg="green"
      )
      ab_cmd = (
          f"ab -c {execution_params['concurrency']} -s 300 -n {execution_params['requests']} -k -p "
          f"{execution_params['tmp_dir']}/benchmark/input -T  {execution_params['content_type']} "
          f"{execution_params['inference_url']}/{execution_params['inference_model_url']} > "
          f"{execution_params['result_file']}"
      )
      execute(ab_cmd, wait=True)
  
      unregister_model()
      stop_torchserve()
  
imports: import csv
  import json
  import os
  import re
  import shutil
  import sys
  import tempfile
  import time
  from subprocess import PIPE, Popen
  from urllib.parse import urlparse
  import click
  import click_config_file
  import matplotlib.pyplot
  import numpy
  import pandas
  import requests
label_desc: Use image node_id 5 for calling a global function with example usage: run_benchmark() without return types