code: def run_single_benchmark(
      jmx, jmeter_args=dict(), threads=100, out_dir=None
  ):
      if out_dir is None:
          out_dir = os.path.join(
              OUT_DIR, benchmark_name, basename(benchmark_model)
          )
      if os.path.exists(out_dir):
          shutil.rmtree(out_dir)
      os.makedirs(out_dir)
  
      protocol = "http"
      hostname = "127.0.0.1"
      port = 8080
      threads = pargs.threads[0] if pargs.threads else threads
      workers = (
          pargs.workers[0]
          if pargs.workers
          else (
              pargs.gpus[0]
              if pargs.gpus
              else multiprocessing.cpu_count()
          )
      )
  
      if pargs.ts:
          url = pargs.ts[0]
          if "://" in url:
              protocol, url = url.split("://")
          if ":" in url:
              hostname, port = url.split(":")
              port = int(port)
          else:
              hostname = url
              port = 80
      else:
          # Start TorchServe
          docker = "nvidia-docker" if pargs.gpus else "docker"
          container = (
              "ts_benchmark_gpu" if pargs.gpus else "ts_benchmark_cpu"
          )
          docker_path = (
              "pytorch/torchserve:latest-gpu"
              if pargs.gpus
              else "pytorch/torchserve:latest"
          )
          if pargs.docker:
              s_pargs_docker = "".join(
                  [str(elem) for elem in pargs.docker]
              )
              if "/" in s_pargs_docker:
                  # Fixed the logic to get the container name correctly
                  container = "ts_benchmark_{}".format(
                      pargs.docker[0].split("/")[-1].split(":")[0]
                  )
                  docker_path = pargs.docker[0]
              else:
                  container = "ts_benchmark_{}".format(
                      pargs.docker[0].split(":")[1]
                  )
                  docker_path = pargs.docker
          docker_path = "".join([str(elem) for elem in docker_path])
          run_process("{} rm -f {}".format(docker, container))
          docker_run_call = "{} run --name {} -p 8080:8080 -p 8081:8081 -itd {}".format(
              docker, container, docker_path
          )
          retval = run_process(docker_run_call).returncode
          if retval != 0:
              raise Exception(
                  "docker run command failed!! Please provide a valid docker image"
              )
  
      management_port = (
          int(pargs.management[0]) if pargs.management else port + 1
      )
      time.sleep(30)
  
      try:
          # temp files
          tmpfile = os.path.join(out_dir, "output.jtl")
          logfile = os.path.join(out_dir, "jmeter.log")
          outfile = os.path.join(out_dir, "out.csv")
          perfmon_file = os.path.join(out_dir, "perfmon.csv")
          graphsDir = os.path.join(out_dir, "graphs")
          reportDir = os.path.join(out_dir, "report")
  
          # run jmeter
          run_jmeter_args = {
              "hostname": hostname,
              "port": port,
              "management_port": management_port,
              "protocol": protocol,
              "min_workers": workers,
              "rampup": 5,
              "threads": threads,
              "loops": int(pargs.loops[0]),
              "perfmon_file": perfmon_file,
          }
          run_jmeter_args.update(JMETER_RESULT_SETTINGS)
          run_jmeter_args.update(jmeter_args)
          run_jmeter_args.update(
              dict(zip(pargs.options[::2], pargs.options[1::2]))
          )
          abs_jmx = (
              jmx if os.path.isabs(jmx) else os.path.join(JMX_BASE, jmx)
          )
          jmeter_args_str = " ".join(
              sorted(
                  [
                      "-J{}={}".format(key, val)
                      for key, val in run_jmeter_args.items()
                  ]
              )
          )
          jmeter_call = "{} -n -t {} {} -l {} -j {} -e -o {}".format(
              JMETER,
              abs_jmx,
              jmeter_args_str,
              tmpfile,
              logfile,
              reportDir,
          )
          run_process(jmeter_call)
          print("Processing jmeter output")
          time.sleep(30)
          # run AggregateReport
          ag_call = "java -jar {} --tool Reporter --generate-csv {} --input-jtl {} --plugin-type AggregateReport".format(
              CMDRUNNER, outfile, tmpfile
          )
          if PLATFORM == "Windows":
              run_process(ag_call, shell=True)
          else:
              run_process(ag_call)
  
          # Generate output graphs
          gLogfile = os.path.join(out_dir, "graph_jmeter.log")
          graphing_args = {
              "raw_output": graphsDir,
              "jtl_input": tmpfile,
          }
          graphing_args.update(JMETER_RESULT_SETTINGS)
          gjmx = os.path.join(JMX_BASE, JMX_GRAPHS_GENERATOR_PLAN)
          graphing_args_str = " ".join(
              [
                  "-J{}={}".format(key, val)
                  for key, val in graphing_args.items()
              ]
          )
          graphing_call = "{} -n -t {} {} -j {}".format(
              JMETER, gjmx, graphing_args_str, gLogfile
          )
          run_process(graphing_call)
  
          print("Output available at {}".format(out_dir))
          print(
              "Report generated at {}".format(
                  os.path.join(reportDir, "index.html")
              )
          )
  
          data_frame = pd.read_csv(outfile, index_col=0)
          report = list()
          for val in EXPERIMENT_RESULTS_MAP[jmx]:
              for full_val in [
                  fv for fv in data_frame.index if val in fv
              ]:
                  report.append(decorate_metrics(data_frame, full_val))
  
          return report
  
      except Exception:  # pylint: disable=broad-except
          traceback.print_exc()
  
imports: import argparse
  import itertools
  import multiprocessing
  import os
  import pprint
  import shutil
  import subprocess
  import sys
  import time
  import traceback
  from functools import reduce
  from urllib.request import urlretrieve
  import tempfile
  import platform
  import pandas
label_desc: Use image node_id 6 for calling a global function with example usage: run_single_benchmark(jmx, jmeter_args, threads, out_dir) and returns: report