code: def run_autotuning(args, active_resources):
      tuner = Autotuner(args, active_resources)
      logger.info("[Start] Running autotuning")
  
      tuner.tune()
      tuner.print_tuning_results()
  
      logger.info("[End] Running autotuning")
      tuner.write_optimal_config()
  
      if args.autotuning == "run":
          tuner.run_after_tuning()
  
imports: import os
  import sys
  import json
  import base64
  import argparse
  import subprocess
  import collections
  from copy import deepcopy
  import signal
  import time
  import torch.cuda
  from .multinode_runner import PDSHRunner, OpenMPIRunner, MVAPICHRunner, SlurmRunner
  from .constants import PDSH_LAUNCHER, OPENMPI_LAUNCHER, MVAPICH_LAUNCHER, SLURM_LAUNCHER
  from ..constants import TORCH_DISTRIBUTED_DEFAULT_PORT
  from ..nebula.constants import NEBULA_EXPORT_ENVS
  from ..utils import logger
  from ..autotuning import Autotuner
label_desc: Use image node_id 7 for calling a global function with example usage: run_autotuning(args, active_resources) without return types