code: def main():
      args, unknown = parse_script_args()
  
      ray.init(address="auto")
  
      actor_launch_start = perf_counter()
      actors = test_max_actors_launch(
          args.cpus_per_actor, args.total_actors, args.num_masters
      )
      actor_launch_end = perf_counter()
      actor_launch_time = actor_launch_end - actor_launch_start
      if args.fail:
          sleep(10)
          return
      actor_ready_start = perf_counter()
      test_actor_ready(actors)
      actor_ready_end = perf_counter()
      actor_ready_time = actor_ready_end - actor_ready_start
  
      print(
          f"Actor launch time: {actor_launch_time} ({args.total_actors} actors)"
      )
      print(
          f"Actor ready time: {actor_ready_time} ({args.total_actors} actors)"
      )
      print(
          f"Total time: {actor_launch_time + actor_ready_time}"
          f" ({args.total_actors} actors)"
      )
  
      if "TEST_OUTPUT_JSON" in os.environ and not args.no_report:
          out_file = open(os.environ["TEST_OUTPUT_JSON"], "w")
          results = {
              "actor_launch_time": actor_launch_time,
              "actor_ready_time": actor_ready_time,
              "total_time": actor_launch_time + actor_ready_time,
              "num_actors": args.total_actors,
              "success": "1",
          }
          json.dump(results, out_file)
  
file_path: ray/release/benchmarks/distributed/many_nodes_tests/multi_master_test.py
imports: import argparse
  import os
  from time import sleep, perf_counter
  import json
  import ray
label_desc: Use image node_id 4 for calling a global function with example usage: main() without return types