code: def run_one(total_actors, cpus_per_actor, no_wait):
      total_cpus = cpus_per_actor * total_actors + psutil.cpu_count()
      total_cpus = int(math.ceil(total_cpus))
      scale_cluster_up(total_cpus)
  
      actor_launch_start = perf_counter()
      actors = test_max_actors_launch(cpus_per_actor, total_actors)
      actor_launch_end = perf_counter()
      actor_launch_time = actor_launch_end - actor_launch_start
      actor_ready_start = perf_counter()
      total_actors = len(actors)
      objs = [actor.foo.remote() for actor in actors]
  
      while len(objs) != 0:
          timeout = None if no_wait else 30
          objs_ready, objs = ray.wait(
              objs, num_returns=len(objs), timeout=timeout
          )
          print(
              f"Status: {total_actors - len(objs)}/{total_actors}, "
              f"{perf_counter() - actor_ready_start}"
          )
      actor_ready_end = perf_counter()
      actor_ready_time = actor_ready_end - actor_ready_start
  
      throughput = total_actors / (actor_ready_time + actor_launch_time)
      print(
          f"Actor launch time: {actor_launch_time} ({total_actors} actors)"
      )
      print(
          f"Actor ready time: {actor_ready_time} ({total_actors} actors)"
      )
      print(
          f"Total time: {actor_launch_time + actor_ready_time}"
          f" ({total_actors} actors)"
      )
      print(f"Through put: {throughput}")
  
      return {
          "actor_launch_time": actor_launch_time,
          "actor_ready_time": actor_ready_time,
          "total_time": actor_launch_time + actor_ready_time,
          "num_actors": total_actors,
          "success": "1",
          "throughput": throughput,
      }
  
file_path: ray/release/benchmarks/distributed/many_nodes_tests/actor_test.py
imports: import argparse
  import os
  import math
  from time import sleep, perf_counter
  import json
  import ray
  import psutil
label_desc: Use image node_id 4 for calling a global function with example usage: run_one(total_actors, cpus_per_actor, no_wait) and returns: dict