code: def benchmark_tasks_and_get_batch(ray, results):
      @ray.remote
      def small_value():
          return b"ok"
  
      def small_value_batch():
          submitted = [small_value.remote() for _ in range(1000)]
          ray.get(submitted)
          return 0
  
      results += timeit(
          "client: tasks and get batch", small_value_batch
      )
  
file_path: ray/python/ray/_private/ray_client_microbenchmark.py
imports: import inspect
  import logging
  import numpy
  import sys
  from ray.util.client.ray_client_helpers import ray_start_client_server
  from ray._private.ray_microbenchmark_helpers import timeit
label_desc: Use image node_id 2 for calling a global function with example usage: benchmark_tasks_and_get_batch(ray, results) and returns: bytes, int