code: def ray_instance(request):
      """Starts and stops a Ray instance for this test.
  
      Args:
          request: request.param should contain a dictionary of env vars and
              their values. The Ray instance will be started with these env vars.
      """
  
      original_env_vars = os.environ.copy()
  
      try:
          requested_env_vars = request.param
      except AttributeError:
          requested_env_vars = {}
  
      os.environ.update(requested_env_vars)
  
      yield ray.init(
          _metrics_export_port=9999,
          _system_config={
              "metrics_report_interval_ms": 1000,
              "task_retry_delay_ms": 50,
          },
      )
  
      ray.shutdown()
  
      os.environ.clear()
      os.environ.update(original_env_vars)
  
imports: import os
  import random
  import subprocess
  import tempfile
  import pytest
  import requests
  import ray
  from ray import serve
  from ray._private.test_utils import wait_for_condition
  from ray._private.usage import usage_lib
  from ray.cluster_utils import AutoscalingCluster, Cluster
  from ray.serve._private import api
  from ray.serve._private.test_utils import TELEMETRY_ROUTE_PREFIX, check_ray_stopped
  from ray.serve.context import _get_global_client
  from ray.tests.conftest import propagate_logs, pytest_runtest_makereport
label_desc: Use image node_id 10 for calling a global function with example usage: ray_instance(request) without return types