code: def main():
      """Submits custom resource request.
  
      Also, validates runtime env data submitted with the Ray Job that executes
      this script.
      """
      # The next two lines validate the runtime env in which this code runs.
      # (See the function ray_job_submit() in tests/kuberay/utils.py)
      assert pytest.__version__ == "6.0.0"
      assert os.getenv("key_foo") == "value_bar"
  
      # Workers and head are annotated as having 5 "Custom2" capacity each,
      # so this should trigger upscaling of two workers.
      # (One of the bundles will be "placed" on the head.)
      ray.autoscaler.sdk.request_resources(
          bundles=[{"Custom2": 3}, {"Custom2": 3}, {"Custom2": 3}]
      )
  
      while (
          ray.cluster_resources().get("Custom2", 0) < 3
          and ray.cluster_resources().get("Custom2", 0) < 6
      ):
          time.sleep(0.1)
  
      # Output something to validate the job logs.
      print("Submitted custom scale request!")
  
imports: import os
  import pytest
  import ray
  import time
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types