class_docstr: Produces an autoscaling config by reading data from the RayCluster CR.
  
  Used to fetch the autoscaling config at the beginning of each autoscaler iteration.
  
  In the context of Ray deployment on Kubernetes, the autoscaling config is an
  internal interface.
  
  The autoscaling config carries the strict subset of RayCluster CR data required by
  the autoscaler to make scaling decisions; in particular, the autoscaling config does
  not carry pod configuration data.
  
  This class is the only public object in this file.
code: def __call__(self):
      ray_cr = self._fetch_ray_cr_from_k8s_with_retries()
      autoscaling_config = _derive_autoscaling_config_from_ray_cr(
          ray_cr
      )
      return autoscaling_config
  
imports: import decimal
  import json
  import logging
  import time
  from typing import Any, Dict, Optional
  import requests
  from ray.autoscaler._private.constants import DISABLE_LAUNCH_CONFIG_CHECK_KEY, DISABLE_NODE_UPDATERS_KEY, FOREGROUND_NODE_LAUNCH_KEY, WORKER_LIVENESS_CHECK_KEY, WORKER_RPC_DRAIN_KEY
  from ray.autoscaler._private.kuberay import node_provider, utils
  from ray.autoscaler._private.util import validate_config
label_desc: Use image node_id 2 for calling the AutoscalingConfigProducer obj's underlying member method code with example usage: obj.__call__() and returns: autoscaling_config