code: def restore_connectors_for_policy(
      policy: "Policy", connector_config: Tuple[str, Tuple[Any]]
  ) -> Connector:
      """Util to create connector for a Policy based on serialized config.
  
      Args:
          policy: Policy instance.
          connector_config: Serialized connector config.
      """
      ctx: ConnectorContext = ConnectorContext.from_policy(policy)
      name, params = connector_config
      return get_connector(name, ctx, params)
  
imports: import logging
  from typing import Any, Tuple, TYPE_CHECKING
  from ray.rllib.connectors.action.clip import ClipActionsConnector
  from ray.rllib.connectors.action.immutable import ImmutableActionsConnector
  from ray.rllib.connectors.action.lambdas import ConvertToNumpyConnector
  from ray.rllib.connectors.action.normalize import NormalizeActionsConnector
  from ray.rllib.connectors.action.pipeline import ActionConnectorPipeline
  from ray.rllib.connectors.agent.clip_reward import ClipRewardAgentConnector
  from ray.rllib.connectors.agent.obs_preproc import ObsPreprocessorConnector
  from ray.rllib.connectors.agent.pipeline import AgentConnectorPipeline
  from ray.rllib.connectors.agent.state_buffer import StateBufferConnector
  from ray.rllib.connectors.agent.view_requirement import ViewRequirementAgentConnector
  from ray.rllib.connectors.connector import Connector, ConnectorContext
  from ray.rllib.connectors.registry import get_connector
  from ray.rllib.connectors.agent.mean_std_filter import MeanStdObservationFilterAgentConnector, ConcurrentMeanStdObservationFilterAgentConnector
  from ray.util.annotations import PublicAPI, DeveloperAPI
  from ray.rllib.connectors.agent.synced_filter import SyncedFilterAgentConnector
label_desc: Use image node_id 6 for calling a global function with example usage: restore_connectors_for_policy(policy, connector_config) and returns: get_connector