class_docstr: REST client to interact with an RLlib policy server.
docstr: Query the server for new policy weights, if local inference is enabled.
docstr_tok: ["Query","the","server","for","new","policy","weights",",","if","local","inference","is","enabled","."]
code: def update_policy_weights(self) -> None:
      """Query the server for new policy weights, if local inference is enabled."""
      self._update_local_policy(force=True)
  
imports: import logging
  import threading
  import time
  from typing import Union, Optional
  from enum import Enum
  import ray.cloudpickle
  from ray.rllib.env.external_env import ExternalEnv
  from ray.rllib.env.external_multi_agent_env import ExternalMultiAgentEnv
  from ray.rllib.env.multi_agent_env import MultiAgentEnv
  from ray.rllib.policy.sample_batch import MultiAgentBatch
  from ray.rllib.utils.annotations import PublicAPI
  from ray.rllib.utils.typing import MultiAgentDict, EnvInfoDict, EnvObsType, EnvActionType
label_desc: Use image node_id 7 for calling the PolicyClient obj's underlying member method code with example usage: obj.update_policy_weights() without return types