code: def get_filters(self, flush_after=False):
      return_filters = {}
      for k, f in self.filters.items():
          return_filters[k] = f.as_serializable()
          if flush_after:
              f.reset_buffer()
      return return_filters
  
imports: import logging
  import random
  import time
  from collections import namedtuple
  from typing import Optional
  import numpy
  from rllib_ars.ars.ars_tf_policy import ARSTFPolicy
  import ray
  from ray.rllib.algorithms import Algorithm
  from ray.rllib.algorithms.algorithm_config import AlgorithmConfig, NotProvided
  from ray.rllib.algorithms.es import optimizers, utils
  from ray.rllib.algorithms.es.es_tf_policy import rollout
  from ray.rllib.env.env_context import EnvContext
  from ray.rllib.evaluation.worker_set import WorkerSet
  from ray.rllib.policy.sample_batch import DEFAULT_POLICY_ID
  from ray.rllib.utils import FilterManager
  from ray.rllib.utils.actor_manager import FaultAwareApply
  from ray.rllib.utils.annotations import override
  from ray.rllib.utils.metrics import NUM_AGENT_STEPS_SAMPLED, NUM_AGENT_STEPS_TRAINED, NUM_ENV_STEPS_SAMPLED, NUM_ENV_STEPS_TRAINED
  from ray.rllib.utils.torch_utils import set_torch_seed
label_desc: Use image node_id 4 for calling the Worker obj's underlying member method code with example usage: obj.get_filters(flush_after) and returns: return_filters