code: def handle_remote_call_result_errors(
      results: RemoteCallResults,
      ignore_worker_failures: bool,
  ) -> None:
      """Checks given results for application errors and raises them if necessary.
  
      Args:
          results: The results to check.
      """
      for r in results.ignore_ray_errors():
          if r.ok:
              continue
          if ignore_worker_failures:
              logger.exception(r.get())
          else:
              raise r.get()
  
imports: import functools
  import gymnasium
  import logging
  import importlib.util
  import os
  from typing import Callable, Container, Dict, List, Optional, Tuple, Type, TYPE_CHECKING, TypeVar, Union
  import ray
  from ray.actor import ActorHandle
  from ray.exceptions import RayActorError
  from ray.rllib.core.rl_module.rl_module import SingleAgentRLModuleSpec
  from ray.rllib.evaluation.rollout_worker import RolloutWorker
  from ray.rllib.utils.actor_manager import RemoteCallResults
  from ray.rllib.env.base_env import BaseEnv
  from ray.rllib.env.env_context import EnvContext
  from ray.rllib.env.env_runner import EnvRunner
  from ray.rllib.offline import get_dataset_and_shards
  from ray.rllib.policy.policy import Policy, PolicyState
  from ray.rllib.policy.sample_batch import DEFAULT_POLICY_ID
  from ray.rllib.utils.actor_manager import FaultTolerantActorManager
  from ray.rllib.utils.annotations import DeveloperAPI
  from ray.rllib.utils.deprecation import Deprecated, deprecation_warning, DEPRECATED_VALUE
  from ray.rllib.utils.framework import try_import_tf
  from ray.rllib.utils.policy import validate_policy_id
  from ray.rllib.utils.typing import AgentID, EnvCreator, EnvType, EpisodeID, PartialAlgorithmConfigDict, PolicyID, SampleBatchType, TensorType
label_desc: Use image node_id 1 for calling a global function with example usage: handle_remote_call_result_errors(results, ignore_worker_failures) without return types