class_docstr: Coordinator of n (possibly remote) Learner workers.
  
  Each Learner worker has a copy of the RLModule, the loss function(s), and
  one or more optimizers.
class_docstr_tok: ["Coordinator","of","n","(","possibly","remote",")","Learner","workers",".","Each","Learner","worker","has","a","copy","of","the","RLModule",",","the","loss","function","(","s",")",",","and","one","or","more","optimizers","."]
docstr: Remove a module from the Learners maintained by this LearnerGroup.
  
  Args:
      module_id: The id of the module to remove.
docstr_tok: ["Remove","a","module","from","the","Learners","maintained","by","this","LearnerGroup",".","Args",":","module_id",":","The","id","of","the","module","to","remove","."]
code: def remove_module(self, module_id: ModuleID) -> None:
      """Remove a module from the Learners maintained by this LearnerGroup.
  
      Args:
          module_id: The id of the module to remove.
  
      """
      if self.is_local:
          self._learner.remove_module(module_id)
      else:
          refs = []
          for worker in self._workers:
              ref = worker.remove_module.remote(module_id)
              refs.append(ref)
          ray.get(refs)
  
imports: from collections import defaultdict, Counter
  from functools import partial
  import pathlib
  from typing import Any, Callable, Dict, List, Optional, Set, Type, Union
  import uuid
  import ray
  from ray.rllib.algorithms.algorithm_config import AlgorithmConfig
  from ray.rllib.core.learner.learner import Learner
  from ray.rllib.core.learner.reduce_result_dict_fn import _reduce_mean_results
  from ray.rllib.core.rl_module.rl_module import SingleAgentRLModuleSpec, RLMODULE_STATE_DIR_NAME
  from ray.rllib.policy.sample_batch import MultiAgentBatch
  from ray.rllib.utils.actor_manager import FaultTolerantActorManager
  from ray.rllib.utils.deprecation import Deprecated, deprecation_warning
  from ray.rllib.utils.minibatch_utils import ShardBatchIterator, ShardEpisodesIterator
  from ray.rllib.utils.numpy import convert_to_numpy
  from ray.rllib.utils.typing import EpisodeType, ModuleID, ResultDict, RLModuleSpec, ShouldModuleBeUpdatedFn
  from ray.train._internal.backend_executor import BackendExecutor
  from ray.tune.utils.file_transfer import sync_dir_between_nodes
  from ray.util.annotations import PublicAPI
label_desc: Use image node_id 12 for calling the LearnerGroup obj's underlying member method code with example usage: obj.remove_module(module_id) without return types