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.
docstr: Creates a temporary directory.
  
  Args:
      _: Unused arg. Exists to make this function compatible with foreach_actor
      calls.
  
  Returns:
      The path to the temporary directory.
docstr_tok: ["Creates","a","temporary","directory",".","Args",":","_",":","Unused","arg",".","Exists","to","make","this","function","compatible","with","foreach_actor","calls",".","Returns",":","The","path","to","the","temporary","directory","."]
code: def _create_temporary_dir(_=None) -> str:
      """Creates a temporary directory.
  
      Args:
          _: Unused arg. Exists to make this function compatible with foreach_actor
          calls.
  
      Returns:
          The path to the temporary directory.
      """
      import tempfile
  
      return tempfile.mkdtemp()
  
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 24 for calling the LearnerGroup obj's underlying member method code with example usage: obj._create_temporary_dir(_) and returns: tempfile