code: def test_add_remove_module(self):
      fws = ["torch", "tf2"]
      scaling_modes = ["multi-gpu-ddp"]
      test_iterator = itertools.product(fws, scaling_modes)
  
      for fw, scaling_mode in test_iterator:
          print(
              f"Testing framework: {fw}, scaling mode: {scaling_mode}."
          )
          env = gym.make("CartPole-v1")
          config_overrides = REMOTE_CONFIGS[scaling_mode]
          config = BaseTestingAlgorithmConfig().update_from_dict(
              config_overrides
          )
          learner_group = config.build_learner_group(env=env)
          reader = get_cartpole_dataset_reader(batch_size=512)
          batch = reader.next()
  
          # update once with the default policy
          results = learner_group.update_from_batch(
              batch=batch.as_multi_agent(), reduce_fn=None
          )
          module_ids_before_add = {DEFAULT_POLICY_ID}
          new_module_id = "test_module"
  
          # add a test_module
          add_module_to_learner_or_learner_group(
              config, env, new_module_id, learner_group
          )
  
          # do training that includes the test_module
          results = learner_group.update_from_batch(
              batch=MultiAgentBatch(
                  {new_module_id: batch, DEFAULT_POLICY_ID: batch},
                  batch.count,
              ),
              reduce_fn=None,
          )
  
          self._check_multi_worker_weights(results)
  
          # check that module ids are updated to include the new module
          module_ids_after_add = {DEFAULT_POLICY_ID, new_module_id}
          for result in results:
              # remove the total_loss key since its not a module key
              self.assertEqual(
                  set(result.keys()) - {ALL_MODULES},
                  module_ids_after_add,
              )
  
          # remove the test_module
          learner_group.remove_module(module_id=new_module_id)
  
          # run training without the test_module
          results = learner_group.update_from_batch(
              batch=batch.as_multi_agent(), reduce_fn=None
          )
  
          self._check_multi_worker_weights(results)
  
          # check that module ids are updated after remove operation to not
          # include the new module
          for result in results:
              # remove the total_loss key since its not a module key
              self.assertEqual(
                  set(result.keys()) - {ALL_MODULES},
                  module_ids_before_add,
              )
  
          # make sure the learner_group resources are freed up so that we don't
          # autoscale
          learner_group.shutdown()
          del learner_group
  
imports: import gymnasium
  import itertools
  import numpy
  from typing import Any, Dict, List
  import tempfile
  import unittest
  import ray
  from ray.rllib.algorithms.algorithm_config import AlgorithmConfig
  from ray.rllib.algorithms.ppo.tests.test_ppo_learner import FAKE_BATCH
  from ray.rllib.core.learner.learner import Learner
  from ray.rllib.core.rl_module.marl_module import MultiAgentRLModule
  from ray.rllib.core.rl_module.rl_module import SingleAgentRLModuleSpec
  from ray.rllib.core.testing.tf.bc_learner import BCTfLearner
  from ray.rllib.core.testing.tf.bc_module import DiscreteBCTFModule
  from ray.rllib.core.testing.utils import add_module_to_learner_or_learner_group
  from ray.rllib.core.testing.testing_learner import BaseTestingAlgorithmConfig
  from ray.rllib.examples.env.multi_agent import MultiAgentCartPole
  from ray.rllib.policy.sample_batch import DEFAULT_POLICY_ID, SampleBatch, MultiAgentBatch
  from ray.rllib.utils.test_utils import check, get_cartpole_dataset_reader
  from ray.rllib.utils.metrics import ALL_MODULES
  from ray.util.timer import _Timer
label_desc: Use image node_id 6 for calling the TestLearnerGroupSyncUpdate obj's underlying member method code with example usage: obj.test_add_remove_module() without return types