code: def test_multi_agent_env(self):
      temp_env = EpisodeEnv(NUM_STEPS, NUM_AGENTS)
      ev = RolloutWorker(
          env_creator=lambda _: temp_env,
          default_policy_class=EchoPolicy,
          config=AlgorithmConfig()
          .multi_agent(
              policies={
                  str(agent_id) for agent_id in range(NUM_AGENTS)
              },
              policy_mapping_fn=lambda agent_id, episode, worker, **kwargs: (
                  str(agent_id)
              ),
          )
          .rollouts(enable_connectors=True, num_rollout_workers=0),
      )
      sample_batches = ev.sample()
      self.assertEqual(len(sample_batches.policy_batches), 4)
      for (
          agent_id,
          sample_batch,
      ) in sample_batches.policy_batches.items():
          self.assertEqual(sample_batch.count, 200)
          # A batch of 100. 4 episodes, each 25.
          self.assertEqual(len(set(sample_batch["eps_id"])), 8)
  
imports: import unittest
  import ray
  from ray.rllib.algorithms.algorithm_config import AlgorithmConfig
  from ray.rllib.env.multi_agent_env import MultiAgentEnv
  from ray.rllib.evaluation.rollout_worker import RolloutWorker
  from ray.rllib.examples.env.mock_env import MockEnv3
  from ray.rllib.policy import Policy
  from ray.rllib.utils import override
label_desc: Use image node_id 4 for calling the TestEpisodeV2 obj's underlying member method code with example usage: obj.test_multi_agent_env() without return types