code: def test_ppo_multi_agent_train_then_rollout(self):
      learn_test_multi_agent_plus_evaluate("PPO")
  
imports: import os
  from pathlib import Path
  import re
  import sys
  import unittest
  from unittest import mock
  import ray
  from ray import air, tune
  from ray.rllib.algorithms.algorithm_config import AlgorithmConfig
  from ray.rllib.examples.env.multi_agent import MultiAgentCartPole
  from ray.rllib.utils.test_utils import framework_iterator
  from ray.tune.registry import get_trainable_cls
  from ray.rllib.core.rl_module.rl_module import SingleAgentRLModuleSpec
  from ray.rllib.core.rl_module.marl_module import MultiAgentRLModuleSpec
label_desc: Use image node_id 2 for calling the TestTrainAndEvaluate obj's underlying member method code with example usage: obj.test_ppo_multi_agent_train_then_rollout() without return types