code: def write_outputs(self, output, fw, output_config=None):
      config = (
          PPOConfig()
          .environment("CartPole-v1")
          .framework(fw)
          .training(train_batch_size=250)
          .offline_data(
              output=output + (fw if output != "logdir" else ""),
              output_config=output_config or {},
          )
      )
      algo = config.build()
      print(algo.train())
      return algo
  
imports: import glob
  import json
  import numpy
  import os
  import random
  import shutil
  import tempfile
  import unittest
  import ray
  from ray.tune.registry import register_env, register_input, registry_get_input, registry_contains_input
  from ray.rllib.algorithms.algorithm_config import AlgorithmConfig
  from ray.rllib.algorithms.pg import PGConfig
  from ray.rllib.algorithms.ppo import PPOConfig
  from ray.rllib.examples.env.multi_agent import MultiAgentCartPole
  from ray.rllib.offline import IOContext, JsonWriter, JsonReader, InputReader, ShuffledInput, DatasetWriter
  from ray.rllib.offline.json_reader import from_json_data
  from ray.rllib.offline.json_writer import _to_json_dict, _to_json
  from ray.rllib.policy.sample_batch import SampleBatch, convert_ma_batch_to_sample_batch
  from ray.rllib.utils.test_utils import framework_iterator
label_desc: Use image node_id 3 for calling the AgentIOTest obj's underlying member method code with example usage: obj.write_outputs(output, fw, output_config) and returns: algo