code: def _test_abc(
      self, steps=100000, require_success=True, gpu=-1, load_model=False
  ):
      if self.recurrent and gpu >= 0:
          self.skipTest(
              "NStepLSTM does not support double backprop with GPU."
          )
      if self.recurrent and chainer.__version__ == "7.0.0b3":
          self.skipTest(
              "chainer==7.0.0b3 has a bug in double backrop of LSTM."
              " See https://github.com/chainer/chainer/pull/8037"
          )
  
      env, _ = self.make_env_and_successful_return(test=False)
      test_env, successful_return = self.make_env_and_successful_return(
          test=True
      )
  
      agent = self.make_agent(env, gpu)
  
      if load_model:
          print("Load agent from", self.agent_dirname)
          agent.load(self.agent_dirname)
  
      max_episode_len = None if self.episodic else 2
  
      # Train
      train_agent_with_evaluation(
          agent=agent,
          env=env,
          eval_env=test_env,
          steps=steps,
          outdir=self.tmpdir,
          eval_interval=200,
          eval_n_steps=None,
          eval_n_episodes=5,
          successful_score=successful_return,
          train_max_episode_len=max_episode_len,
      )
  
      agent.stop_episode()
  
      # Test
      n_test_runs = 10
      eval_returns = run_evaluation_episodes(
          test_env,
          agent,
          n_steps=None,
          n_episodes=n_test_runs,
          max_episode_len=max_episode_len,
      )
      if require_success:
          n_succeeded = np.sum(
              np.asarray(eval_returns) >= successful_return
          )
          self.assertEqual(n_succeeded, n_test_runs)
  
      # Save
      agent.save(self.agent_dirname)
  
imports: import os
  import tempfile
  import unittest
  import chainer
  import chainer.functions
  from chainer import links
  from chainer import optimizers
  from chainer import testing
  import numpy
  import chainerrl
  from chainerrl.agents import trpo
  from chainerrl.envs.abc import ABC
  from chainerrl.experiments.evaluator import batch_run_evaluation_episodes
  from chainerrl.experiments.evaluator import run_evaluation_episodes
  from chainerrl.experiments import train_agent_batch_with_evaluation
  from chainerrl.experiments import train_agent_with_evaluation
  from chainerrl.links import StatelessRecurrentSequential
  from chainerrl import policies
label_desc: Use image node_id 10 for calling the TestTRPO obj's underlying member method code with example usage: obj._test_abc(steps, require_success, gpu, load_model) without return types