code: def make_env_and_successful_return(self, test):
      env = ABC(
          discrete=self.discrete,
          episodic=self.episodic or test,
          deterministic=test,
          partially_observable=self.recurrent,
      )
      return env, 1
  
imports: import os
  import tempfile
  import unittest
  import numpy
  import pytest
  import torch
  from torch import nn
  import pfrl
  from pfrl.agents import trpo
  from pfrl.envs.abc import ABC
  from pfrl.experiments import train_agent_batch_with_evaluation, train_agent_with_evaluation
  from pfrl.experiments.evaluator import batch_run_evaluation_episodes, run_evaluation_episodes
  from pfrl.nn import RecurrentSequential
  from pfrl.policies import GaussianHeadWithStateIndependentCovariance, SoftmaxCategoricalHead
  from pfrl.testing import torch_assert_allclose
label_desc: Use image node_id 14 for calling the _TestTRPO obj's underlying member method code with example usage: obj.make_env_and_successful_return(test) and returns: env,  int