code: def make_env_and_successful_return(self, test):
      return (
          ABC(
              discrete=True,
              partially_observable=True,
              deterministic=test,
          ),
          1,
      )
  
imports: import numpy
  import torch.nn
  import torch.optim
  from basetest_training import _TestTraining
  from pfrl import q_functions, replay_buffers
  from pfrl.envs.abc import ABC
  from pfrl.explorers.epsilon_greedy import LinearDecayEpsilonGreedy
  from pfrl.nn import RecurrentSequential
label_desc: Use image node_id 3 for calling the _TestDQNOnDiscretePOABC obj's underlying member method code with example usage: obj.make_env_and_successful_return(test) and returns: ABC,  int