code: def make_vec_env_and_successful_return(self, test, num_envs=3):
      def make_env():
          return self.make_env_and_successful_return(test)[0]
  
      vec_env = pfrl.envs.MultiprocessVectorEnv(
          [make_env for _ in range(num_envs)]
      )
      return vec_env, 1.0
  
imports: import os
  import tempfile
  import numpy
  import pytest
  import torch
  from torch import distributions, nn
  import pfrl
  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.lmbda import Lambda
label_desc: Use image node_id 14 for calling the TestSoftActorCritic obj's underlying member method code with example usage: obj.make_vec_env_and_successful_return(test, num_envs) and returns: vec_env,  int, self