code: def init_batch_and_play(
      self,
      env_name,
      steps_per_epoch=1,
      epochs=(0,),
      generate_data=False,
      batch_size=2,
      **kwargs,
  ):
      env = gym_env.T2TGymEnv(env_name, batch_size=batch_size, **kwargs)
      obs = []
      rewards = []
      num_dones = 0
      for epoch in epochs:
          env.start_new_epoch(epoch, self.out_dir)
          _, epoch_obs, epoch_rewards, epoch_num_dones = self.play(
              env, steps_per_epoch
          )
          epoch_obs.append(env.reset())
          if generate_data:
              env.generate_data(self.out_dir)
          obs.extend(epoch_obs)
          rewards.extend(epoch_rewards)
          num_dones += epoch_num_dones
      return env, obs, rewards, num_dones
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import shutil
  import gym
  from gym.spaces import Box
  from gym.spaces import Discrete
  import numpy
  from tensor2tensor.data_generators import gym_env
  from tensor2tensor.data_generators import problem
  from tensor2tensor.rl.gym_utils import make_gym_env
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling the GymEnvTest obj's underlying member method code with example usage: obj.init_batch_and_play(env_name, steps_per_epoch, epochs, generate_data, batch_size) and returns: env,  obs,  rewards,  num_dones