class_docstr: Base wrapper implementing PyEnvironmentBaseWrapper interface for Gym envs.
  
  Action and observation specs are automatically generated from the action and
  observation spaces. See base class for py_environment.Base details.
code: def gym(self) -> gym.Env:
      return self._gym_env
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  from typing import Any, Dict, Optional, Text
  import gym
  import gym.spaces
  import numpy
  import tensorflow
  from tf_agents import specs
  from tf_agents.environments import py_environment
  from tf_agents.trajectories import time_step
  from tf_agents.typing import types
  from tensorflow.python.util import nest
label_desc: Use image node_id 2 for calling the GymWrapper obj's underlying member method code with example usage: obj.gym() and returns: self