class_docstr: Run simulated and real env side-by-side for comparison.
  
  Displays three windows - one for real environment, second for simulated
  and third for their differences.
  
  Normal actions are passed to both environments.
  
  Special Actions:
    RESTART_SIMULATED_ENV_ACTION: restart simulated environment only, using
      current frames from real environment.
    See `PlayerEnv` for rest of special actions.
  
  Naming conventions:
    envs_step_tuples: dictionary with two keys.
    {
      "real_env": (observation, reward, done, info),
      "sim_env": (observation, reward, done, info)
    }
class_docstr_tok: ["Run","simulated","and","real","env","side-by-side","for","comparison",".","Displays","three","windows","-","one","for","real","environment",",","second","for","simulated","and","third","for","their","differences",".","Normal","actions","are","passed","to","both","environments",".","Special","Actions",":","RESTART_SIMULATED_ENV_ACTION",":","restart","simulated","environment","only",",","using","current","frames","from","real","environment",".","See","`","PlayerEnv","`","for","rest","of","special","actions",".","Naming","conventions",":","envs_step_tuples",":","dictionary","with","two","keys",".","{","``","real_env","''",":","(","observation",",","reward",",","done",",","info",")",",","``","sim_env","''",":","(","observation",",","reward",",","done",",","info",")","}"]
code: def _player_actions(self):
      actions = super(SimAndRealEnvPlayer, self)._player_actions()
      actions.update(
          {
              self.RESTART_SIMULATED_ENV_ACTION: self.player_restart_simulated_env_action,
          }
      )
      return actions
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import gym
  from gym.utils import play
  import numpy
  from tensor2tensor.bin import t2t_trainer
  from tensor2tensor.rl import player_utils
  from tensor2tensor.rl.envs.simulated_batch_env import PIL_Image
  from tensor2tensor.rl.envs.simulated_batch_env import PIL_ImageDraw
  from tensor2tensor.rl.envs.simulated_batch_gym_env import FlatBatchEnv
  from tensor2tensor.rl.rl_utils import absolute_hinge_difference
  from tensor2tensor.rl.rl_utils import full_game_name
  import tensor2tensor.rl.trainer_model_based_params
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling the SimAndRealEnvPlayer obj's underlying member method code with example usage: obj._player_actions() and returns: actions