class_docstr: "Play on single (simulated or real) environment.
  
  See `PlayerEnv` for more details.
  
  Naming conventions:
    envs_step_tuples: dictionary with single key.
      {
        "env": (observation, reward, done, info),
      }
      Plural form used for consistency with `PlayerEnv`.
class_docstr_tok: ["``","Play","on","single","(","simulated","or","real",")","environment",".","See","`","PlayerEnv","`","for","more","details",".","Naming","conventions",":","envs_step_tuples",":","dictionary","with","single","key",".","{","``","env","''",":","(","observation",",","reward",",","done",",","info",")",",","}","Plural","form","used","for","consistency","with","`","PlayerEnv","`","."]
code: def _pack_step_tuples(self, env_step_tuple):
      return dict(env=env_step_tuple)
  
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 3 for calling the SingleEnvPlayer obj's underlying member method code with example usage: obj._pack_step_tuples(env_step_tuple) and returns: dict