class_docstr: End episodes after specified number of steps and reset after game_over.
  
  This differs from the default TimeLimit wrapper in that it looks at the
  game_over property before resetting. We need this to properly handle life
  loss terminations -- the default TimeLimit wrapper would .reset() the
  environment and the step count after such a termination, but we want the
  environment to keep going.
class_docstr_tok: ["End","episodes","after","specified","number","of","steps","and","reset","after","game_over",".","This","differs","from","the","default","TimeLimit","wrapper","in","that","it","looks","at","the","game_over","property","before","resetting",".","We","need","this","to","properly","handle","life","loss","terminations","--","the","default","TimeLimit","wrapper","would",".reset","(",")","the","environment","and","the","step","count","after","such","a","termination",",","but","we","want","the","environment","to","keep","going","."]
code: def _reset(self):
      self._num_steps = 0
      return self._env.reset()
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  from typing import Any, Text
  import gym
  import numpy
  from tf_agents.environments import py_environment
  from tf_agents.environments import wrappers
  from tf_agents.trajectories import time_step
label_desc: Use image node_id 2 for calling the AtariTimeLimit obj's underlying member method code with example usage: obj._reset() and returns: self