class_docstr: Observe the number of elapsed steps in an episode.
  
  A new observation will be a tuple of an original observation and an integer
  that is equal to the elapsed steps in an episode.
code: def __init__(self, env, max_steps):
      super().__init__(env)
      self._max_steps = max_steps
      self._elapsed_steps = 0
      self.observation_space = gym.spaces.Tuple(
          (
              env.observation_space,
              gym.spaces.Discrete(self._max_steps + 1),
          )
      )
  
imports: import argparse
  import functools
  import os
  import chainer
  from chainer import functions
  from chainer import links
  from chainer import optimizers
  import gym
  import gym.spaces
  import numpy
  import chainerrl
  from chainerrl.action_value import DiscreteActionValue
  from chainerrl import experiments
  from chainerrl import explorers
  from chainerrl import misc
  from chainerrl import replay_buffer
label_desc: Use image node_id 1 to create a new ObserveElapsedSteps object from inherited base classes: gym with example: obj = ObserveElapsedSteps(env, max_steps)