class_docstr: Counts up in the observation as steps are taken.
  
  Step observation values are of the form (10 ** episodes + self._current_step)
  if steps_per_episode is greater than 10 then on reset the value of the
  observation count may go down.
class_docstr_tok: ["Counts","up","in","the","observation","as","steps","are","taken",".","Step","observation","values","are","of","the","form","(","10","*","*","episodes","+","self._current_step",")","if","steps_per_episode","is","greater","than","10","then","on","reset","the","value","of","the","observation","count","may","go","down","."]
code: def _get_observation(self):
      if self._episodes:
          return np.array(
              10 * self._episodes + self._current_step,
              dtype=self._dtype,
          )
      return self._current_step
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import gin
  import numpy
  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
label_desc: Use image node_id 5 for calling the CountingEnv obj's underlying member method code with example usage: obj._get_observation() and returns: self, np