class_docstr: A RL task: environment and a collection of trajectories.
class_docstr_tok: ["A","RL","task",":","environment","and","a","collection","of","trajectories","."]
docstr: Returns the env's observation space in a Gym interface.
docstr_tok: ["Returns","the","env","'s","observation","space","in","a","Gym","interface","."]
code: def observation_space(self):
      """Returns the env's observation space in a Gym interface."""
      if self._dm_suite:
          return gym.spaces.Box(
              shape=self._env.observation_spec().shape,
              dtype=self._env.observation_spec().dtype,
              low=float("-inf"),
              high=float("+inf"),
          )
      else:
          return self._env.observation_space
  
imports: import collections
  import os
  import gin
  import gym
  import numpy
  from trax import fastmath
  from trax.rl import advantages
  from trax.supervised import training
label_desc: Use image node_id 7 for calling the RLTask obj's underlying member method code with example usage: obj.observation_space() and returns: gym, self