class_docstr: Filter Dict observation space by the keys.
  
  Example:
      >>> import gym
      >>> env = gym.wrappers.TransformObservation(
      ...     gym.make('CartPole-v1'), lambda obs: {'obs': obs, 'time': 0}
      ... )
      >>> env.observation_space = gym.spaces.Dict(obs=env.observation_space, time=gym.spaces.Discrete(1))
      >>> env.reset()
      {'obs': array([-0.00067088, -0.01860439,  0.04772898, -0.01911527], dtype=float32), 'time': 0}
      >>> env = FilterObservation(env, filter_keys=['time'])
      >>> env.reset()
      {'obs': array([ 0.04560107,  0.04466959, -0.0328232 , -0.02367178], dtype=float32)}
      >>> env.step(0)
      ({'obs': array([ 0.04649447, -0.14996664, -0.03329664,  0.25847703], dtype=float32)}, 1.0, False, {})
code: def _filter_observation(self, observation):
      observation = type(observation)(
          [
              (name, value)
              for name, value in observation.items()
              if name in self._filter_keys
          ]
      )
      return observation
  
file_path: gym/gym/wrappers/filter_observation.py
imports: import copy
  from typing import Sequence
  import gym
  from gym import spaces
label_desc: Use image node_id 3 for calling the FilterObservation obj's underlying member method code with example usage: obj._filter_observation(observation) and returns: observation