code: def _wrap_state(self, state):
      if not isinstance(self.env.observation_space, gym.spaces.Dict):
          return {"observation": state}
      return state
  
imports: import gym
  import numpy
  from enum import IntEnum
  import scipy.ndimage
  from rl_coach.graph_managers.graph_manager import ScheduleParameters
  from rl_coach.utils import lower_under_to_upper, short_dynamic_import
  from typing import Dict, Any, Union
  from rl_coach.core_types import RunPhase, EnvironmentSteps
  from rl_coach.environments.environment import Environment, EnvironmentParameters, LevelSelection
  from rl_coach.spaces import DiscreteActionSpace, BoxActionSpace, ImageObservationSpace, VectorObservationSpace, PlanarMapsObservationSpace, TensorObservationSpace, StateSpace, RewardSpace
  from rl_coach.filters.filter import NoInputFilter, NoOutputFilter
  from rl_coach.filters.reward.reward_clipping_filter import RewardClippingFilter
  from rl_coach.filters.observation.observation_rescale_to_size_filter import ObservationRescaleToSizeFilter
  from rl_coach.filters.observation.observation_stacking_filter import ObservationStackingFilter
  from rl_coach.filters.observation.observation_rgb_to_y_filter import ObservationRGBToYFilter
  from rl_coach.filters.observation.observation_to_uint8_filter import ObservationToUInt8Filter
  from rl_coach.filters.filter import InputFilter
  import random
  from rl_coach.base_parameters import VisualizationParameters
  from rl_coach.logger import screen
label_desc: Use image node_id 2 for calling the GymEnvironment obj's underlying member method code with example usage: obj._wrap_state(state) and returns: state, dict