class_docstr: Based on OpenAI Gym version
  (https://github.com/openai/gym/blob/master/gym/envs/classic_control/cartpole.py)
code: def states(self):
      return dict(
          type="float",
          shape=tuple(self._state_indices.shape),
          min_value=-self._state_bounds[0, self._state_indices],
          max_value=self._state_bounds[0, self._state_indices],
      )
  
file_path: tensorforce/tensorforce/environments/cartpole.py
imports: import numpy
  from tensorforce.environments import Environment
label_desc: Use image node_id 2 for calling the CartPole obj's underlying member method code with example usage: obj.states() and returns: dict