class_docstr: A dummy akro.Dict environment with predefined inner spaces.
  
  Args:
      random (bool): If observations are randomly generated or not.
      obs_space_type (str): The type of the inner spaces of the
          dict observation space.
      act_space_type (str): The type of action space to mock.
class_docstr_tok: ["A","dummy","akro.Dict","environment","with","predefined","inner","spaces",".","Args",":","random","(","bool",")",":","If","observations","are","randomly","generated","or","not",".","obs_space_type","(","str",")",":","The","type","of","the","inner","spaces","of","the","dict","observation","space",".","act_space_type","(","str",")",":","The","type","of","action","space","to","mock","."]
docstr: Return the action space.
  
  Returns:
      akro.Box: Action space.
docstr_tok: ["Return","the","action","space",".","Returns",":","akro.Box",":","Action","space","."]
code: def action_space(self):
      """Return the action space.
  
      Returns:
          akro.Box: Action space.
  
      """
      if self.act_space_type == "box":
          return akro.Box(
              low=-5.0, high=5.0, shape=(1,), dtype=np.float32
          )
      else:
          return akro.Discrete(5)
  
file_path: garage/tests/fixtures/envs/dummy/dummy_dict_env.py
imports: import akro
  import gym
  import numpy
  from garage import EnvSpec
  from tests.fixtures.envs.dummy import DummyEnv
label_desc: Use image node_id 3 for calling the DummyDictEnv obj's underlying member method code with example usage: obj.action_space() and returns: akro, akro