class_docstr: The DiscretizeActionsWrapper provides functionality for discretizing individual continuous actions into discrete
   ones.
  
  An example is given by having a continuous action called 'action_up' with space:
  gym.spaces.Box(shape=(5,), low=[-1,-1,-1,-1,-1], high=[1,1,1,1,1]
  
  discretization_config:
      action_up:
          num_bins: 5
          low: [-1, 0, 0.5, 0, 0]
          high: 1
  
  Now the action space will be split where each of the 5 continuous values of the box spaces are split evenly within
  the ranges of (-1,1),(0,1),(0.5,1), (0,1), (0,1) respectively.
  
  :param env: Environment/wrapper to wrap.
  :param discretization_config: The action discretization configuration.
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docstr: The currently active gym action space.
          
docstr_tok: ["The","currently","active","gym","action","space","."]
code: def action_space(self) -> gym.spaces.Dict:
      """The currently active gym action space."""
      return self._action_spaces_dict[self.env.actor_id()[0]]
  
file_path: maze/maze/core/wrappers/discretize_actions_wrapper.py
imports: from typing import Union, Dict, List
  import gym
  import numpy
  from maze.core.annotations import override
  from maze.core.env.simulated_env_mixin import SimulatedEnvMixin
  from maze.core.env.structured_env import StructuredEnv
  from maze.core.env.structured_env_spaces_mixin import StructuredEnvSpacesMixin
  from maze.core.utils.structured_env_utils import flat_structured_space
  from maze.core.wrappers.wrapper import ActionWrapper, EnvType
label_desc: Use image node_id 4 for calling the DiscretizeActionsWrapper obj's underlying member method code with example usage: obj.action_space() and returns: self