class_docstr: Wraps an environment with continuous actions and discretizes them.
  
  This is a simplified adaptation of ActionDiscretizeWrapper
  from tf_agents.
docstr: Steps the environment while remapping the actions.
  
  Args:
    action: Action to take.
  
  Returns:
    The next time_step from the environment.
docstr_tok: ["Steps","the","environment","while","remapping","the","actions",".","Args",":","action",":","Action","to","take",".","Returns",":","The","next","time_step","from","the","environment","."]
code: def action(self, action):
      """Steps the environment while remapping the actions.
  
      Args:
        action: Action to take.
  
      Returns:
        The next time_step from the environment.
      """
      return self._map_actions(action)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  from absl import logging
  import gym
  import gym.wrappers
  import numpy
  from PIL import Image
label_desc: Use image node_id 4 for calling the ActionDiscretizeWrapper obj's underlying member method code with example usage: obj.action(action) and returns: self