code: def __init__(self, env):
      self.env = env
      self.action_space = self.env.action_space
      self.observation_space = self.env.observation_space
      self.low_bound = self.env.action_space.low[0]
      self.high_bound = self.env.action_space.high[0]
      assert self.high_bound > self.low_bound
  
file_path: PARL/examples/tutorials/parl2_dygraph/lesson5/homework/ddpg_quadrotor/train.py
imports: import gym
  import parl
  import paddle
  import argparse
  import numpy
  from parl.utils import logger, tensorboard, ReplayMemory
  from quadrotor_model import QuadrotorModel
  from quadrotor_agent import QuadrotorAgent
  from parl.algorithms import DDPG
  from rlschool import make_env
  import paddle
label_desc: Use image node_id 1 to create a new ActionMappingWrapper object  with example: obj = ActionMappingWrapper(env)