text: # -*- coding: utf-8 -*-
  """
  Created on Wed Dec  4 10:31:28 2019
  @author: Z0014354
  """
  
  from multiprocessing import Process, Pipe
  import numpy as np
  
  def worker(remote, parent_remote, env_fn_wrapper):
      parent_remote.close()
      env = env_fn_wrapper.x()
      while True:
          cmd, data = remote.recv()
          if cmd == 'step':
              ob, reward, done, info = env.step(data)
              if done:
                  ob = env.reset()
              remote.send((ob, reward, done, info))
          elif cmd == 'reset':
              ob = env.reset()
              remote.send(ob)
          elif cmd == 'reset_task':
              ob = env.reset_task()
              remote.send(ob)
          elif cmd == 'close':
              remote.close()
              break
          elif cmd == "seed":
              env.seed(data)
          elif cmd == 'get_spaces':
              remote.send((env.observation_space, env.action_space))
          else:
              raise NotImplementedError
  
  class CloudpickleWrapper(object):
      """
      Uses cloudpickle to serialize contents (otherwise multiprocessing tries to use pickle)
      """
      def __init__(self, x):
          self.x = x
      def __getstate__(self):
          import cloudpickle
          return cloudpickle.dumps(self.x)
      def __setstate__(self, ob):
          import pickle
          self.x = pickle.loads(ob)
          
  
  class VecEnv(object):
      """
      An abstract asynchronous, vectorized environment.
      """
      def __init__(self, num_envs, observation_space, action_space):
          self.num_envs = num_envs
          self.observation_space = observation_space
          self.action_space = action_space
  
      def reset(self):
          """
          Reset all the environments and return an array of
          observations, or a tuple of observation arrays.
          If step_async is still doing work, that work will
          be cancelled and step_wait() should not be called
          until step_async() is invoked again.
          """
          pass
  
      def step_async(self, actions):
          """
          Tell all the environments to start taking a step
          with the given actions.
          Call step_wait() to get the results of the step.
          You should not call this if a step_async run is
          already pending.
          """
          pass
  
      def step_wait(self):
          """
          Wait for the step taken with step_async().
          Returns (obs, rews, dones, infos):
           - obs: an array of observations, or a tuple of
                  arrays of observations.
           - rews: an array of rewards
           - dones: an array of "episode done" booleans
           - infos: a sequence of info objects
          """
          pass
  
      def close(self):
          """
          Clean up the environments' resources.
          """
          pass
  
      def step(self, actions):
          self.step_async(actions)
          return self.step_wait()
  
  class SubprocVecEnv(VecEnv):
      def __init__(self, env_fns, spaces=None):
          """
          envs: list of gym environments to run in subprocesses
          """
          self.waiting = False
          self.closed = False
          nenvs = len(env_fns)
          self.nenvs = nenvs
          self.remotes, self.work_remotes = zip(*[Pipe() for _ in range(nenvs)])
          self.ps = [Process(target=worker, args=(work_remote, remote, CloudpickleWrapper(env_fn)))
              for (work_remote, remote, env_fn) in zip(self.work_remotes, self.remotes, env_fns)]
          for p in self.ps:
              p.daemon = True # if the main process crashes, we should not cause things to hang
              p.start()
          for remote in self.work_remotes:
              remote.close()
  
          self.remotes[0].send(('get_spaces', None))
          observation_space, action_space = self.remotes[0].recv()
          VecEnv.__init__(self, len(env_fns), observation_space, action_space)
  
      def step_async(self, actions):
          for remote, action in zip(self.remotes, actions):
              remote.send(('step', action))
          self.waiting = True
  
      def step_wait(self):
          results = [remote.recv() for remote in self.remotes]
          self.waiting = False
          obs, rews, dones, infos = zip(*results)
          return np.stack(obs), np.stack(rews), np.stack(dones), infos
  
      def reset(self):
          for remote in self.remotes:
              remote.send(('reset', None))
          return np.stack([remote.recv() for remote in self.remotes])
  
      def reset_task(self):
          for remote in self.remotes:
              remote.send(('reset_task', None))
          return np.stack([remote.recv() for remote in self.remotes])
      def seed(self, seed):
          for idx, remote in enumerate(self.remotes):
              remote.send(("seed", seed+idx))
  
      def close(self):
          if self.closed:
              return
          if self.waiting:
              for remote in self.remotes:            
                  remote.recv()
          for remote in self.remotes:
              remote.send(('close', None))
          for p in self.ps:
              p.join()
              self.closed = True
              
      def __len__(self):
          return self.nenvs