text: import numpy as np
  from multiprocessing import Process, Pipe
  from rlstudy.common.vec_env import VecEnv, CloudpickleWrapper
  
  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 == 'render':
              remote.send(env.render(mode='rgb_array'))
          elif cmd == 'close':
              remote.close()
              break
          elif cmd == 'get_spaces':
              remote.send((env.observation_space, env.action_space))
          else:
              raise NotImplementedError
  
  
  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.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 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 render(self, mode='human'):
          for pipe in self.remotes:
              pipe.send(('render', None))
          imgs = [pipe.recv() for pipe in self.remotes]
          bigimg = tile_images(imgs)
          if mode == 'human':
              import cv2
              cv2.imshow('vecenv', bigimg[:,:,::-1])
              cv2.waitKey(1)
          elif mode == 'rgb_array':
              return bigimg
          else:
              raise NotImplementedError