text: import gym
  import numpy as np
  from gym.envs.classic_control import rendering
  # from gymgrid.envs.general_grid import *
  from .general_grid import *
  
  def Sample1():
      env = GridWorld(world_width=4, world_height=4, goal_reward=0)
      env.action_space = gym.spaces.Discrete(4)
      env.goal_grid = [(0,3), (3,0)]
      return env
  
  
  def Sample2():
      env = GridWorld(world_width=4, world_height=4, goal_reward=0)
      env.action_space = gym.spaces.Discrete(4)
      env.goal_grid = [(0,3)]
      return env
  
  
  if __name__ == '__main__':
      env = Sample2()
      # nfs = env.observation_space
      # nfa = env.action_space
      # print("nfs:%s; nfa:%s"%(nfs,nfa))
      # print(env.observation_space)
      # print(env.action_space)
      # print(env.state)
      for i_episode in range(20):
          observation = env.reset()
          for t in range(100):
              env.render()
              print(observation)
              action = env.action_space.sample()
              observation, reward, done, info = env.step(action)
              if done:
                  print("Episode finished after {} timesteps".format(t+1))
                  break
      env.close()
      print("env closed")