Implement train_pybullet_racecar.py and enjoy_pybullet_racecar.py using OpenAI baselines DQN for the RacecarGymEnv.

examples/pybullet/gym/enjoy_pybullet_racecar.py

@@ -0,0 +1,45 @@
+import gym
+from envs.bullet.racecarGymEnv import RacecarGymEnv
+
+from baselines import deepq
+
+
+def main():
+    
+    env = RacecarGymEnv(render=True)
+    act = deepq.load("racecar_model.pkl")
+    print(act)
+    while True:
+        obs, done = env.reset(), False
+        print("===================================")        
+        print("obs")
+        print(obs)
+        episode_rew = 0
+        while not done:
+            #env.render()
+
+            print("!!!!!!!!!!!!!!!!!!!!!!!!!!")
+            print("obs")
+            print(obs)
+            print("???????????????????????????")
+            print("obs[None]")
+            print(obs[None])
+            o = obs[None]
+            print("o")
+            print(o)
+            aa = act(o)
+            print("aa")
+            print (aa)
+            a = aa[0]
+            print("a")
+            print(a)
+            obs, rew, done, _ = env.step(a)
+            print("===================================")
+            print("obs")
+            print(obs)
+            episode_rew += rew
+        print("Episode reward", episode_rew)
+
+
+if __name__ == '__main__':
+    main()