Added a simple benchmark script

example.py → benchmark.py

@@ -2,11 +2,15 @@ import gym
 import gym_stirap
 import numpy as np
 
+import time 
+
 env = gym.make('stirap-v0')
 
 reward = np.zeros(env.timesteps)
+env.reset()
+
+tic = time.process_time()
 for t in range(env.timesteps):
-    env.render()
 
     # Perform a random action
     action = env.action_space.sample()
@@ -16,4 +20,6 @@ for t in range(env.timesteps):
         print("Episode finished after {} timesteps".format(t+1))
         break
 
+toc = time.process_time()
 print("Score: ", np.sum(reward))
+print("Elapsed time: {} s".format(toc - tic))
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