import argparse import gymnasium as gym import gym_donkeycar import argparse import gymnasium as gym import gym_donkeycar import sys import time from discretize_action import DiscretizedActionWrapper if __name__ == "__main__": parser = argparse.ArgumentParser(description="Run multi-episode RL test loop for DonkeyCar Gym. No model training/saving.") parser.add_argument('--agent', type=str, default='dqn', help='RL agent type (only dqn supported in this runner)') parser.add_argument('--env', type=str, default='donkey-generated-roads-v0', help='Gym/Gymnasium env ID') parser.add_argument('--timesteps', type=int, default=5000, help='Unused (for outer loop compatibility)') parser.add_argument('--eval-episodes', type=int, default=10, help='Episodes for evaluation') parser.add_argument('--log-dir', type=str, default=None, help='Unused (kept for arg compatibility)') parser.add_argument('--seed', type=int, default=None, help='Optional seed') parser.add_argument('--n-steer', type=int, default=3, help='Number of steer bins (DQN only)') parser.add_argument('--n-throttle', type=int, default=3, help='Number of throttle bins (DQN only)') args = parser.parse_args() print('[SB3 Runner] Starting: Connecting to sim…', flush=True) try: env = gym.make(args.env) print(f'[SB3 Runner][MONITOR] Connected to gym env. {time.ctime()}', flush=True) except Exception as e: print(f'[SB3 Runner][MONITOR ALERT] Failed to connect to sim: {str(e)}', flush=True) sys.exit(100) if args.agent == 'dqn': env = DiscretizedActionWrapper(env, n_steer=args.n_steer, n_throttle=args.n_throttle) print(f'[SB3 Runner][MONITOR] Action discretization: steer={args.n_steer}, throttle={args.n_throttle}. {time.ctime()}', flush=True) EPISODES = args.eval_episodes try: ep_rewards = [] for episode in range(EPISODES): ep_reward = 0.0 if args.seed is not None: obs = env.reset(seed=args.seed) else: obs = env.reset() print(f'[SB3 Runner][TEST] Episode {episode+1}/{EPISODES} - reset at {time.ctime()}', flush=True) done = False t = 0 while not done: action = env.action_space.sample() result = env.step(action) if len(result) in (4, 5): if len(result) == 4: obs, reward, done, info = result else: obs, reward, done, truncated, info = result done = done or truncated else: print('[SB3 Runner][MONITOR] UNEXPECTED step() result shape!', flush=True) break ep_reward += reward t += 1 if t % 10 == 0 or done: print(f'[SB3 Runner][TEST] Step {t} done={done} reward={reward} {time.ctime()}', flush=True) if done: print(f'[SB3 Runner][TEST] Episode {episode+1} ended after {t} steps, total_reward={ep_reward} at {time.ctime()}', flush=True) break ep_rewards.append(ep_reward) print(f'[SB3 Runner][TEST] All episode rewards: {ep_rewards}', flush=True) if len(ep_rewards) > 0: print(f'[SB3 Runner][TEST] mean_reward={sum(ep_rewards)/len(ep_rewards):.4f}', flush=True) except Exception as e: print(f'[SB3 Runner][MONITOR ALERT] Exception during episodes: {str(e)} {time.ctime()}', flush=True) sys.exit(102) print(f'[SB3 Runner][MONITOR] Calling env.close() at {time.ctime()}', flush=True) try: env.close() print(f'[SB3 Runner][MONITOR] env.close() complete. {time.ctime()}', flush=True) except Exception as e: print(f'[SB3 Runner][MONITOR ALERT] Exception during env.close(): {str(e)} {time.ctime()}', flush=True) print(f'[SB3 Runner][MONITOR] Waiting 2s before process exit to avoid race. {time.ctime()}', flush=True) time.sleep(2) print(f'[SB3 Runner][MONITOR] Exiting RL runner at {time.ctime()}', flush=True)