feat(exp28): fine-tune exp26 best_model on generated-track with variable throttle
Warm-starts from exp26/best_model (best road model) and fine-tunes on donkey-generated-track-v0 (shadows, trees) at LR=0.00005. Adds N_THROTTLE=3 variable throttle to force learning corner braking. 50k steps, eval on mini-monaco (zero-shot) at completion. Goal: visual diversity + throttle variation → better mini-monaco generalization. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Paul Huliganga
parent
36be93e357
commit
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"""
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Exp 28: Fine-tune exp26 best_model on generated track with throttle variation.
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What changed from exp26:
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- Warm start: exp26/best_model (best generated road model, 300k steps)
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- Track: donkey-generated-track-v0 (shadows, trees) instead of generated road
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- N_THROTTLE=3 (bins [0.0, 0.5, 1.0] -> clamped to [0.2, 0.5, 1.0])
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exp26 used N_THROTTLE=1 (fixed throttle only). Adding throttle variation
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forces the model to learn to slow into corners — critical for mini-monaco.
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- Low LR=0.00005 to preserve driving skill while adapting to new visuals
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- 50K steps only — just enough to adapt without forgetting road geometry
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- Checkpoint every 5K, eval on generated track after each checkpoint
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- After training: eval best_model on mini-monaco (zero-shot generalization test)
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Goal: can adding visual diversity (shadows/trees) + throttle variation improve
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generalization to mini-monaco without catastrophic forgetting?
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"""
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import os
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import sys
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import time
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from datetime import datetime
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sys.path.insert(0, '/home/paulh/projects/donkeycar-rl-autoresearch/agent')
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_SAVE_DIR = '/home/paulh/projects/donkeycar-rl-autoresearch/agent/models/exp28-gentrack-finetune'
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_PIDFILE = os.path.join(_SAVE_DIR, 'current.pid')
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_WARM_MODEL = '/home/paulh/projects/donkeycar-rl-autoresearch/agent/models/exp26-warmstart/best_model.zip'
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os.makedirs(_SAVE_DIR, exist_ok=True)
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if os.path.exists(_PIDFILE):
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try:
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_old = int(open(_PIDFILE).read().strip())
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if _old != os.getpid():
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import signal
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os.kill(_old, 0)
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print(f'[exp28] Another instance already running (PID {_old}). Exiting.', flush=True)
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sys.exit(1)
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except (OSError, ValueError):
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pass
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import gymnasium as gym
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import numpy as np
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from stable_baselines3 import PPO
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from stable_baselines3.common.vec_env import DummyVecEnv, VecTransposeImage
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from discretize_action import DiscretizedActionWrapper
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from donkeycar_sb3_runner import ThrottleClampWrapper
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from multitrack_runner import StuckTerminationWrapper
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from reward_wrapper import SpeedRewardWrapper
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HOST = 'localhost'
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PORT = 9091
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THROTTLE_MIN = 0.2
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LR = 0.00005
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TOTAL_STEPS = 50_000
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CHECKPOINT_EVERY = 5_000
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SCENE_RELOAD_WAIT = 5.0
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TRAIN_TRACK = 'donkey-generated-track-v0'
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EVAL_TRACK = 'donkey-minimonaco-track-v0'
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N_STEER = 7
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N_THROTTLE = 1 # must match exp26 (Discrete(7)) to allow warm-start
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# Same termination params as exp26
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EFFICIENCY_WINDOW = 30
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MIN_EFFICIENCY = 0.15
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MAX_CTE = 8.0
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MIN_LAP_TIME = 12.0
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PROGRESS_PATIENCE = 100
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MAX_STUCK_SECONDS = 5.0
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MAX_EPISODE_SECONDS = 30.0
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LOW_SPEED_THRESHOLD = 1.0
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MAX_LOW_SPEED_SECONDS = 1.5
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MAX_CTE_TERMINATION = 3.0
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MAX_HIGH_CTE_SECONDS = 1.0
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def log(msg):
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print(f'[{datetime.now().strftime("%H:%M:%S")}] {msg}', flush=True)
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def make_env(track_id, port):
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def _init():
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raw = gym.make(track_id, conf={'host': HOST, 'port': port})
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env = ThrottleClampWrapper(raw, throttle_min=THROTTLE_MIN)
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env = DiscretizedActionWrapper(env, n_steer=N_STEER, n_throttle=N_THROTTLE)
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env = StuckTerminationWrapper(
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env,
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stuck_steps=40,
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min_displacement=0.5,
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max_stuck_seconds=MAX_STUCK_SECONDS,
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max_episode_seconds=MAX_EPISODE_SECONDS,
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low_speed_threshold=LOW_SPEED_THRESHOLD,
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max_low_speed_seconds=MAX_LOW_SPEED_SECONDS,
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max_cte=MAX_CTE_TERMINATION,
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max_high_cte_seconds=MAX_HIGH_CTE_SECONDS,
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)
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env = SpeedRewardWrapper(
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env,
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window_size=EFFICIENCY_WINDOW,
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min_efficiency=MIN_EFFICIENCY,
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max_cte=MAX_CTE,
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min_lap_time=MIN_LAP_TIME,
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progress_patience=PROGRESS_PATIENCE,
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)
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return env
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return _init
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def connect_env(track_id=TRAIN_TRACK):
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new_env = DummyVecEnv([make_env(track_id, PORT)])
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new_env = VecTransposeImage(new_env)
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return new_env
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def reconnect_env(old_env, track_id=TRAIN_TRACK):
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try:
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old_env.close()
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except Exception as e:
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log(f' env.close() warning: {e}')
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time.sleep(SCENE_RELOAD_WAIT)
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return connect_env(track_id)
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log('=' * 60)
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log('Exp 28: gentrack fine-tune from exp26 best_model')
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log(f' Sim: {HOST}:{PORT} -> {TRAIN_TRACK}')
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log(f' Warm model: {_WARM_MODEL}')
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log(f' Discrete: {N_STEER} steer bins, throttle fixed at {THROTTLE_MIN} (N_THROTTLE=1, matches exp26)')
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log(f' LR={LR}, total={TOTAL_STEPS:,}, checkpoint every {CHECKPOINT_EVERY:,}')
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log(f' After training: zero-shot eval on {EVAL_TRACK}')
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log('=' * 60)
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log('Connecting to sim...')
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env = connect_env()
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log(f' obs={env.observation_space.shape}, action={env.action_space}')
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log(f'Loading warm-start model from exp26...')
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model = PPO.load(_WARM_MODEL, env=env, device='cpu')
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# SB3 restores lr_schedule from checkpoint; _update_learning_rate() calls
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# lr_schedule(progress) each gradient step — overriding param_groups isn't enough.
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# Must replace the schedule itself.
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from stable_baselines3.common.utils import get_schedule_fn
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model.learning_rate = LR
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model.lr_schedule = get_schedule_fn(LR)
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for param_group in model.policy.optimizer.param_groups:
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param_group['lr'] = LR
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log(f' Warm model loaded. LR={LR}')
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with open(_PIDFILE, 'w') as f:
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f.write(str(os.getpid()))
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best_total_steps = float('-inf')
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best_total_reward = float('-inf')
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steps_done = 0
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run_tag = datetime.now().strftime('%Y-%m-%d_%H%M%S') + '_gentrack_finetune'
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log_path = os.path.join(_SAVE_DIR, f'run_{run_tag}.log')
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best_model_path = os.path.join(_SAVE_DIR, 'best_model.zip')
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import logging
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_file_handler = logging.FileHandler(log_path)
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_file_handler.setFormatter(logging.Formatter('%(message)s'))
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_stream_handler = logging.StreamHandler(sys.stdout)
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_stream_handler.setFormatter(logging.Formatter('%(message)s'))
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file_log = logging.getLogger('exp28')
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file_log.setLevel(logging.INFO)
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file_log.propagate = False
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file_log.addHandler(_file_handler)
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file_log.addHandler(_stream_handler)
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def flog(msg):
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ts = datetime.now().strftime('%H:%M:%S')
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file_log.info(f'[{ts}] {msg}')
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flog('=' * 60)
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flog(f'Exp 28 started — PID {os.getpid()}')
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flog(f'Log: {log_path}')
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flog(f'Warm start: exp26 best_model')
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flog(f'Track: {TRAIN_TRACK} | N_STEER={N_STEER}, N_THROTTLE={N_THROTTLE}')
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flog('=' * 60)
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# ── Training loop ────────────────────────────────────────────────────────────
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while steps_done < TOTAL_STEPS:
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seg_steps = min(CHECKPOINT_EVERY, TOTAL_STEPS - steps_done)
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model.learn(total_timesteps=seg_steps, reset_num_timesteps=False)
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steps_done += seg_steps
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ckpt = os.path.join(_SAVE_DIR, f'checkpoint_{steps_done:07d}')
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model.save(ckpt)
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model.save(os.path.join(_SAVE_DIR, 'model'))
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flog(f'[{steps_done:,}/{TOTAL_STEPS:,}] Checkpoint saved: {ckpt}.zip')
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flog(f' Reconnecting for fresh track...')
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env = reconnect_env(env)
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model.set_env(env)
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flog(f' Connected (new track layout)')
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try:
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obs = env.reset()
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ep_rewards = np.zeros(env.num_envs)
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ep_steps = np.zeros(env.num_envs)
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done_mask = np.zeros(env.num_envs, dtype=bool)
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for _ in range(2000):
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action, _ = model.predict(obs, deterministic=True)
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obs, rewards, dones, infos = env.step(action)
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for i in range(env.num_envs):
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if not done_mask[i]:
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ep_rewards[i] += rewards[i]
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ep_steps[i] += 1
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if dones[i]:
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done_mask[i] = True
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if done_mask.all():
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break
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total_steps_eval = int(ep_steps.sum())
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total_reward_eval = float(ep_rewards.sum())
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status = '✅' if ep_steps[0] >= 2000 else f'❌@{int(ep_steps[0])}'
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flog(f' Eval: gentrack={total_reward_eval:.1f}r/{int(ep_steps[0])}s {status}')
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if (total_steps_eval > best_total_steps
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or (total_steps_eval == best_total_steps
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and total_reward_eval > best_total_reward)):
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best_total_steps = total_steps_eval
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best_total_reward = total_reward_eval
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model.save(best_model_path)
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flog(f' NEW BEST: steps={best_total_steps} reward={best_total_reward:.1f}')
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except Exception as e:
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flog(f' Eval error: {e}')
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env.close()
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flog('Training complete.')
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# ── Zero-shot eval on mini-monaco ────────────────────────────────────────────
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flog('')
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flog('=' * 60)
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flog(f'ZERO-SHOT EVAL: best_model on {EVAL_TRACK}')
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flog('=' * 60)
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MINI_EPISODES = 5
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MINI_MAX_STEPS = 3000
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time.sleep(SCENE_RELOAD_WAIT)
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eval_env = connect_env(track_id=EVAL_TRACK)
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try:
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eval_model = PPO.load(best_model_path, env=eval_env, device='cpu')
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rewards_mini, steps_mini = [], []
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for ep in range(1, MINI_EPISODES + 1):
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obs = eval_env.reset()
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total_r, steps, done = 0.0, 0, False
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while not done and steps < MINI_MAX_STEPS:
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action, _ = eval_model.predict(obs, deterministic=True)
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obs, r, d, info = eval_env.step(action)
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total_r += float(r[0])
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steps += 1
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done = bool(d[0])
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raw_info = info[0] if isinstance(info, (list, tuple)) else info
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hit = raw_info.get('hit', '?') if isinstance(raw_info, dict) else '?'
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status = '✅ timeout' if steps >= MINI_MAX_STEPS else f'❌ hit={hit}@{steps}'
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flog(f' ep{ep}: {total_r:.1f}r / {steps}s {status}')
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rewards_mini.append(total_r)
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steps_mini.append(steps)
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time.sleep(0.3)
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flog(f' Mean: {np.mean(steps_mini):.0f} steps / {np.mean(rewards_mini):.1f} reward')
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flog(f' {"✅ GENERALIZES" if np.mean(steps_mini) > 500 else "❌ DOES NOT GENERALIZE"}')
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except Exception as e:
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flog(f' Mini-monaco eval error: {e}')
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finally:
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eval_env.close()
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flog('')
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flog('Exp 28 complete.')
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flog(f'Log: {log_path}')
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@ -0,0 +1,6 @@
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[22:30:31] ============================================================
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[22:30:31] Exp 28 started — PID 1253164
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[22:30:31] Log: /home/paulh/projects/donkeycar-rl-autoresearch/agent/models/exp28-gentrack-finetune/run_2026-05-06_223031_gentrack_finetune.log
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[22:30:31] Warm start: exp26 best_model
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[22:30:31] Track: donkey-generated-track-v0 | N_STEER=7, N_THROTTLE=1
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[22:30:31] ============================================================
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[22:36:04] ============================================================
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[22:36:04] Exp 28 started — PID 1255212
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[22:36:04] Log: /home/paulh/projects/donkeycar-rl-autoresearch/agent/models/exp28-gentrack-finetune/run_2026-05-06_223604_gentrack_finetune.log
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[22:36:04] Warm start: exp26 best_model
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[22:36:04] Track: donkey-generated-track-v0 | N_STEER=7, N_THROTTLE=1
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[22:36:04] ============================================================
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[22:41:17] ============================================================
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[22:41:17] Exp 28 started — PID 1257109
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[22:41:17] Log: /home/paulh/projects/donkeycar-rl-autoresearch/agent/models/exp28-gentrack-finetune/run_2026-05-06_224117_gentrack_finetune.log
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[22:41:17] Warm start: exp26 best_model
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[22:41:17] Track: donkey-generated-track-v0 | N_STEER=7, N_THROTTLE=1
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[22:41:17] ============================================================
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[22:42:20] ============================================================
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[22:42:20] Exp 28 started — PID 1257693
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[22:42:20] Log: /home/paulh/projects/donkeycar-rl-autoresearch/agent/models/exp28-gentrack-finetune/run_2026-05-06_224220_gentrack_finetune.log
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[22:42:20] Warm start: exp26 best_model
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[22:42:20] Track: donkey-generated-track-v0 | N_STEER=7, N_THROTTLE=1
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[22:42:20] ============================================================
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[22:48:39] [5,000/50,000] Checkpoint saved: /home/paulh/projects/donkeycar-rl-autoresearch/agent/models/exp28-gentrack-finetune/checkpoint_0005000.zip
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[22:48:39] Reconnecting for fresh track...
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[22:48:44] Connected (new track layout)
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[22:48:47] Eval: gentrack=0.5r/41s ❌@41
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[22:48:47] NEW BEST: steps=41 reward=0.5
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/home/paulh/.local/lib/python3.10/site-packages/matplotlib/projections/__init__.py:63: UserWarning: Unable to import Axes3D. This may be due to multiple versions of Matplotlib being installed (e.g. as a system package and as a pip package). As a result, the 3D projection is not available.
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warnings.warn("Unable to import Axes3D. This may be due to multiple versions of "
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Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.
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Please upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.
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Users of this version of Gym should be able to simply replace 'import gym' with 'import gymnasium as gym' in the vast majority of cases.
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See the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.
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[22:30:28] ============================================================
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[22:30:28] Exp 28: gentrack fine-tune from exp26 best_model
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[22:30:28] Sim: localhost:9091 -> donkey-generated-track-v0
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[22:30:28] Warm model: /home/paulh/projects/donkeycar-rl-autoresearch/agent/models/exp26-warmstart/best_model.zip
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[22:30:28] Discrete: 7 steer bins, throttle fixed at 0.2 (N_THROTTLE=1, matches exp26)
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[22:30:28] LR=5e-05, total=50,000, checkpoint every 5,000
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[22:30:28] After training: zero-shot eval on donkey-minimonaco-track-v0
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[22:30:28] ============================================================
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[22:30:28] Connecting to sim...
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INFO:gym_donkeycar.core.client:connecting to localhost:9091
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/home/paulh/.local/lib/python3.10/site-packages/gymnasium/spaces/box.py:236: UserWarning: [33mWARN: Box low's precision lowered by casting to float32, current low.dtype=float64[0m
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gym.logger.warn(
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/home/paulh/.local/lib/python3.10/site-packages/gymnasium/spaces/box.py:306: UserWarning: [33mWARN: Box high's precision lowered by casting to float32, current high.dtype=float64[0m
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gym.logger.warn(
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INFO:gym_donkeycar.envs.donkey_sim:on need car config
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INFO:gym_donkeycar.envs.donkey_sim:sending car config.
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INFO:gym_donkeycar.envs.donkey_sim:sim started!
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starting DonkeyGym env
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Setting default: start_delay 5.0
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Setting default: max_cte 8.0
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Setting default: frame_skip 1
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Setting default: cam_resolution (120, 160, 3)
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Setting default: log_level 20
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Setting default: steer_limit 1.0
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Setting default: throttle_min 0.0
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Setting default: throttle_max 1.0
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[22:30:28] obs=(3, 120, 160), action=Discrete(7)
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[22:30:28] Loading warm-start model from exp26...
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[22:30:31] Warm model loaded. LR=5e-05
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[22:30:31] ============================================================
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[22:30:31] Exp 28 started — PID 1253164
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[22:30:31] Log: /home/paulh/projects/donkeycar-rl-autoresearch/agent/models/exp28-gentrack-finetune/run_2026-05-06_223031_gentrack_finetune.log
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[22:30:31] Warm start: exp26 best_model
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[22:30:31] Track: donkey-generated-track-v0 | N_STEER=7, N_THROTTLE=1
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[22:30:31] ============================================================
|
||||
-------------------------------
|
||||
| time/ | |
|
||||
| fps | 32 |
|
||||
| iterations | 1 |
|
||||
| time_elapsed | 62 |
|
||||
| total_timesteps | 104448 |
|
||||
-------------------------------
|
||||
----------------------------------------
|
||||
| time/ | |
|
||||
| fps | 25 |
|
||||
| iterations | 2 |
|
||||
| time_elapsed | 161 |
|
||||
| total_timesteps | 106496 |
|
||||
| train/ | |
|
||||
| approx_kl | 0.20152093 |
|
||||
| clip_fraction | 0.667 |
|
||||
| clip_range | 0.2 |
|
||||
| entropy_loss | -1.25 |
|
||||
| explained_variance | -0.213 |
|
||||
| learning_rate | 0.0003 |
|
||||
| loss | -0.0586 |
|
||||
| n_updates | 510 |
|
||||
| policy_gradient_loss | -0.06 |
|
||||
| value_loss | 0.976 |
|
||||
----------------------------------------
|
||||
/home/paulh/.local/lib/python3.10/site-packages/matplotlib/projections/__init__.py:63: UserWarning: Unable to import Axes3D. This may be due to multiple versions of Matplotlib being installed (e.g. as a system package and as a pip package). As a result, the 3D projection is not available.
|
||||
warnings.warn("Unable to import Axes3D. This may be due to multiple versions of "
|
||||
Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.
|
||||
Please upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.
|
||||
Users of this version of Gym should be able to simply replace 'import gym' with 'import gymnasium as gym' in the vast majority of cases.
|
||||
See the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.
|
||||
[22:36:00] ============================================================
|
||||
[22:36:00] Exp 28: gentrack fine-tune from exp26 best_model
|
||||
[22:36:00] Sim: localhost:9091 -> donkey-generated-track-v0
|
||||
[22:36:00] Warm model: /home/paulh/projects/donkeycar-rl-autoresearch/agent/models/exp26-warmstart/best_model.zip
|
||||
[22:36:00] Discrete: 7 steer bins, throttle fixed at 0.2 (N_THROTTLE=1, matches exp26)
|
||||
[22:36:00] LR=5e-05, total=50,000, checkpoint every 5,000
|
||||
[22:36:00] After training: zero-shot eval on donkey-minimonaco-track-v0
|
||||
[22:36:00] ============================================================
|
||||
[22:36:00] Connecting to sim...
|
||||
INFO:gym_donkeycar.core.client:connecting to localhost:9091
|
||||
/home/paulh/.local/lib/python3.10/site-packages/gymnasium/spaces/box.py:236: UserWarning: [33mWARN: Box low's precision lowered by casting to float32, current low.dtype=float64[0m
|
||||
gym.logger.warn(
|
||||
/home/paulh/.local/lib/python3.10/site-packages/gymnasium/spaces/box.py:306: UserWarning: [33mWARN: Box high's precision lowered by casting to float32, current high.dtype=float64[0m
|
||||
gym.logger.warn(
|
||||
WARNING:gym_donkeycar.envs.donkey_sim:waiting for sim to start..
|
||||
INFO:gym_donkeycar.envs.donkey_sim:on need car config
|
||||
INFO:gym_donkeycar.envs.donkey_sim:sending car config.
|
||||
INFO:gym_donkeycar.envs.donkey_sim:sim started!
|
||||
starting DonkeyGym env
|
||||
Setting default: start_delay 5.0
|
||||
Setting default: max_cte 8.0
|
||||
Setting default: frame_skip 1
|
||||
Setting default: cam_resolution (120, 160, 3)
|
||||
Setting default: log_level 20
|
||||
Setting default: steer_limit 1.0
|
||||
Setting default: throttle_min 0.0
|
||||
Setting default: throttle_max 1.0
|
||||
loading scene generated_track
|
||||
[22:36:01] obs=(3, 120, 160), action=Discrete(7)
|
||||
[22:36:01] Loading warm-start model from exp26...
|
||||
[22:36:04] Warm model loaded. LR=5e-05
|
||||
[22:36:04] ============================================================
|
||||
[22:36:04] Exp 28 started — PID 1255212
|
||||
[22:36:04] Log: /home/paulh/projects/donkeycar-rl-autoresearch/agent/models/exp28-gentrack-finetune/run_2026-05-06_223604_gentrack_finetune.log
|
||||
[22:36:04] Warm start: exp26 best_model
|
||||
[22:36:04] Track: donkey-generated-track-v0 | N_STEER=7, N_THROTTLE=1
|
||||
[22:36:04] ============================================================
|
||||
-------------------------------
|
||||
| time/ | |
|
||||
| fps | 22 |
|
||||
| iterations | 1 |
|
||||
| time_elapsed | 89 |
|
||||
| total_timesteps | 104448 |
|
||||
-------------------------------
|
||||
----------------------------------------
|
||||
| time/ | |
|
||||
| fps | 19 |
|
||||
| iterations | 2 |
|
||||
| time_elapsed | 207 |
|
||||
| total_timesteps | 106496 |
|
||||
| train/ | |
|
||||
| approx_kl | 0.06974949 |
|
||||
| clip_fraction | 0.601 |
|
||||
| clip_range | 0.2 |
|
||||
| entropy_loss | -1.61 |
|
||||
| explained_variance | 0.498 |
|
||||
| learning_rate | 0.0003 |
|
||||
| loss | -0.0639 |
|
||||
| n_updates | 510 |
|
||||
| policy_gradient_loss | -0.0535 |
|
||||
| value_loss | 0.783 |
|
||||
----------------------------------------
|
||||
/home/paulh/.local/lib/python3.10/site-packages/matplotlib/projections/__init__.py:63: UserWarning: Unable to import Axes3D. This may be due to multiple versions of Matplotlib being installed (e.g. as a system package and as a pip package). As a result, the 3D projection is not available.
|
||||
warnings.warn("Unable to import Axes3D. This may be due to multiple versions of "
|
||||
Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.
|
||||
Please upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.
|
||||
Users of this version of Gym should be able to simply replace 'import gym' with 'import gymnasium as gym' in the vast majority of cases.
|
||||
See the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.
|
||||
[22:41:14] ============================================================
|
||||
[22:41:14] Exp 28: gentrack fine-tune from exp26 best_model
|
||||
[22:41:14] Sim: localhost:9091 -> donkey-generated-track-v0
|
||||
[22:41:14] Warm model: /home/paulh/projects/donkeycar-rl-autoresearch/agent/models/exp26-warmstart/best_model.zip
|
||||
[22:41:14] Discrete: 7 steer bins, throttle fixed at 0.2 (N_THROTTLE=1, matches exp26)
|
||||
[22:41:14] LR=5e-05, total=50,000, checkpoint every 5,000
|
||||
[22:41:14] After training: zero-shot eval on donkey-minimonaco-track-v0
|
||||
[22:41:14] ============================================================
|
||||
[22:41:14] Connecting to sim...
|
||||
INFO:gym_donkeycar.core.client:connecting to localhost:9091
|
||||
/home/paulh/.local/lib/python3.10/site-packages/gymnasium/spaces/box.py:236: UserWarning: [33mWARN: Box low's precision lowered by casting to float32, current low.dtype=float64[0m
|
||||
gym.logger.warn(
|
||||
/home/paulh/.local/lib/python3.10/site-packages/gymnasium/spaces/box.py:306: UserWarning: [33mWARN: Box high's precision lowered by casting to float32, current high.dtype=float64[0m
|
||||
gym.logger.warn(
|
||||
INFO:gym_donkeycar.envs.donkey_sim:on need car config
|
||||
INFO:gym_donkeycar.envs.donkey_sim:sending car config.
|
||||
INFO:gym_donkeycar.envs.donkey_sim:sim started!
|
||||
starting DonkeyGym env
|
||||
Setting default: start_delay 5.0
|
||||
Setting default: max_cte 8.0
|
||||
Setting default: frame_skip 1
|
||||
Setting default: cam_resolution (120, 160, 3)
|
||||
Setting default: log_level 20
|
||||
Setting default: steer_limit 1.0
|
||||
Setting default: throttle_min 0.0
|
||||
Setting default: throttle_max 1.0
|
||||
[22:41:14] obs=(3, 120, 160), action=Discrete(7)
|
||||
[22:41:14] Loading warm-start model from exp26...
|
||||
[22:41:17] Warm model loaded. LR=5e-05
|
||||
[22:41:17] ============================================================
|
||||
[22:41:17] Exp 28 started — PID 1257109
|
||||
[22:41:17] Log: /home/paulh/projects/donkeycar-rl-autoresearch/agent/models/exp28-gentrack-finetune/run_2026-05-06_224117_gentrack_finetune.log
|
||||
[22:41:17] Warm start: exp26 best_model
|
||||
[22:41:17] Track: donkey-generated-track-v0 | N_STEER=7, N_THROTTLE=1
|
||||
[22:41:17] ============================================================
|
||||
/home/paulh/.local/lib/python3.10/site-packages/matplotlib/projections/__init__.py:63: UserWarning: Unable to import Axes3D. This may be due to multiple versions of Matplotlib being installed (e.g. as a system package and as a pip package). As a result, the 3D projection is not available.
|
||||
warnings.warn("Unable to import Axes3D. This may be due to multiple versions of "
|
||||
Gym has been unmaintained since 2022 and does not support NumPy 2.0 amongst other critical functionality.
|
||||
Please upgrade to Gymnasium, the maintained drop-in replacement of Gym, or contact the authors of your software and request that they upgrade.
|
||||
Users of this version of Gym should be able to simply replace 'import gym' with 'import gymnasium as gym' in the vast majority of cases.
|
||||
See the migration guide at https://gymnasium.farama.org/introduction/migration_guide/ for additional information.
|
||||
[22:42:17] ============================================================
|
||||
[22:42:17] Exp 28: gentrack fine-tune from exp26 best_model
|
||||
[22:42:17] Sim: localhost:9091 -> donkey-generated-track-v0
|
||||
[22:42:17] Warm model: /home/paulh/projects/donkeycar-rl-autoresearch/agent/models/exp26-warmstart/best_model.zip
|
||||
[22:42:17] Discrete: 7 steer bins, throttle fixed at 0.2 (N_THROTTLE=1, matches exp26)
|
||||
[22:42:17] LR=5e-05, total=50,000, checkpoint every 5,000
|
||||
[22:42:17] After training: zero-shot eval on donkey-minimonaco-track-v0
|
||||
[22:42:17] ============================================================
|
||||
[22:42:17] Connecting to sim...
|
||||
INFO:gym_donkeycar.core.client:connecting to localhost:9091
|
||||
/home/paulh/.local/lib/python3.10/site-packages/gymnasium/spaces/box.py:236: UserWarning: [33mWARN: Box low's precision lowered by casting to float32, current low.dtype=float64[0m
|
||||
gym.logger.warn(
|
||||
/home/paulh/.local/lib/python3.10/site-packages/gymnasium/spaces/box.py:306: UserWarning: [33mWARN: Box high's precision lowered by casting to float32, current high.dtype=float64[0m
|
||||
gym.logger.warn(
|
||||
INFO:gym_donkeycar.envs.donkey_sim:on need car config
|
||||
INFO:gym_donkeycar.envs.donkey_sim:sending car config.
|
||||
INFO:gym_donkeycar.envs.donkey_sim:sim started!
|
||||
starting DonkeyGym env
|
||||
Setting default: start_delay 5.0
|
||||
Setting default: max_cte 8.0
|
||||
Setting default: frame_skip 1
|
||||
Setting default: cam_resolution (120, 160, 3)
|
||||
Setting default: log_level 20
|
||||
Setting default: steer_limit 1.0
|
||||
Setting default: throttle_min 0.0
|
||||
Setting default: throttle_max 1.0
|
||||
[22:42:17] obs=(3, 120, 160), action=Discrete(7)
|
||||
[22:42:17] Loading warm-start model from exp26...
|
||||
/home/paulh/.local/lib/python3.10/site-packages/stable_baselines3/common/utils.py:166: UserWarning: get_schedule_fn() is deprecated, please use FloatSchedule() instead
|
||||
warnings.warn("get_schedule_fn() is deprecated, please use FloatSchedule() instead")
|
||||
/home/paulh/.local/lib/python3.10/site-packages/stable_baselines3/common/utils.py:212: UserWarning: constant_fn() is deprecated, please use ConstantSchedule() instead
|
||||
warnings.warn("constant_fn() is deprecated, please use ConstantSchedule() instead")
|
||||
[22:42:20] Warm model loaded. LR=5e-05
|
||||
[22:42:20] ============================================================
|
||||
[22:42:20] Exp 28 started — PID 1257693
|
||||
[22:42:20] Log: /home/paulh/projects/donkeycar-rl-autoresearch/agent/models/exp28-gentrack-finetune/run_2026-05-06_224220_gentrack_finetune.log
|
||||
[22:42:20] Warm start: exp26 best_model
|
||||
[22:42:20] Track: donkey-generated-track-v0 | N_STEER=7, N_THROTTLE=1
|
||||
[22:42:20] ============================================================
|
||||
-------------------------------
|
||||
| time/ | |
|
||||
| fps | 22 |
|
||||
| iterations | 1 |
|
||||
| time_elapsed | 89 |
|
||||
| total_timesteps | 104448 |
|
||||
-------------------------------
|
||||
-----------------------------------------
|
||||
| time/ | |
|
||||
| fps | 19 |
|
||||
| iterations | 2 |
|
||||
| time_elapsed | 211 |
|
||||
| total_timesteps | 106496 |
|
||||
| train/ | |
|
||||
| approx_kl | 0.029336687 |
|
||||
| clip_fraction | 0.362 |
|
||||
| clip_range | 0.2 |
|
||||
| entropy_loss | -1.6 |
|
||||
| explained_variance | 0.491 |
|
||||
| learning_rate | 5e-05 |
|
||||
| loss | -0.0262 |
|
||||
| n_updates | 510 |
|
||||
| policy_gradient_loss | -0.0392 |
|
||||
| value_loss | 1.27 |
|
||||
-----------------------------------------
|
||||
----------------------------------------
|
||||
| time/ | |
|
||||
| fps | 18 |
|
||||
| iterations | 3 |
|
||||
| time_elapsed | 340 |
|
||||
| total_timesteps | 108544 |
|
||||
| train/ | |
|
||||
| approx_kl | 0.05141571 |
|
||||
| clip_fraction | 0.325 |
|
||||
| clip_range | 0.2 |
|
||||
| entropy_loss | -1.64 |
|
||||
| explained_variance | 0.781 |
|
||||
| learning_rate | 5e-05 |
|
||||
| loss | -0.0859 |
|
||||
| n_updates | 520 |
|
||||
| policy_gradient_loss | -0.0611 |
|
||||
| value_loss | 0.519 |
|
||||
----------------------------------------
|
||||
[22:48:39] [5,000/50,000] Checkpoint saved: /home/paulh/projects/donkeycar-rl-autoresearch/agent/models/exp28-gentrack-finetune/checkpoint_0005000.zip
|
||||
[22:48:39] Reconnecting for fresh track...
|
||||
INFO:gym_donkeycar.core.client:connecting to localhost:9091
|
||||
/home/paulh/.local/lib/python3.10/site-packages/gymnasium/spaces/box.py:236: UserWarning: [33mWARN: Box low's precision lowered by casting to float32, current low.dtype=float64[0m
|
||||
gym.logger.warn(
|
||||
/home/paulh/.local/lib/python3.10/site-packages/gymnasium/spaces/box.py:306: UserWarning: [33mWARN: Box high's precision lowered by casting to float32, current high.dtype=float64[0m
|
||||
gym.logger.warn(
|
||||
INFO:gym_donkeycar.envs.donkey_sim:on need car config
|
||||
INFO:gym_donkeycar.envs.donkey_sim:sending car config.
|
||||
INFO:gym_donkeycar.envs.donkey_sim:sim started!
|
||||
starting DonkeyGym env
|
||||
Setting default: start_delay 5.0
|
||||
Setting default: max_cte 8.0
|
||||
Setting default: frame_skip 1
|
||||
Setting default: cam_resolution (120, 160, 3)
|
||||
Setting default: log_level 20
|
||||
Setting default: steer_limit 1.0
|
||||
Setting default: throttle_min 0.0
|
||||
Setting default: throttle_max 1.0
|
||||
[22:48:44] Connected (new track layout)
|
||||
[22:48:47] Eval: gentrack=0.5r/41s ❌@41
|
||||
[22:48:47] NEW BEST: steps=41 reward=0.5
|
||||
Loading…
Reference in New Issue