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fix: load warm-start with original action space (throttle_min=0.2), then switch env for phase1 throttle

This commit is contained in:
Paul Huliganga 2026-04-19 20:09:08 -04:00
parent bc23a316e0
commit 41d12dede2
1 changed files with 15 additions and 5 deletions
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20
agent/experiments/exp14_finetune_v5.py
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@ -134,19 +134,29 @@ def log(s):
phase_defs = [ (PH1_STEPS, 0.4), (PH2_STEPS, 0.2) ]
# create initial env and model (warm start)
first_throttle = phase_defs[0][1]
env0 = VecTransposeImage(DummyVecEnv([make_env(first_throttle)]))
# Important: load the warm-start model using the SAME action space it was trained with
# (throttle_min=0.2) so we can then switch envs for phase 1 if needed.
loaded_env = VecTransposeImage(DummyVecEnv([make_env(0.2)]))
if os.path.exists(WARM_PATH):
log(f'Loading warm-start model from {WARM_PATH}')
model = PPO.load(WARM_PATH, env=env0, device='cpu')
log(f'Loading warm-start model from {WARM_PATH} using throttle_min=0.2 env')
model = PPO.load(WARM_PATH, env=loaded_env, device='cpu')
# override lr and schedules
model.learning_rate = LR
model.lr_schedule = model.get_schedule_fn(LR) if hasattr(model,'get_schedule_fn') else None
for pg in getattr(getattr(model.policy,'optimizer',None) or [], 'param_groups', []):
pg['lr'] = LR
# Now create the actual training env with the first throttle setting
first_throttle = phase_defs[0][1]
env0 = VecTransposeImage(DummyVecEnv([make_env(first_throttle)]))
if first_throttle != 0.2:
log(f'Switching model to env with throttle_min={first_throttle}')
model.set_env(env0)
else:
log('No warm-start found')
log('No warm-start found — creating fresh model with first throttle')
first_throttle = phase_defs[0][1]
env0 = VecTransposeImage(DummyVecEnv([make_env(first_throttle)]))
model = PPO('CnnPolicy', env0, learning_rate=LR, verbose=1, device='cpu')
loaded_env.close()
steps_done = 0
best_reward = float('-inf')