74 lines
2.1 KiB
Python
74 lines
2.1 KiB
Python
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from slate import Slate
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import fancy_gym
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from stable_baselines3 import PPO
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from stable_baselines3.common.monitor import Monitor
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from stable_baselines3.common.vec_env import DummyVecEnv, VecVideoRecorder
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from wandb.integration.sb3 import WandbCallback
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import gymnasium as gym
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import copy
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PCA = None
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def debug_runner(slate, run, config):
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print(config)
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for k in list(config.keys()):
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del config[k]
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import time
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time.sleep(10)
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def sb3_runner(slate, run, config):
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videoC, testC, envC, algoC, pcaC = slate.consume(config, 'video', {}), slate.consume(config, 'test', {}), slate.consume(config,
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'env', {}), slate.consume(config, 'algo', {}), slate.consume(config, 'pca', {})
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assert config == {}
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env = DummyVecEnv([make_env_func(slate, envC)])
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if slate.consume(videoC, 'enable', False):
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env = VecVideoRecorder(env, f"videos/{run.id}", record_video_trigger=lambda x: x % videoC['frequency'] == 0, video_length=videoC['length'])
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assert slate.consume(algoC, 'name') == 'PPO'
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policy_name = slate.consume(algoC, 'policy_name')
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total_timesteps = config.get('run', {}).get('total_timesteps', {})
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model = PPO(policy_name, env, **algoC)
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if slate.consume(pcaC, 'enable', False):
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model.policy.action_dist = PCA(model.policy.action_space.shape, **pcaC)
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model.learn(
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total_timesteps=total_timesteps,
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callback=WandbCallback()
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)
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def make_env_func(slate, env_conf):
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conf = copy.deepcopy(env_conf)
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name = slate.consume(conf, 'name')
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legacy_fancy = slate.consume(conf, 'legacy_fancy', False)
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wrappers = slate.consume(conf, 'wrappers', [])
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def func():
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if legacy_fancy: # TODO: Remove when no longer needed
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fancy_gym.make(name, **conf)
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else:
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env = gym.make(name, **conf)
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# TODO: Implement wrappers
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env = Monitor(env)
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return env
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return func
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runners = {
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'sb3': sb3_runner,
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'debug': debug_runner
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}
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if __name__ == '__main__':
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slate = Slate(runners)
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slate.from_args()
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