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358dd8b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | import optuna
from cleanrl_utils.tuner import Tuner
def test_tuner():
tuner = Tuner(
script="cleanrl/ppo.py",
metric="charts/episodic_return",
metric_last_n_average_window=50,
direction="maximize",
target_scores={
"CartPole-v1": [0, 500],
"Acrobot-v1": [-500, 0],
},
params_fn=lambda trial: {
"learning-rate": trial.suggest_float("learning-rate", 0.0003, 0.003, log=True),
"num-minibatches": trial.suggest_categorical("num-minibatches", [1, 2, 4]),
"update-epochs": trial.suggest_categorical("update-epochs", [1, 2, 4]),
"num-steps": trial.suggest_categorical("num-steps", [1200]),
"vf-coef": trial.suggest_float("vf-coef", 0, 5),
"max-grad-norm": trial.suggest_float("max-grad-norm", 0, 5),
"total-timesteps": 1200,
"num-envs": 1,
},
pruner=optuna.pruners.MedianPruner(n_startup_trials=5),
sampler=optuna.samplers.TPESampler(),
# wandb_kwargs={"project": "cleanrl"},
)
tuner.tune(
num_trials=1,
num_seeds=1,
)
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