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Added tests

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Dominik Moritz Roth 2024-03-14 17:34:59 +01:00
parent 39c21ab6b9
commit 8d4f57a59d
2 changed files with 29 additions and 0 deletions
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tests/test_ppo.py Normal file
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import gymnasium as gym
import pytest
from metastable_baselines2 import PPO
@pytest.mark.parametrize("env_id", ["LunarLanderContinuous-v2", "MountainCarContinuous-v0"])
def test_trpl(env_id):
model = PPO("MlpPolicy", env_id, n_steps=128, seed=0, policy_kwargs=dict(net_arch=[16]), verbose=1)
model.learn(total_timesteps=500)

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tests/test_trpl.py Normal file
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import gymnasium as gym
import pytest
from metastable_baselines2 import TRPL
PROJECTIONS = ["Frobenius", "Wasserstein"] #, "KL"]
@pytest.mark.parametrize("env_id", ["LunarLanderContinuous-v2", "MountainCarContinuous-v0"])
@pytest.mark.parametrize("projection", PROJECTIONS)
def test_trpl(env_id, projection):
model = TRPL("MlpPolicy", env_id, n_steps=128, seed=0, policy_kwargs=dict(net_arch=[16]), projection_class=projection, verbose=1)
model.learn(total_timesteps=500)
@pytest.mark.parametrize("env_id", ["LunarLanderContinuous-v2"])
@pytest.mark.parametrize("projection", PROJECTIONS)
@pytest.mark.parametrize("mean_bound", [0.03, 0.06])
@pytest.mark.parametrize("cov_bound", [1.0e-3, 2.0e-3])
def test_trpl_params(env_id, projection, mean_bound, cov_bound):
model = TRPL("MlpPolicy", env_id, n_steps=128, seed=0, policy_kwargs=dict(net_arch=[16]), projection_class=projection, projection_kwargs={'mean_bound': mean_bound, 'cov_bound': cov_bound}, verbose=1)
model.learn(total_timesteps=100)