File size: 1,079 Bytes
a89d35f | 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 35 36 37 38 | import os
import pytest
from stable_baselines3 import A2C, PPO, SAC, TD3
MODEL_DICT = {
"a2c": (A2C, "CartPole-v1"),
"ppo": (PPO, "CartPole-v1"),
"sac": (SAC, "Pendulum-v0"),
"td3": (TD3, "Pendulum-v0"),
}
N_STEPS = 100
@pytest.mark.parametrize("model_name", MODEL_DICT.keys())
def test_tensorboard(tmp_path, model_name):
# Skip if no tensorboard installed
pytest.importorskip("tensorboard")
logname = model_name.upper()
algo, env_id = MODEL_DICT[model_name]
model = algo("MlpPolicy", env_id, verbose=1, tensorboard_log=tmp_path)
model.learn(N_STEPS)
model.learn(N_STEPS, reset_num_timesteps=False)
assert os.path.isdir(tmp_path / str(logname + "_1"))
assert not os.path.isdir(tmp_path / str(logname + "_2"))
logname = "tb_multiple_runs_" + model_name
model.learn(N_STEPS, tb_log_name=logname)
model.learn(N_STEPS, tb_log_name=logname)
assert os.path.isdir(tmp_path / str(logname + "_1"))
# Check that the log dir name increments correctly
assert os.path.isdir(tmp_path / str(logname + "_2"))
|