| import gym |
| import numpy as np |
| import pytest |
| from gym import spaces |
|
|
| from stable_baselines3.common.vec_env import DummyVecEnv, VecCheckNan |
|
|
|
|
| class NanAndInfEnv(gym.Env): |
| """Custom Environment that raised NaNs and Infs""" |
|
|
| metadata = {"render.modes": ["human"]} |
|
|
| def __init__(self): |
| super(NanAndInfEnv, self).__init__() |
| self.action_space = spaces.Box(low=-np.inf, high=np.inf, shape=(1,), dtype=np.float64) |
| self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(1,), dtype=np.float64) |
|
|
| @staticmethod |
| def step(action): |
| if np.all(np.array(action) > 0): |
| obs = float("NaN") |
| elif np.all(np.array(action) < 0): |
| obs = float("inf") |
| else: |
| obs = 0 |
| return [obs], 0.0, False, {} |
|
|
| @staticmethod |
| def reset(): |
| return [0.0] |
|
|
| def render(self, mode="human", close=False): |
| pass |
|
|
|
|
| def test_check_nan(): |
| """Test VecCheckNan Object""" |
|
|
| env = DummyVecEnv([NanAndInfEnv]) |
| env = VecCheckNan(env, raise_exception=True) |
|
|
| env.step([[0]]) |
|
|
| with pytest.raises(ValueError): |
| env.step([[float("NaN")]]) |
|
|
| with pytest.raises(ValueError): |
| env.step([[float("inf")]]) |
|
|
| with pytest.raises(ValueError): |
| env.step([[-1]]) |
|
|
| with pytest.raises(ValueError): |
| env.step([[1]]) |
|
|
| env.step(np.array([[0, 1], [0, 1]])) |
|
|
| env.reset() |
|
|