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| import numpy as np | |
| import pytest | |
| from dizoo.gym_soccer.envs.gym_soccer_env import GymSoccerEnv | |
| from easydict import EasyDict | |
| class TestGymSoccerEnv: | |
| def test_naive(self): | |
| env = GymSoccerEnv(EasyDict({'env_id': 'Soccer-v0', 'act_scale': True})) | |
| # env.enable_save_replay('./video') | |
| env.seed(25, dynamic_seed=False) | |
| assert env._seed == 25 | |
| obs = env.reset() | |
| assert obs.shape == (59, ) | |
| for i in range(1000): | |
| random_action = env.get_random_action() | |
| # print('random_action', random_action) | |
| timestep = env.step(random_action) | |
| # env.render() | |
| assert isinstance(timestep.obs, np.ndarray) | |
| assert isinstance(timestep.done, bool) | |
| assert timestep.obs.shape == (59, ) | |
| # print(timestep.obs) | |
| assert timestep.reward.shape == (1, ) | |
| assert timestep.info['action_args_mask'].shape == (3, 5) | |
| if timestep.done: | |
| print('reset env') | |
| env.reset() | |
| assert env._eval_episode_return == 0 | |
| print(env.info()) | |
| # env.replay_log("./video/20211019011053-base_left_0-vs-base_right_0.rcg") | |
| env.close() | |