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import numpy as np |
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import pytest |
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from dizoo.gym_hybrid.envs import GymHybridEnv |
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from easydict import EasyDict |
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@pytest.mark.envtest |
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class TestGymHybridEnv: |
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def test_naive(self): |
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env = GymHybridEnv( |
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EasyDict( |
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{ |
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'env_id': 'Moving-v0', |
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'act_scale': False, |
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'save_replay_gif': False, |
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'replay_path_gif': None, |
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'replay_path': None |
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} |
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) |
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) |
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env.enable_save_replay('./video') |
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env.seed(314, dynamic_seed=False) |
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assert env._seed == 314 |
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obs = env.reset() |
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assert obs.shape == (10, ) |
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for i in range(200): |
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random_action = env.random_action() |
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print('random_action', random_action) |
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timestep = env.step(random_action) |
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assert isinstance(timestep.obs, np.ndarray) |
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assert isinstance(timestep.done, bool) |
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assert timestep.obs.shape == (10, ) |
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assert timestep.reward.shape == (1, ) |
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assert timestep.info['action_args_mask'].shape == (3, 2) |
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if timestep.done: |
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print('reset env') |
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env.reset() |
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print(env.observation_space, env.action_space, env.reward_space) |
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env.close() |
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