mirror of
https://github.com/Farama-Foundation/Gymnasium.git
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49d8299a1e
* WIP refactor info API sync vector. * Add missing untracked file. * Add info strategy to reset_wait. * Add interface and docstring. * info with strategy pattern on async vector env. * Add default to async vecenv. * episode statistics for asyncvecnev. * Add tests info strategy format. * Add info strategy to reset_wait. * refactor and cleanup. * Code cleanup. Add tests. * Add tests for video recording with new info format. * fix test case. * fix camelcase. * rename enum. * update tests, docstrings, cleanup. * Changes brax strategy to numpy. add_strategy method in StrategyFactory. Add tests. * fix docstring and logging format. * Set Brax info format as default. Remove classic info format. Update tests. * breaking the wrong loop. * WIP: wrapper. * Add wrapper for brax to classic info. * WIP: wrapper with nested RecordEpisodeStatistic. * Add tests. Refactor docstrings. Cleanup. * cleanup. * patch conflicts. * rebase and conflicts. * new pre-commit conventions. * docstring. * renaming. * incorporate info_processor in vecEnv. * renaming. Create info dict only if needed. * remove all brax references. update docstring. Update duplicate test. * reviews. * pre-commit. * reviews. * docstring. * cleanup blank lines. * add support for numpy dtypes. * docstring fix. * formatting. * naming. * assert correct info from wrappers chaining. Test correct wrappers chaining. naming. * simplify episode_statistics. * change args orer. * update tests. * wip: refactor episode_statistics. * Add test for add_vecore_episode_statistics.
59 lines
1.8 KiB
Python
59 lines
1.8 KiB
Python
import pytest
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import gym
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from gym.wrappers import RecordEpisodeStatistics, VectorListInfo
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ENV_ID = "CartPole-v1"
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NUM_ENVS = 3
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ENV_STEPS = 50
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SEED = 42
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def test_usage_in_vector_env():
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env = gym.make(ENV_ID)
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vector_env = gym.vector.make(ENV_ID, num_envs=NUM_ENVS)
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VectorListInfo(vector_env)
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with pytest.raises(AssertionError):
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VectorListInfo(env)
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def test_info_to_list():
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env_to_wrap = gym.vector.make(ENV_ID, num_envs=NUM_ENVS)
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wrapped_env = VectorListInfo(env_to_wrap)
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wrapped_env.action_space.seed(SEED)
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_, info = wrapped_env.reset(seed=SEED, return_info=True)
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assert isinstance(info, list)
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assert len(info) == NUM_ENVS
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for _ in range(ENV_STEPS):
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action = wrapped_env.action_space.sample()
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_, _, dones, list_info = wrapped_env.step(action)
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for i, done in enumerate(dones):
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if done:
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assert "terminal_observation" in list_info[i]
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else:
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assert "terminal_observation" not in list_info[i]
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def test_info_to_list_statistics():
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env_to_wrap = gym.vector.make(ENV_ID, num_envs=NUM_ENVS)
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wrapped_env = VectorListInfo(RecordEpisodeStatistics(env_to_wrap))
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_, info = wrapped_env.reset(seed=SEED, return_info=True)
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wrapped_env.action_space.seed(SEED)
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assert isinstance(info, list)
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assert len(info) == NUM_ENVS
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for _ in range(ENV_STEPS):
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action = wrapped_env.action_space.sample()
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_, _, dones, list_info = wrapped_env.step(action)
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for i, done in enumerate(dones):
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if done:
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assert "episode" in list_info[i]
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for stats in ["r", "l", "t"]:
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assert stats in list_info[i]["episode"]
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assert isinstance(list_info[i]["episode"][stats], float)
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else:
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assert "episode" not in list_info[i]
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