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Gymnasium/tests/wrappers/test_record_episode_statistics.py

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import pytest
import numpy as np
import gym
from gym.wrappers import RecordEpisodeStatistics
Reduces warnings produced by pytest from ~1500 to 13 (#2660) * Updated cartpole-v0 to v1 to prevent warning and added pytest.mark.filterwarnings for tests where warnings are unavoidable * Change np.bool to bool as numpy raises a warning and bool is the suggested solution * Seeding randint is deprecated in the future, integers is new solution * Fixed errors thrown when the video recorder is deleted but not closed * spaces.Box expects a floating array, updated all cases where this was not true and modified float32 to float64 as float array default to float64. Otherwise space.Box raises warning that dtype precision (float32) is lower than array precision (float64). * Added pytest.mark.filterwarnings to preventing the raising of an intended warning * Added comment to explain why a warning is raised that can't be prevented without version update to the environment * Added comment to explain why warning is raised * Changed values to float as expected by the box which default to float64 * Removed --forked from pytest as the pytest-forked project is no being maintained and was not raising warnings as expected * When AsyncVectorEnv has shared_memory=True then a ValueError is raised before _state is initialised. Therefore, on the destruction on the env an error is thrown in .close_extra as _state does not exist * Possible fix that was causing an error in test_call_async_vector_env by ensuring that pygame resources are released * Pygame throws an error with ALSA when closed, using a fix from PettingZoo (https://github.com/Farama-Foundation/PettingZoo/blob/master/pettingzoo/__init__.py). We use the dsp audiodriver to prevent this issue * Modification due to running pre-commit locally * Updated cartpole-v0 to v1 to prevent warning and added pytest.mark.filterwarnings for tests where warnings are unavoidable * Change np.bool to bool as numpy raises a warning and bool is the suggested solution * Seeding randint is deprecated in the future, integers is new solution * Fixed errors thrown when the video recorder is deleted but not closed * spaces.Box expects a floating array, updated all cases where this was not true and modified float32 to float64 as float array default to float64. Otherwise space.Box raises warning that dtype precision (float32) is lower than array precision (float64). * Added pytest.mark.filterwarnings to preventing the raising of an intended warning * Added comment to explain why a warning is raised that can't be prevented without version update to the environment * Added comment to explain why warning is raised * Changed values to float as expected by the box which default to float64 * Removed --forked from pytest as the pytest-forked project is no being maintained and was not raising warnings as expected * When AsyncVectorEnv has shared_memory=True then a ValueError is raised before _state is initialised. Therefore, on the destruction on the env an error is thrown in .close_extra as _state does not exist * Possible fix that was causing an error in test_call_async_vector_env by ensuring that pygame resources are released * Pygame throws an error with ALSA when closed, using a fix from PettingZoo (https://github.com/Farama-Foundation/PettingZoo/blob/master/pettingzoo/__init__.py). We use the dsp audiodriver to prevent this issue * Modification due to running pre-commit locally
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@pytest.mark.parametrize("env_id", ["CartPole-v1", "Pendulum-v1"])
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@pytest.mark.parametrize("deque_size", [2, 5])
def test_record_episode_statistics(env_id, deque_size):
env = gym.make(env_id)
env = RecordEpisodeStatistics(env, deque_size)
for n in range(5):
env.reset()
assert env.episode_returns[0] == 0.0
assert env.episode_lengths[0] == 0
for t in range(env.spec.max_episode_steps):
_, _, done, info = env.step(env.action_space.sample())
if done:
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assert "episode" in info
assert all([item in info["episode"] for item in ["r", "l", "t"]])
break
assert len(env.return_queue) == deque_size
assert len(env.length_queue) == deque_size
def test_record_episode_statistics_reset_info():
env = gym.make("CartPole-v1")
env = RecordEpisodeStatistics(env)
ob_space = env.observation_space
obs = env.reset()
assert ob_space.contains(obs)
del obs
obs, info = env.reset(return_info=True)
assert ob_space.contains(obs)
assert isinstance(info, dict)
@pytest.mark.parametrize(
("num_envs", "asynchronous"), [(1, False), (1, True), (4, False), (4, True)]
)
def test_record_episode_statistics_with_vectorenv(num_envs, asynchronous):
Reduces warnings produced by pytest from ~1500 to 13 (#2660) * Updated cartpole-v0 to v1 to prevent warning and added pytest.mark.filterwarnings for tests where warnings are unavoidable * Change np.bool to bool as numpy raises a warning and bool is the suggested solution * Seeding randint is deprecated in the future, integers is new solution * Fixed errors thrown when the video recorder is deleted but not closed * spaces.Box expects a floating array, updated all cases where this was not true and modified float32 to float64 as float array default to float64. Otherwise space.Box raises warning that dtype precision (float32) is lower than array precision (float64). * Added pytest.mark.filterwarnings to preventing the raising of an intended warning * Added comment to explain why a warning is raised that can't be prevented without version update to the environment * Added comment to explain why warning is raised * Changed values to float as expected by the box which default to float64 * Removed --forked from pytest as the pytest-forked project is no being maintained and was not raising warnings as expected * When AsyncVectorEnv has shared_memory=True then a ValueError is raised before _state is initialised. Therefore, on the destruction on the env an error is thrown in .close_extra as _state does not exist * Possible fix that was causing an error in test_call_async_vector_env by ensuring that pygame resources are released * Pygame throws an error with ALSA when closed, using a fix from PettingZoo (https://github.com/Farama-Foundation/PettingZoo/blob/master/pettingzoo/__init__.py). We use the dsp audiodriver to prevent this issue * Modification due to running pre-commit locally * Updated cartpole-v0 to v1 to prevent warning and added pytest.mark.filterwarnings for tests where warnings are unavoidable * Change np.bool to bool as numpy raises a warning and bool is the suggested solution * Seeding randint is deprecated in the future, integers is new solution * Fixed errors thrown when the video recorder is deleted but not closed * spaces.Box expects a floating array, updated all cases where this was not true and modified float32 to float64 as float array default to float64. Otherwise space.Box raises warning that dtype precision (float32) is lower than array precision (float64). * Added pytest.mark.filterwarnings to preventing the raising of an intended warning * Added comment to explain why a warning is raised that can't be prevented without version update to the environment * Added comment to explain why warning is raised * Changed values to float as expected by the box which default to float64 * Removed --forked from pytest as the pytest-forked project is no being maintained and was not raising warnings as expected * When AsyncVectorEnv has shared_memory=True then a ValueError is raised before _state is initialised. Therefore, on the destruction on the env an error is thrown in .close_extra as _state does not exist * Possible fix that was causing an error in test_call_async_vector_env by ensuring that pygame resources are released * Pygame throws an error with ALSA when closed, using a fix from PettingZoo (https://github.com/Farama-Foundation/PettingZoo/blob/master/pettingzoo/__init__.py). We use the dsp audiodriver to prevent this issue * Modification due to running pre-commit locally
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envs = gym.vector.make("CartPole-v1", num_envs=num_envs, asynchronous=asynchronous)
envs = RecordEpisodeStatistics(envs)
max_episode_step = (
envs.env_fns[0]().spec.max_episode_steps
if asynchronous
else envs.env.envs[0].spec.max_episode_steps
)
envs.reset()
for _ in range(max_episode_step + 1):
_, _, dones, infos = envs.step(envs.action_space.sample())
for idx, info in enumerate(infos):
if dones[idx]:
assert "episode" in info
assert all([item in info["episode"] for item in ["r", "l", "t"]])
break