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https://github.com/Farama-Foundation/Gymnasium.git
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90 lines
2.9 KiB
Python
90 lines
2.9 KiB
Python
import numpy as np
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from nose2 import tools
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import os
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import logging
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logger = logging.getLogger(__name__)
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import gym
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from gym import envs
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def should_skip_env_spec_for_tests(spec):
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# We skip tests for envs that require dependencies or are otherwise
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# troublesome to run frequently
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# Skip mujoco tests for pull request CI
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skip_mujoco = not (os.environ.get('MUJOCO_KEY_BUNDLE') or os.path.exists(os.path.expanduser('~/.mujoco')))
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if skip_mujoco and spec._entry_point.startswith('gym.envs.mujoco:'):
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return True
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# TODO(jonas 2016-05-11): Re-enable these tests after fixing box2d-py
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if spec._entry_point.startswith('gym.envs.box2d:'):
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logger.warn("Skipping tests for box2d env {}".format(spec._entry_point))
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return True
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# Skip ConvergenceControl tests (the only env in parameter_tuning) according to pull #104
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if spec._entry_point.startswith('gym.envs.parameter_tuning:'):
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logger.warn("Skipping tests for parameter_tuning env {}".format(spec._entry_point))
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return True
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return False
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# This runs a smoketest on each official registered env. We may want
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# to try also running environments which are not officially registered
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# envs.
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specs = [spec for spec in envs.registry.all() if spec._entry_point is not None]
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@tools.params(*specs)
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def test_env(spec):
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if should_skip_env_spec_for_tests(spec):
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return
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env = spec.make()
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ob_space = env.observation_space
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act_space = env.action_space
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ob = env.reset()
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assert ob_space.contains(ob), 'Reset observation: {!r} not in space'.format(ob)
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a = act_space.sample()
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observation, reward, done, _info = env.step(a)
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assert ob_space.contains(observation), 'Step observation: {!r} not in space'.format(observation)
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assert np.isscalar(reward), "{} is not a scalar for {}".format(reward, env)
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assert isinstance(done, bool), "Expected {} to be a boolean".format(done)
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for mode in env.metadata.get('render.modes', []):
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env.render(mode=mode)
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env.render(close=True)
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# Make sure we can render the environment after close.
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for mode in env.metadata.get('render.modes', []):
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env.render(mode=mode)
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env.render(close=True)
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env.close()
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# Run a longer rollout on some environments
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def test_random_rollout():
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for env in [envs.make('CartPole-v0'), envs.make('FrozenLake-v0')]:
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agent = lambda ob: env.action_space.sample()
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ob = env.reset()
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for _ in range(10):
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assert env.observation_space.contains(ob)
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a = agent(ob)
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assert env.action_space.contains(a)
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(ob, _reward, done, _info) = env.step(a)
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if done: break
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def test_double_close():
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class TestEnv(gym.Env):
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def __init__(self):
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self.close_count = 0
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def _close(self):
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self.close_count += 1
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env = TestEnv()
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assert env.close_count == 0
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env.close()
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assert env.close_count == 1
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env.close()
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assert env.close_count == 1
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