mirror of
https://github.com/Farama-Foundation/Gymnasium.git
synced 2025-08-17 20:39:12 +00:00
cb1a4836fb
* Copied over SB3 env checker * Added test from SB3 * Addition of MIT license attribution and black formatting * Removed SB3 dependence * Implemented rough, non-vectorized version of check_nan * Made some SB3 warnings a bit more "general" * Removed check for "unsupported" spaces, since Gym should support any space * Added action/observation checks from pettingzoo, referenced in file docstring * Removed copy of MIT license in file docstring * Re-added usage of the check_inf flag for helper functino * Changed test to be simple/classic example. Should add more tests * Added API compliance check to registered envs
74 lines
2.2 KiB
Python
74 lines
2.2 KiB
Python
import pytest
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import numpy as np
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from gym import envs
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from gym.envs.tests.spec_list import spec_list
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from gym.utils.env_checker import check_env
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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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@pytest.mark.parametrize("spec", spec_list)
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def test_env(spec):
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# Capture warnings
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with pytest.warns(None) as warnings:
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env = spec.make()
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# Test if env adheres to Gym API
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check_env(env, warn=True, skip_render_check=True)
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# Check that dtype is explicitly declared for gym.Box spaces
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for warning_msg in warnings:
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assert "autodetected dtype" not in str(warning_msg.message)
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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(
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observation
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)
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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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# 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.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:
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break
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env.close()
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def test_env_render_result_is_immutable():
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environs = [
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envs.make("Taxi-v3"),
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envs.make("FrozenLake-v0"),
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envs.make("Reverse-v0"),
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]
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for env in environs:
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env.reset()
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output = env.render(mode="ansi")
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assert isinstance(output, str)
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env.close()
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