Files
Gymnasium/tests/vector/test_vector_env.py
2022-12-05 19:14:56 +00:00

126 lines
4.2 KiB
Python

from functools import partial
import numpy as np
import pytest
from gymnasium.spaces import Discrete, Tuple
from gymnasium.vector.async_vector_env import AsyncVectorEnv
from gymnasium.vector.sync_vector_env import SyncVectorEnv
from gymnasium.vector.vector_env import VectorEnv
from tests.testing_env import GenericTestEnv
from tests.vector.utils import CustomSpace, make_env
@pytest.mark.parametrize("shared_memory", [True, False])
def test_vector_env_equal(shared_memory):
env_fns = [make_env("CartPole-v1", i) for i in range(4)]
num_steps = 100
async_env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
sync_env = SyncVectorEnv(env_fns)
assert async_env.num_envs == sync_env.num_envs
assert async_env.observation_space == sync_env.observation_space
assert async_env.single_observation_space == sync_env.single_observation_space
assert async_env.action_space == sync_env.action_space
assert async_env.single_action_space == sync_env.single_action_space
async_observations, async_infos = async_env.reset(seed=0)
sync_observations, sync_infos = sync_env.reset(seed=0)
assert np.all(async_observations == sync_observations)
for _ in range(num_steps):
actions = async_env.action_space.sample()
assert actions in sync_env.action_space
# fmt: off
async_observations, async_rewards, async_terminateds, async_truncateds, async_infos = async_env.step(actions)
sync_observations, sync_rewards, sync_terminateds, sync_truncateds, sync_infos = sync_env.step(actions)
# fmt: on
if any(sync_terminateds) or any(sync_truncateds):
assert "final_observation" in async_infos
assert "_final_observation" in async_infos
assert "final_observation" in sync_infos
assert "_final_observation" in sync_infos
assert np.all(async_observations == sync_observations)
assert np.all(async_rewards == sync_rewards)
assert np.all(async_terminateds == sync_terminateds)
assert np.all(async_truncateds == sync_truncateds)
async_env.close()
sync_env.close()
def test_custom_space_vector_env():
env = VectorEnv(4, CustomSpace(), CustomSpace())
assert isinstance(env.single_observation_space, CustomSpace)
assert isinstance(env.observation_space, Tuple)
assert isinstance(env.single_action_space, CustomSpace)
assert isinstance(env.action_space, Tuple)
@pytest.mark.parametrize(
"vectoriser",
(
SyncVectorEnv,
partial(AsyncVectorEnv, shared_memory=True),
partial(AsyncVectorEnv, shared_memory=False),
),
ids=["Sync", "Async with shared memory", "Async without shared memory"],
)
def test_final_obs_info(vectoriser):
"""Tests that the vector environments correctly return the final observation and info."""
def reset_fn(self, seed=None, options=None):
return 0, {"reset": True}
def thunk():
return GenericTestEnv(
action_space=Discrete(4),
observation_space=Discrete(4),
reset_func=reset_fn,
step_func=lambda self, action: (
action if action < 3 else 0,
0,
action >= 3,
False,
{"action": action},
),
)
env = vectoriser([thunk])
obs, info = env.reset()
assert obs == np.array([0]) and info == {
"reset": np.array([True]),
"_reset": np.array([True]),
}
obs, _, termination, _, info = env.step([1])
assert (
obs == np.array([1])
and termination == np.array([False])
and info == {"action": np.array([1]), "_action": np.array([True])}
)
obs, _, termination, _, info = env.step([2])
assert (
obs == np.array([2])
and termination == np.array([False])
and info == {"action": np.array([2]), "_action": np.array([True])}
)
obs, _, termination, _, info = env.step([3])
assert (
obs == np.array([0])
and termination == np.array([True])
and info["reset"] == np.array([True])
)
assert "final_observation" in info and "final_info" in info
assert info["final_observation"] == np.array([0]) and info["final_info"] == {
"action": 3
}