Files
Gymnasium/gym/vector/tests/test_async_vector_env.py
2019-06-28 16:32:39 -07:00

197 lines
7.1 KiB
Python

import pytest
import numpy as np
from multiprocessing import TimeoutError
from gym.spaces import Box
from gym.error import (AlreadyPendingCallError, NoAsyncCallError,
ClosedEnvironmentError)
from gym.vector.tests.utils import make_env, make_slow_env
from gym.vector.async_vector_env import AsyncVectorEnv
@pytest.mark.parametrize('shared_memory', [True, False])
def test_create_async_vector_env(shared_memory):
env_fns = [make_env('CubeCrash-v0', i) for i in range(8)]
try:
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
finally:
env.close()
assert env.num_envs == 8
@pytest.mark.parametrize('shared_memory', [True, False])
def test_reset_async_vector_env(shared_memory):
env_fns = [make_env('CubeCrash-v0', i) for i in range(8)]
try:
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
observations = env.reset()
finally:
env.close()
assert isinstance(env.observation_space, Box)
assert isinstance(observations, np.ndarray)
assert observations.dtype == env.observation_space.dtype
assert observations.shape == (8,) + env.single_observation_space.shape
assert observations.shape == env.observation_space.shape
@pytest.mark.parametrize('shared_memory', [True, False])
@pytest.mark.parametrize('use_single_action_space', [True, False])
def test_step_async_vector_env(shared_memory, use_single_action_space):
env_fns = [make_env('CubeCrash-v0', i) for i in range(8)]
try:
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
observations = env.reset()
if use_single_action_space:
actions = [env.single_action_space.sample() for _ in range(8)]
else:
actions = env.action_space.sample()
observations, rewards, dones, _ = env.step(actions)
finally:
env.close()
assert isinstance(env.observation_space, Box)
assert isinstance(observations, np.ndarray)
assert observations.dtype == env.observation_space.dtype
assert observations.shape == (8,) + env.single_observation_space.shape
assert observations.shape == env.observation_space.shape
assert isinstance(rewards, np.ndarray)
assert isinstance(rewards[0], (float, np.floating))
assert rewards.ndim == 1
assert rewards.size == 8
assert isinstance(dones, np.ndarray)
assert dones.dtype == np.bool_
assert dones.ndim == 1
assert dones.size == 8
@pytest.mark.parametrize('shared_memory', [True, False])
def test_copy_async_vector_env(shared_memory):
env_fns = [make_env('CubeCrash-v0', i) for i in range(8)]
try:
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory,
copy=True)
observations = env.reset()
observations[0] = 128
assert not np.all(env.observations[0] == 128)
finally:
env.close()
@pytest.mark.parametrize('shared_memory', [True, False])
def test_no_copy_async_vector_env(shared_memory):
env_fns = [make_env('CubeCrash-v0', i) for i in range(8)]
try:
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory,
copy=False)
observations = env.reset()
observations[0] = 128
assert np.all(env.observations[0] == 128)
finally:
env.close()
@pytest.mark.parametrize('shared_memory', [True, False])
def test_reset_timeout_async_vector_env(shared_memory):
env_fns = [make_slow_env(0.3, i) for i in range(4)]
with pytest.raises(TimeoutError):
try:
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
env.reset_async()
observations = env.reset_wait(timeout=0.1)
finally:
env.close(terminate=True)
@pytest.mark.parametrize('shared_memory', [True, False])
def test_step_timeout_async_vector_env(shared_memory):
env_fns = [make_slow_env(0., i) for i in range(4)]
with pytest.raises(TimeoutError):
try:
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
observations = env.reset()
env.step_async([0.1, 0.1, 0.3, 0.1])
observations, rewards, dones, _ = env.step_wait(timeout=0.1)
finally:
env.close(terminate=True)
@pytest.mark.filterwarnings('ignore::UserWarning')
@pytest.mark.parametrize('shared_memory', [True, False])
def test_reset_out_of_order_async_vector_env(shared_memory):
env_fns = [make_env('CubeCrash-v0', i) for i in range(4)]
with pytest.raises(NoAsyncCallError):
try:
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
observations = env.reset_wait()
except NoAsyncCallError as exception:
assert exception.name == 'reset'
raise
finally:
env.close(terminate=True)
with pytest.raises(AlreadyPendingCallError):
try:
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
actions = env.action_space.sample()
observations = env.reset()
env.step_async(actions)
env.reset_async()
except NoAsyncCallError as exception:
assert exception.name == 'step'
raise
finally:
env.close(terminate=True)
@pytest.mark.filterwarnings('ignore::UserWarning')
@pytest.mark.parametrize('shared_memory', [True, False])
def test_step_out_of_order_async_vector_env(shared_memory):
env_fns = [make_env('CubeCrash-v0', i) for i in range(4)]
with pytest.raises(NoAsyncCallError):
try:
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
actions = env.action_space.sample()
observations = env.reset()
observations, rewards, dones, infos = env.step_wait()
except AlreadyPendingCallError as exception:
assert exception.name == 'step'
raise
finally:
env.close(terminate=True)
with pytest.raises(AlreadyPendingCallError):
try:
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
actions = env.action_space.sample()
env.reset_async()
env.step_async(actions)
except AlreadyPendingCallError as exception:
assert exception.name == 'reset'
raise
finally:
env.close(terminate=True)
@pytest.mark.parametrize('shared_memory', [True, False])
def test_already_closed_async_vector_env(shared_memory):
env_fns = [make_env('CubeCrash-v0', i) for i in range(4)]
with pytest.raises(ClosedEnvironmentError):
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
env.close()
observations = env.reset()
@pytest.mark.parametrize('shared_memory', [True, False])
def test_check_observations_async_vector_env(shared_memory):
# CubeCrash-v0 - observation_space: Box(40, 32, 3)
env_fns = [make_env('CubeCrash-v0', i) for i in range(8)]
# MemorizeDigits-v0 - observation_space: Box(24, 32, 3)
env_fns[1] = make_env('MemorizeDigits-v0', 1)
with pytest.raises(RuntimeError):
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
env.close(terminate=True)