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Gymnasium/tests/vector/test_async_vector_env.py
2024-07-15 15:53:11 +01:00

437 lines
14 KiB
Python

"""Test the `SyncVectorEnv` implementation."""
import re
import warnings
from multiprocessing import TimeoutError
import numpy as np
import pytest
from gymnasium.error import (
AlreadyPendingCallError,
ClosedEnvironmentError,
NoAsyncCallError,
)
from gymnasium.spaces import Box, Discrete, MultiDiscrete, Tuple
from gymnasium.vector import AsyncVectorEnv
from tests.testing_env import GenericTestEnv
from tests.vector.testing_utils import (
CustomSpace,
make_custom_space_env,
make_env,
make_slow_env,
)
@pytest.mark.parametrize("shared_memory", [True, False])
def test_create_async_vector_env(shared_memory):
"""Test creating an async vector environment with or without shared memory."""
env_fns = [make_env("CartPole-v1", i) for i in range(8)]
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
assert env.num_envs == 8
env.close()
@pytest.mark.parametrize("shared_memory", [True, False])
def test_reset_async_vector_env(shared_memory):
"""Test the reset of async vector environment with or without shared memory."""
env_fns = [make_env("CartPole-v1", i) for i in range(8)]
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
observations, infos = env.reset()
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
try:
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
observations, infos = 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
assert isinstance(infos, dict)
assert all([isinstance(info, dict) for info in infos])
def test_render_async_vector():
envs = AsyncVectorEnv(
[make_env("CartPole-v1", i, render_mode="rgb_array") for i in range(3)]
)
assert envs.render_mode == "rgb_array"
envs.reset()
rendered_frames = envs.render()
assert isinstance(rendered_frames, tuple)
assert len(rendered_frames) == envs.num_envs
assert all(isinstance(frame, np.ndarray) for frame in rendered_frames)
envs.close()
envs = AsyncVectorEnv([make_env("CartPole-v1", i) for i in range(3)])
assert envs.render_mode is None
envs.close()
@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):
"""Test the step async vector environment with and without shared memory."""
env_fns = [make_env("CartPole-v1", i) for i in range(8)]
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
env.reset()
assert isinstance(env.single_action_space, Discrete)
assert isinstance(env.action_space, MultiDiscrete)
if use_single_action_space:
actions = [env.single_action_space.sample() for _ in range(8)]
else:
actions = env.action_space.sample()
observations, rewards, terminations, truncations, _ = env.step(actions)
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(terminations, np.ndarray)
assert terminations.dtype == np.bool_
assert terminations.ndim == 1
assert terminations.size == 8
assert isinstance(truncations, np.ndarray)
assert truncations.dtype == np.bool_
assert truncations.ndim == 1
assert truncations.size == 8
@pytest.mark.parametrize("shared_memory", [True, False])
def test_call_async_vector_env(shared_memory):
"""Test call with async vector environment."""
env_fns = [
make_env("CartPole-v1", i, render_mode="rgb_array_list") for i in range(4)
]
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
env.reset()
images = env.call("render")
gravity = env.call("gravity")
env.close()
assert isinstance(images, tuple)
assert len(images) == 4
for i in range(4):
assert len(images[i]) == 1
assert isinstance(images[i][0], np.ndarray)
assert isinstance(gravity, tuple)
assert len(gravity) == 4
for i in range(4):
assert isinstance(gravity[i], float)
assert gravity[i] == 9.8
@pytest.mark.parametrize("shared_memory", [True, False])
def test_set_attr_async_vector_env(shared_memory):
"""Test `set_attr_` for async vector environment with or without shared memory."""
env_fns = [make_env("CartPole-v1", i) for i in range(4)]
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
env.set_attr("gravity", [9.81, 3.72, 8.87, 1.62])
gravity = env.get_attr("gravity")
assert gravity == (9.81, 3.72, 8.87, 1.62)
env.close()
@pytest.mark.parametrize("shared_memory", [True, False])
def test_copy_async_vector_env(shared_memory):
"""Test observations are a copy of the true observation with and without shared memory."""
env_fns = [make_env("CartPole-v1", i) for i in range(8)]
# TODO, these tests do nothing, understand the purpose of the tests and fix them
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory, copy=True)
observations, infos = env.reset()
observations[0] = 0
env.close()
@pytest.mark.parametrize("shared_memory", [True, False])
def test_no_copy_async_vector_env(shared_memory):
"""Test observation are not a copy of the true observation with and without shared memory."""
env_fns = [make_env("CartPole-v1", i) for i in range(8)]
# TODO, these tests do nothing, understand the purpose of the tests and fix them
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory, copy=False)
observations, infos = env.reset()
observations[0] = 0
env.close()
@pytest.mark.parametrize("shared_memory", [True, False])
def test_reset_timeout_async_vector_env(shared_memory):
"""Test timeout error on reset with and without shared memory."""
env_fns = [make_slow_env(0.3, i) for i in range(4)]
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
with pytest.raises(TimeoutError):
env.reset_async()
env.reset_wait(timeout=0.1)
env.close(terminate=True)
@pytest.mark.parametrize("shared_memory", [True, False])
def test_step_timeout_async_vector_env(shared_memory):
"""Test timeout error on step with and without shared memory."""
env_fns = [make_slow_env(0.0, i) for i in range(4)]
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
with pytest.raises(TimeoutError):
env.reset()
env.step_async(np.array([0.1, 0.1, 0.3, 0.1]))
observations, rewards, terminations, truncations, _ = env.step_wait(timeout=0.1)
env.close(terminate=True)
@pytest.mark.parametrize("shared_memory", [True, False])
def test_reset_out_of_order_async_vector_env(shared_memory):
"""Test reset being called out of order with and without shared memory."""
env_fns = [make_env("CartPole-v1", i) for i in range(4)]
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
with pytest.raises(
NoAsyncCallError,
match=re.escape(
"Calling `reset_wait` without any prior call to `reset_async`."
),
):
env.reset_wait()
env.close(terminate=True)
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
with pytest.raises(
AlreadyPendingCallError,
match=re.escape(
"Calling `reset_async` while waiting for a pending call to `step` to complete"
),
):
actions = env.action_space.sample()
env.reset()
env.step_async(actions)
env.reset_async()
with pytest.warns(
UserWarning,
match=re.escape(
"Calling `close` while waiting for a pending call to `step` to complete."
),
):
env.close(terminate=True)
@pytest.mark.parametrize("shared_memory", [True, False])
def test_step_out_of_order_async_vector_env(shared_memory):
"""Test step out of order with and without shared memory."""
env_fns = [make_env("CartPole-v1", i) for i in range(4)]
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
with pytest.raises(
NoAsyncCallError,
match=re.escape("Calling `step_wait` without any prior call to `step_async`."),
):
env.action_space.sample()
env.reset()
env.step_wait()
env.close(terminate=True)
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
with pytest.raises(
AlreadyPendingCallError,
match=re.escape(
"Calling `step_async` while waiting for a pending call to `reset` to complete"
),
):
actions = env.action_space.sample()
env.reset_async()
env.step_async(actions)
with pytest.warns(
UserWarning,
match=re.escape(
"Calling `close` while waiting for a pending call to `reset` to complete."
),
):
env.close(terminate=True)
@pytest.mark.parametrize("shared_memory", [True, False])
def test_already_closed_async_vector_env(shared_memory):
"""Test the error if a function is called if environment is already closed."""
env_fns = [make_env("CartPole-v1", i) for i in range(4)]
with pytest.raises(ClosedEnvironmentError):
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
env.close()
env.reset()
@pytest.mark.parametrize("shared_memory", [True, False])
def test_check_spaces_async_vector_env(shared_memory):
"""Test check spaces for async vector environment with and without shared memory."""
# CartPole-v1 - observation_space: Box(4,), action_space: Discrete(2)
env_fns = [make_env("CartPole-v1", i) for i in range(8)]
# FrozenLake-v1 - Discrete(16), action_space: Discrete(4)
env_fns[1] = make_env("FrozenLake-v1", 1)
with pytest.raises(RuntimeError):
env = AsyncVectorEnv(env_fns, shared_memory=shared_memory)
env.close(terminate=True)
def test_custom_space_async_vector_env():
"""Test custom spaces with async vector environment."""
env_fns = [make_custom_space_env(i) for i in range(4)]
env = AsyncVectorEnv(env_fns, shared_memory=False)
reset_observations, reset_infos = env.reset()
assert isinstance(env.single_action_space, CustomSpace)
assert isinstance(env.action_space, Tuple)
actions = ("action-2", "action-3", "action-5", "action-7")
step_observations, rewards, terminations, truncations, _ = env.step(actions)
env.close()
assert isinstance(env.single_observation_space, CustomSpace)
assert isinstance(env.observation_space, Tuple)
assert isinstance(reset_observations, tuple)
assert reset_observations == ("reset", "reset", "reset", "reset")
assert isinstance(step_observations, tuple)
assert step_observations == (
"step(action-2)",
"step(action-3)",
"step(action-5)",
"step(action-7)",
)
def test_custom_space_async_vector_env_shared_memory():
"""Test custom space with shared memory."""
env_fns = [make_custom_space_env(i) for i in range(4)]
with pytest.raises(ValueError):
env = AsyncVectorEnv(env_fns, shared_memory=True)
env.close(terminate=True)
def raise_error_reset(self, seed, options):
super(GenericTestEnv, self).reset(seed=seed, options=options)
if seed == 1:
raise ValueError("Error in reset")
return self.observation_space.sample(), {}
def raise_error_step(self, action):
if action >= 1:
raise ValueError(f"Error in step with {action}")
return self.observation_space.sample(), 0, False, False, {}
def test_async_vector_subenv_error():
envs = AsyncVectorEnv(
[
lambda: GenericTestEnv(
reset_func=raise_error_reset, step_func=raise_error_step
)
]
* 2
)
with warnings.catch_warnings(record=True) as caught_warnings:
envs.reset(seed=[0, 0])
assert len(caught_warnings) == 0
with warnings.catch_warnings(record=True) as caught_warnings:
with pytest.raises(ValueError, match="Error in reset"):
envs.reset(seed=[1, 0])
envs.close()
assert len(caught_warnings) == 3
assert (
"Received the following error from Worker-0 - Shutting it down"
in caught_warnings[0].message.args[0]
)
assert (
'in raise_error_reset\n raise ValueError("Error in reset")\nValueError: Error in reset'
in caught_warnings[1].message.args[0]
)
assert (
caught_warnings[2].message.args[0]
== "\x1b[31mERROR: Raising the last exception back to the main process.\x1b[0m"
)
envs = AsyncVectorEnv(
[
lambda: GenericTestEnv(
reset_func=raise_error_reset, step_func=raise_error_step
)
]
* 3
)
with warnings.catch_warnings(record=True) as caught_warnings:
with pytest.raises(ValueError, match="Error in step"):
envs.step([0, 1, 2])
envs.close()
assert len(caught_warnings) == 5
# due to variance in the step time, the order of warnings is random
assert re.match(
r"\x1b\[31mERROR: Received the following error from Worker-[12] - Shutting it down\x1b\[0m",
caught_warnings[0].message.args[0],
)
assert re.match(
r"\x1b\[31mERROR: Traceback \(most recent call last\):(?s:.)*in raise_error_step(?s:.)*ValueError: Error in step with [12]\n\x1b\[0m",
caught_warnings[1].message.args[0],
)
assert re.match(
r"\x1b\[31mERROR: Received the following error from Worker-[12] - Shutting it down\x1b\[0m",
caught_warnings[2].message.args[0],
)
assert re.match(
r"\x1b\[31mERROR: Traceback \(most recent call last\):(?s:.)*in raise_error_step(?s:.)*ValueError: Error in step with [12]\n\x1b\[0m",
caught_warnings[3].message.args[0],
)
assert (
caught_warnings[4].message.args[0]
== "\x1b[31mERROR: Raising the last exception back to the main process.\x1b[0m"
)