Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目,它使游戏和模拟能够作为训练智能代理的环境。
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import unittest.mock as mock
import pytest
import numpy as np
from mlagents.envs.environment import UnityEnvironment
from mlagents.envs.exception import UnityEnvironmentException, UnityActionException
from mlagents.envs.brain import BrainInfo
from mlagents.envs.mock_communicator import MockCommunicator
@mock.patch("mlagents.envs.environment.UnityEnvironment.get_communicator")
def test_handles_bad_filename(get_communicator):
with pytest.raises(UnityEnvironmentException):
UnityEnvironment(" ")
@mock.patch("mlagents.envs.environment.UnityEnvironment.executable_launcher")
@mock.patch("mlagents.envs.environment.UnityEnvironment.get_communicator")
def test_initialization(mock_communicator, mock_launcher):
mock_communicator.return_value = MockCommunicator(
discrete_action=False, visual_inputs=0
)
env = UnityEnvironment(" ")
assert env.brain_names[0] == "RealFakeBrain"
env.close()
@mock.patch("mlagents.envs.environment.UnityEnvironment.executable_launcher")
@mock.patch("mlagents.envs.environment.UnityEnvironment.get_communicator")
def test_reset(mock_communicator, mock_launcher):
mock_communicator.return_value = MockCommunicator(
discrete_action=False, visual_inputs=0
)
env = UnityEnvironment(" ")
brain = env.brains["RealFakeBrain"]
brain_info = env.reset()
env.close()
assert isinstance(brain_info, dict)
assert isinstance(brain_info["RealFakeBrain"], BrainInfo)
assert isinstance(brain_info["RealFakeBrain"].visual_observations, list)
assert isinstance(brain_info["RealFakeBrain"].vector_observations, np.ndarray)
assert (
len(brain_info["RealFakeBrain"].visual_observations)
== brain.number_visual_observations
)
assert len(brain_info["RealFakeBrain"].vector_observations) == len(
brain_info["RealFakeBrain"].agents
)
assert (
len(brain_info["RealFakeBrain"].vector_observations[0])
== brain.vector_observation_space_size * brain.num_stacked_vector_observations
)
@mock.patch("mlagents.envs.environment.UnityEnvironment.executable_launcher")
@mock.patch("mlagents.envs.environment.UnityEnvironment.get_communicator")
def test_step(mock_communicator, mock_launcher):
mock_communicator.return_value = MockCommunicator(
discrete_action=False, visual_inputs=0
)
env = UnityEnvironment(" ")
brain = env.brains["RealFakeBrain"]
brain_info = env.step()
brain_info = env.step(
[0]
* brain.vector_action_space_size[0]
* len(brain_info["RealFakeBrain"].agents)
)
with pytest.raises(UnityActionException):
env.step([0])
brain_info = env.step(
[-1]
* brain.vector_action_space_size[0]
* len(brain_info["RealFakeBrain"].agents)
)
env.close()
assert isinstance(brain_info, dict)
assert isinstance(brain_info["RealFakeBrain"], BrainInfo)
assert isinstance(brain_info["RealFakeBrain"].visual_observations, list)
assert isinstance(brain_info["RealFakeBrain"].vector_observations, np.ndarray)
assert (
len(brain_info["RealFakeBrain"].visual_observations)
== brain.number_visual_observations
)
assert len(brain_info["RealFakeBrain"].vector_observations) == len(
brain_info["RealFakeBrain"].agents
)
assert (
len(brain_info["RealFakeBrain"].vector_observations[0])
== brain.vector_observation_space_size * brain.num_stacked_vector_observations
)
print("\n\n\n\n\n\n\n" + str(brain_info["RealFakeBrain"].local_done))
assert not brain_info["RealFakeBrain"].local_done[0]
assert brain_info["RealFakeBrain"].local_done[2]
@mock.patch("mlagents.envs.environment.UnityEnvironment.executable_launcher")
@mock.patch("mlagents.envs.environment.UnityEnvironment.get_communicator")
def test_close(mock_communicator, mock_launcher):
comm = MockCommunicator(discrete_action=False, visual_inputs=0)
mock_communicator.return_value = comm
env = UnityEnvironment(" ")
assert env._loaded
env.close()
assert not env._loaded
assert comm.has_been_closed
def test_returncode_to_signal_name():
assert UnityEnvironment.returncode_to_signal_name(-2) == "SIGINT"
assert UnityEnvironment.returncode_to_signal_name(42) is None
assert UnityEnvironment.returncode_to_signal_name("SIGINT") is None
if __name__ == "__main__":
pytest.main()