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。
您最多选择25个主题 主题必须以中文或者字母或数字开头,可以包含连字符 (-),并且长度不得超过35个字符
 
 
 
 
 

90 行
3.4 KiB

import unittest.mock as mock
from unittest.mock import MagicMock
import unittest
from mlagents.envs.subprocess_environment import *
from mlagents.envs import UnityEnvironmentException, BrainInfo
def mock_env_factory(worker_id: int):
return mock.create_autospec(spec=BaseUnityEnvironment)
class MockEnvWorker:
def __init__(self, worker_id):
self.worker_id = worker_id
self.process = None
self.conn = None
self.send = MagicMock()
self.recv = MagicMock()
class SubprocessEnvironmentTest(unittest.TestCase):
def test_environments_are_created(self):
SubprocessUnityEnvironment.create_worker = MagicMock()
env = SubprocessUnityEnvironment(mock_env_factory, 2)
# Creates two processes
self.assertEqual(env.create_worker.call_args_list, [
mock.call(0, mock_env_factory),
mock.call(1, mock_env_factory)
])
self.assertEqual(len(env.envs), 2)
def test_step_async_fails_when_waiting(self):
env = SubprocessUnityEnvironment(mock_env_factory, 0)
env.waiting = True
with self.assertRaises(UnityEnvironmentException):
env.step_async(vector_action=[])
@staticmethod
def test_step_async_splits_input_by_agent_count():
env = SubprocessUnityEnvironment(mock_env_factory, 0)
env.env_agent_counts = {
'MockBrain': [1, 3, 5]
}
env.envs = [
MockEnvWorker(0),
MockEnvWorker(1),
MockEnvWorker(2),
]
env_0_actions = [[1.0, 2.0]]
env_1_actions = ([[3.0, 4.0]] * 3)
env_2_actions = ([[5.0, 6.0]] * 5)
vector_action = {
'MockBrain': env_0_actions + env_1_actions + env_2_actions
}
env.step_async(vector_action=vector_action)
env.envs[0].send.assert_called_with('step', ({'MockBrain': env_0_actions}, {}, {}, {}))
env.envs[1].send.assert_called_with('step', ({'MockBrain': env_1_actions}, {}, {}, {}))
env.envs[2].send.assert_called_with('step', ({'MockBrain': env_2_actions}, {}, {}, {}))
def test_step_async_sets_waiting(self):
env = SubprocessUnityEnvironment(mock_env_factory, 0)
env.step_async(vector_action=[])
self.assertTrue(env.waiting)
def test_step_await_fails_if_not_waiting(self):
env = SubprocessUnityEnvironment(mock_env_factory, 0)
with self.assertRaises(UnityEnvironmentException):
env.step_await()
def test_step_await_combines_brain_info(self):
all_brain_info_env0 = {
'MockBrain': BrainInfo([], [[1.0, 2.0], [1.0, 2.0]], [], agents=[1, 2], memory=np.zeros((0,0)))
}
all_brain_info_env1 = {
'MockBrain': BrainInfo([], [[3.0, 4.0]], [], agents=[3], memory=np.zeros((0,0)))
}
env_worker_0 = MockEnvWorker(0)
env_worker_0.recv.return_value = EnvironmentResponse('step', 0, all_brain_info_env0)
env_worker_1 = MockEnvWorker(1)
env_worker_1.recv.return_value = EnvironmentResponse('step', 1, all_brain_info_env1)
env = SubprocessUnityEnvironment(mock_env_factory, 0)
env.envs = [env_worker_0, env_worker_1]
env.waiting = True
combined_braininfo = env.step_await()['MockBrain']
self.assertEqual(
combined_braininfo.vector_observations.tolist(),
[[1.0, 2.0], [1.0, 2.0], [3.0, 4.0]]
)
self.assertEqual(combined_braininfo.agents, ['0-1', '0-2', '1-3'])