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227 行
8.7 KiB
227 行
8.7 KiB
from unittest import mock
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from unittest.mock import Mock, MagicMock
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import unittest
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import pytest
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from queue import Empty as EmptyQueue
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from mlagents.trainers.subprocess_env_manager import (
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SubprocessEnvManager,
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EnvironmentResponse,
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StepResponse,
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EnvironmentCommand,
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)
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from mlagents.trainers.env_manager import EnvironmentStep
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from mlagents_envs.base_env import BaseEnv
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from mlagents_envs.side_channel.engine_configuration_channel import EngineConfig
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from mlagents_envs.side_channel.stats_side_channel import StatsAggregationMethod
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from mlagents_envs.exception import UnityEnvironmentException
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from mlagents.trainers.tests.simple_test_envs import SimpleEnvironment
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from mlagents.trainers.stats import StatsReporter
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from mlagents.trainers.agent_processor import AgentManagerQueue
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from mlagents.trainers.tests.test_simple_rl import (
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_check_environment_trains,
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PPO_CONFIG,
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DebugWriter,
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)
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def mock_env_factory(worker_id):
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return mock.create_autospec(spec=BaseEnv)
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class MockEnvWorker:
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def __init__(self, worker_id, resp=None):
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self.worker_id = worker_id
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self.process = None
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self.conn = None
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self.send = Mock()
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self.recv = Mock(return_value=resp)
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self.waiting = False
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def create_worker_mock(worker_id, step_queue, env_factor, engine_c):
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return MockEnvWorker(
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worker_id, EnvironmentResponse(EnvironmentCommand.RESET, worker_id, worker_id)
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)
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class SubprocessEnvManagerTest(unittest.TestCase):
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@mock.patch(
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"mlagents.trainers.subprocess_env_manager.SubprocessEnvManager.create_worker"
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)
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def test_environments_are_created(self, mock_create_worker):
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mock_create_worker.side_effect = create_worker_mock
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env = SubprocessEnvManager(mock_env_factory, EngineConfig.default_config(), 2)
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# Creates two processes
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env.create_worker.assert_has_calls(
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[
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mock.call(
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0, env.step_queue, mock_env_factory, EngineConfig.default_config()
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),
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mock.call(
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1, env.step_queue, mock_env_factory, EngineConfig.default_config()
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),
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]
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)
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self.assertEqual(len(env.env_workers), 2)
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@mock.patch(
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"mlagents.trainers.subprocess_env_manager.SubprocessEnvManager.create_worker"
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)
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def test_reset_passes_reset_params(self, mock_create_worker):
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mock_create_worker.side_effect = create_worker_mock
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manager = SubprocessEnvManager(
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mock_env_factory, EngineConfig.default_config(), 1
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)
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params = {"test": "params"}
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manager._reset_env(params)
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manager.env_workers[0].send.assert_called_with(
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EnvironmentCommand.RESET, (params)
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)
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@mock.patch(
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"mlagents.trainers.subprocess_env_manager.SubprocessEnvManager.create_worker"
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)
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def test_reset_collects_results_from_all_envs(self, mock_create_worker):
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mock_create_worker.side_effect = create_worker_mock
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manager = SubprocessEnvManager(
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mock_env_factory, EngineConfig.default_config(), 4
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)
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params = {"test": "params"}
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res = manager._reset_env(params)
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for i, env in enumerate(manager.env_workers):
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env.send.assert_called_with(EnvironmentCommand.RESET, (params))
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env.recv.assert_called()
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# Check that the "last steps" are set to the value returned for each step
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self.assertEqual(
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manager.env_workers[i].previous_step.current_all_step_result, i
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)
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assert res == list(map(lambda ew: ew.previous_step, manager.env_workers))
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@mock.patch(
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"mlagents.trainers.subprocess_env_manager.SubprocessEnvManager.create_worker"
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)
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def test_step_takes_steps_for_all_non_waiting_envs(self, mock_create_worker):
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mock_create_worker.side_effect = create_worker_mock
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manager = SubprocessEnvManager(
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mock_env_factory, EngineConfig.default_config(), 3
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)
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manager.step_queue = Mock()
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manager.step_queue.get_nowait.side_effect = [
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EnvironmentResponse(EnvironmentCommand.STEP, 0, StepResponse(0, None, {})),
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EnvironmentResponse(EnvironmentCommand.STEP, 1, StepResponse(1, None, {})),
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EmptyQueue(),
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]
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step_mock = Mock()
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last_steps = [Mock(), Mock(), Mock()]
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manager.env_workers[0].previous_step = last_steps[0]
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manager.env_workers[1].previous_step = last_steps[1]
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manager.env_workers[2].previous_step = last_steps[2]
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manager.env_workers[2].waiting = True
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manager._take_step = Mock(return_value=step_mock)
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res = manager._step()
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for i, env in enumerate(manager.env_workers):
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if i < 2:
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env.send.assert_called_with(EnvironmentCommand.STEP, step_mock)
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manager.step_queue.get_nowait.assert_called()
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# Check that the "last steps" are set to the value returned for each step
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self.assertEqual(
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manager.env_workers[i].previous_step.current_all_step_result, i
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)
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assert res == [
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manager.env_workers[0].previous_step,
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manager.env_workers[1].previous_step,
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]
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@mock.patch("mlagents.trainers.subprocess_env_manager.SubprocessEnvManager._step")
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@mock.patch(
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"mlagents.trainers.subprocess_env_manager.SubprocessEnvManager.training_behaviors",
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new_callable=mock.PropertyMock,
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)
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@mock.patch(
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"mlagents.trainers.subprocess_env_manager.SubprocessEnvManager.create_worker"
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)
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def test_advance(self, mock_create_worker, training_behaviors_mock, step_mock):
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brain_name = "testbrain"
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action_info_dict = {brain_name: MagicMock()}
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mock_create_worker.side_effect = create_worker_mock
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env_manager = SubprocessEnvManager(
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mock_env_factory, EngineConfig.default_config(), 3
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)
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training_behaviors_mock.return_value = [brain_name]
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agent_manager_mock = mock.Mock()
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mock_policy = mock.Mock()
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agent_manager_mock.policy_queue.get_nowait.side_effect = [
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mock_policy,
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mock_policy,
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AgentManagerQueue.Empty(),
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]
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env_manager.set_agent_manager(brain_name, agent_manager_mock)
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step_info_dict = {brain_name: (Mock(), Mock())}
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env_stats = {
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"averaged": (1.0, StatsAggregationMethod.AVERAGE),
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"most_recent": (2.0, StatsAggregationMethod.MOST_RECENT),
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}
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step_info = EnvironmentStep(step_info_dict, 0, action_info_dict, env_stats)
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step_mock.return_value = [step_info]
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env_manager.process_steps(env_manager.get_steps())
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# Test add_experiences
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env_manager._step.assert_called_once()
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agent_manager_mock.add_experiences.assert_called_once_with(
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step_info.current_all_step_result[brain_name][0],
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step_info.current_all_step_result[brain_name][1],
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0,
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step_info.brain_name_to_action_info[brain_name],
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)
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# Test policy queue
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assert env_manager.policies[brain_name] == mock_policy
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assert agent_manager_mock.policy == mock_policy
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@pytest.mark.parametrize("num_envs", [1, 4])
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def test_subprocess_env_endtoend(num_envs):
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def simple_env_factory(worker_id, config):
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env = SimpleEnvironment(["1D"], use_discrete=True)
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return env
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env_manager = SubprocessEnvManager(
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simple_env_factory, EngineConfig.default_config(), num_envs
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)
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# Run PPO using env_manager
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_check_environment_trains(
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simple_env_factory(0, []),
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{"1D": PPO_CONFIG},
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env_manager=env_manager,
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success_threshold=None,
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)
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# Note we can't check the env's rewards directly (since they're in separate processes) so we
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# check the StatsReporter's debug stat writer's last reward.
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assert isinstance(StatsReporter.writers[0], DebugWriter)
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assert all(
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val > 0.7 for val in StatsReporter.writers[0].get_last_rewards().values()
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)
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env_manager.close()
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@pytest.mark.parametrize("num_envs", [1, 4])
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def test_subprocess_env_raises_errors(num_envs):
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def failing_env_factory(worker_id, config):
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import time
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# Sleep momentarily to allow time for the EnvManager to be waiting for the
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# subprocess response. We won't be able to capture failures from the subprocess
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# that cause it to close the pipe before we can send the first message.
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time.sleep(0.1)
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raise UnityEnvironmentException()
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env_manager = SubprocessEnvManager(
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failing_env_factory, EngineConfig.default_config(), num_envs
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)
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with pytest.raises(UnityEnvironmentException):
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env_manager.reset()
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env_manager.close()
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