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 pytest
from unittest.mock import patch, call, Mock
from mlagents.trainers.meta_curriculum import MetaCurriculum
from mlagents.trainers.exception import MetaCurriculumError
class MetaCurriculumTest(MetaCurriculum):
"""This class allows us to test MetaCurriculum objects without calling
MetaCurriculum's __init__ function.
"""
def __init__(self, brains_to_curriculums):
self._brains_to_curriculums = brains_to_curriculums
@pytest.fixture
def default_reset_parameters():
return {'param1' : 1, 'param2' : 2, 'param3' : 3}
@pytest.fixture
def more_reset_parameters():
return {'param4' : 4, 'param5' : 5, 'param6' : 6}
@pytest.fixture
def measure_vals():
return {'Brain1' : 0.2, 'Brain2' : 0.3}
@pytest.fixture
def reward_buff_sizes():
return {'Brain1' : 7, 'Brain2' : 8}
@patch('mlagents.trainers.Curriculum.get_config', return_value={})
@patch('mlagents.trainers.Curriculum.__init__', return_value=None)
@patch('os.listdir', return_value=['Brain1.json', 'Brain2.json'])
def test_init_meta_curriculum_happy_path(listdir, mock_curriculum_init,
mock_curriculum_get_config,
default_reset_parameters):
meta_curriculum = MetaCurriculum('test/', default_reset_parameters)
assert len(meta_curriculum.brains_to_curriculums) == 2
assert 'Brain1' in meta_curriculum.brains_to_curriculums
assert 'Brain2' in meta_curriculum.brains_to_curriculums
calls = [call('test/Brain1.json', default_reset_parameters),
call('test/Brain2.json', default_reset_parameters)]
mock_curriculum_init.assert_has_calls(calls)
@patch('os.listdir', side_effect=NotADirectoryError())
def test_init_meta_curriculum_bad_curriculum_folder_raises_error(listdir):
with pytest.raises(MetaCurriculumError):
MetaCurriculum('test/', default_reset_parameters)
@patch('mlagents.trainers.Curriculum')
@patch('mlagents.trainers.Curriculum')
def test_set_lesson_nums(curriculum_a, curriculum_b):
meta_curriculum = MetaCurriculumTest({'Brain1' : curriculum_a,
'Brain2' : curriculum_b})
meta_curriculum.lesson_nums = {'Brain1' : 1, 'Brain2' : 3}
assert curriculum_a.lesson_num == 1
assert curriculum_b.lesson_num == 3
@patch('mlagents.trainers.Curriculum')
@patch('mlagents.trainers.Curriculum')
def test_increment_lessons(curriculum_a, curriculum_b, measure_vals):
meta_curriculum = MetaCurriculumTest({'Brain1' : curriculum_a,
'Brain2' : curriculum_b})
meta_curriculum.increment_lessons(measure_vals)
curriculum_a.increment_lesson.assert_called_with(0.2)
curriculum_b.increment_lesson.assert_called_with(0.3)
@patch('mlagents.trainers.Curriculum')
@patch('mlagents.trainers.Curriculum')
def test_increment_lessons_with_reward_buff_sizes(curriculum_a, curriculum_b,
measure_vals,
reward_buff_sizes):
curriculum_a.min_lesson_length = 5
curriculum_b.min_lesson_length = 10
meta_curriculum = MetaCurriculumTest({'Brain1' : curriculum_a,
'Brain2' : curriculum_b})
meta_curriculum.increment_lessons(measure_vals,
reward_buff_sizes=reward_buff_sizes)
curriculum_a.increment_lesson.assert_called_with(0.2)
curriculum_b.increment_lesson.assert_not_called()
@patch('mlagents.trainers.Curriculum')
@patch('mlagents.trainers.Curriculum')
def test_set_all_curriculums_to_lesson_num(curriculum_a, curriculum_b):
meta_curriculum = MetaCurriculumTest({'Brain1' : curriculum_a,
'Brain2' : curriculum_b})
meta_curriculum.set_all_curriculums_to_lesson_num(2)
assert curriculum_a.lesson_num == 2
assert curriculum_b.lesson_num == 2
@patch('mlagents.trainers.Curriculum')
@patch('mlagents.trainers.Curriculum')
def test_get_config(curriculum_a, curriculum_b, default_reset_parameters,
more_reset_parameters):
curriculum_a.get_config.return_value = default_reset_parameters
curriculum_b.get_config.return_value = default_reset_parameters
meta_curriculum = MetaCurriculumTest({'Brain1' : curriculum_a,
'Brain2' : curriculum_b})
assert meta_curriculum.get_config() == default_reset_parameters
curriculum_b.get_config.return_value = more_reset_parameters
new_reset_parameters = dict(default_reset_parameters)
new_reset_parameters.update(more_reset_parameters)
assert meta_curriculum.get_config() == new_reset_parameters