import pytest import io import os from unittest.mock import patch from mlagents.trainers.trainer import TrainerFactory from mlagents.trainers.cli_utils import load_config, _load_config from mlagents.trainers.ppo.trainer import PPOTrainer from mlagents.trainers.exception import TrainerConfigError, UnityTrainerException from mlagents.trainers.settings import RunOptions from mlagents.trainers.tests.dummy_config import ppo_dummy_config from mlagents.trainers.environment_parameter_manager import EnvironmentParameterManager from mlagents.trainers.directory_utils import validate_existing_directories @pytest.fixture def dummy_config(): return RunOptions(behaviors={"testbrain": ppo_dummy_config()}) @patch("mlagents_envs.base_env.BehaviorSpec") def test_initialize_ppo_trainer(BehaviorSpecMock, dummy_config): brain_name = "testbrain" training_behaviors = {"testbrain": BehaviorSpecMock()} output_path = "results_dir" train_model = True load_model = False seed = 11 expected_reward_buff_cap = 1 base_config = dummy_config.behaviors expected_config = ppo_dummy_config() def mock_constructor( self, brain, reward_buff_cap, trainer_settings, training, load, seed, artifact_path, ): assert brain == brain_name assert trainer_settings == expected_config assert reward_buff_cap == expected_reward_buff_cap assert training == train_model assert load == load_model assert seed == seed assert artifact_path == os.path.join(output_path, brain_name) with patch.object(PPOTrainer, "__init__", mock_constructor): trainer_factory = TrainerFactory( trainer_config=base_config, output_path=output_path, train_model=train_model, load_model=load_model, seed=seed, param_manager=EnvironmentParameterManager(), ) trainers = {} for brain_name in training_behaviors.keys(): trainers[brain_name] = trainer_factory.generate(brain_name) assert "testbrain" in trainers assert isinstance(trainers["testbrain"], PPOTrainer) def test_handles_no_config_provided(): """ Make sure the trainer setup handles no configs provided at all. """ brain_name = "testbrain" no_default_config = RunOptions().behaviors # Pretend this was created without a YAML file no_default_config.set_config_specified(False) trainer_factory = TrainerFactory( trainer_config=no_default_config, output_path="output_path", train_model=True, load_model=False, seed=42, param_manager=EnvironmentParameterManager(), ) trainer_factory.generate(brain_name) def test_load_config_missing_file(): with pytest.raises(TrainerConfigError): load_config("thisFileDefinitelyDoesNotExist.yaml") def test_load_config_valid_yaml(): file_contents = """ this: - is fine """ fp = io.StringIO(file_contents) res = _load_config(fp) assert res == {"this": ["is fine"]} def test_load_config_invalid_yaml(): file_contents = """ you: - will - not - parse """ with pytest.raises(TrainerConfigError): fp = io.StringIO(file_contents) _load_config(fp) def test_existing_directories(tmp_path): output_path = os.path.join(tmp_path, "runid") # Test fresh new unused path - should do nothing. validate_existing_directories(output_path, False, False) # Test resume with fresh path - should throw an exception. with pytest.raises(UnityTrainerException): validate_existing_directories(output_path, True, False) # make a directory os.mkdir(output_path) # Test try to train w.o. force, should complain with pytest.raises(UnityTrainerException): validate_existing_directories(output_path, False, False) # Test try to train w/ resume - should work validate_existing_directories(output_path, True, False) # Test try to train w/ force - should work validate_existing_directories(output_path, False, True) # Test initialize option init_path = os.path.join(tmp_path, "runid2") with pytest.raises(UnityTrainerException): validate_existing_directories(output_path, False, True, init_path) os.mkdir(init_path) # Should pass since the directory exists now. validate_existing_directories(output_path, False, True, init_path)