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