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158 行
5.1 KiB
158 行
5.1 KiB
import pytest
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from unittest.mock import MagicMock, patch
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from mlagents.trainers import learn
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from mlagents.trainers.trainer_controller import TrainerController
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from mlagents.trainers.learn import parse_command_line
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def basic_options(extra_args=None):
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extra_args = extra_args or {}
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args = ["basic_path"]
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if extra_args:
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args += [f"{k}={v}" for k, v in extra_args.items()]
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return parse_command_line(args)
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@patch("mlagents.trainers.learn.TrainerFactory")
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@patch("mlagents.trainers.learn.SamplerManager")
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@patch("mlagents.trainers.learn.SubprocessEnvManager")
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@patch("mlagents.trainers.learn.create_environment_factory")
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@patch("mlagents.trainers.learn.load_config")
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def test_run_training(
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load_config,
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create_environment_factory,
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subproc_env_mock,
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sampler_manager_mock,
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trainer_factory_mock,
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):
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mock_env = MagicMock()
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mock_env.external_brain_names = []
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mock_env.academy_name = "TestAcademyName"
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create_environment_factory.return_value = mock_env
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trainer_config_mock = MagicMock()
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load_config.return_value = trainer_config_mock
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mock_init = MagicMock(return_value=None)
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with patch.object(TrainerController, "__init__", mock_init):
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with patch.object(TrainerController, "start_learning", MagicMock()):
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learn.run_training(0, 0, basic_options(), MagicMock())
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mock_init.assert_called_once_with(
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trainer_factory_mock.return_value,
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"./models/ppo-0",
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"./summaries",
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"ppo-0",
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50000,
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None,
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False,
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0,
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sampler_manager_mock.return_value,
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None,
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)
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@patch("mlagents.trainers.learn.SamplerManager")
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@patch("mlagents.trainers.learn.SubprocessEnvManager")
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@patch("mlagents.trainers.learn.create_environment_factory")
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@patch("mlagents.trainers.learn.load_config")
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def test_docker_target_path(
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load_config, create_environment_factory, subproc_env_mock, sampler_manager_mock
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):
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mock_env = MagicMock()
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mock_env.external_brain_names = []
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mock_env.academy_name = "TestAcademyName"
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create_environment_factory.return_value = mock_env
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trainer_config_mock = MagicMock()
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load_config.return_value = trainer_config_mock
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options_with_docker_target = basic_options({"--docker-target-name": "dockertarget"})
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mock_init = MagicMock(return_value=None)
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with patch.object(TrainerController, "__init__", mock_init):
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with patch.object(TrainerController, "start_learning", MagicMock()):
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learn.run_training(0, 0, options_with_docker_target, MagicMock())
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mock_init.assert_called_once()
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assert mock_init.call_args[0][1] == "/dockertarget/models/ppo-0"
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assert mock_init.call_args[0][2] == "/dockertarget/summaries"
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def test_commandline_args():
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# No args raises
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with pytest.raises(SystemExit):
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parse_command_line([])
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# Test with defaults
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opt = parse_command_line(["mytrainerpath"])
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assert opt.trainer_config_path == "mytrainerpath"
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assert opt.env_path is None
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assert opt.curriculum_folder is None
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assert opt.sampler_file_path is None
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assert opt.keep_checkpoints == 5
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assert opt.lesson == 0
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assert opt.load_model is False
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assert opt.run_id == "ppo"
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assert opt.save_freq == 50000
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assert opt.seed == -1
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assert opt.train_model is False
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assert opt.base_port == 5005
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assert opt.num_envs == 1
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assert opt.docker_target_name is None
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assert opt.no_graphics is False
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assert opt.debug is False
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assert opt.multi_gpu is False
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assert opt.env_args is None
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full_args = [
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"mytrainerpath",
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"--env=./myenvfile",
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"--curriculum=./mycurriculum",
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"--sampler=./mysample",
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"--keep-checkpoints=42",
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"--lesson=3",
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"--load",
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"--run-id=myawesomerun",
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"--num-runs=3",
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"--save-freq=123456",
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"--seed=7890",
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"--train",
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"--base-port=4004",
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"--num-envs=2",
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"--docker-target-name=mydockertarget",
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"--no-graphics",
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"--debug",
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"--multi-gpu",
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]
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opt = parse_command_line(full_args)
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assert opt.trainer_config_path == "mytrainerpath"
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assert opt.env_path == "./myenvfile"
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assert opt.curriculum_folder == "./mycurriculum"
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assert opt.sampler_file_path == "./mysample"
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assert opt.keep_checkpoints == 42
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assert opt.lesson == 3
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assert opt.load_model is True
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assert opt.run_id == "myawesomerun"
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assert opt.save_freq == 123456
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assert opt.seed == 7890
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assert opt.train_model is True
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assert opt.base_port == 4004
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assert opt.num_envs == 2
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assert opt.docker_target_name == "mydockertarget"
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assert opt.no_graphics is True
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assert opt.debug is True
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assert opt.multi_gpu is True
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def test_env_args():
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full_args = [
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"mytrainerpath",
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"--env=./myenvfile",
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"--env-args", # Everything after here will be grouped in a list
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"--foo=bar",
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"--blah",
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"baz",
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"100",
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]
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opt = parse_command_line(full_args)
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assert opt.env_args == ["--foo=bar", "--blah", "baz", "100"]
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