def test_commandline_args(mock_file):
# No args raises
with pytest.raises(SystemExit):
parse_command_line([])
# Test with defaults
opt = parse_command_line(["mytrainerpath"])
assert opt.trainer_config == {}
assert opt.env_path is None
assert opt.curriculum_config is None
assert opt.sampler_config is None
assert opt.keep_checkpoints == 5
assert opt.lesson == 0
assert opt.resume is False
assert opt.inference is False
assert opt.run_id == "ppo"
assert opt.save_freq == 50000
assert opt.seed == -1
assert opt.base_port == 5005
assert opt.num_envs == 1
assert opt.no_graphics is False
assert opt.debug is False
assert opt.env_args is None
full_args = [
"mytrainerpath",
"--env=./myenvfile",
"--curriculum=./mycurriculum",
"--sampler=./mysample",
"--keep-checkpoints=42",
"--lesson=3",
"--resume",
"--inference",
"--run-id=myawesomerun",
"--save-freq=123456",
"--seed=7890",
"--train",
"--base-port=4004",
"--num-envs=2",
"--no-graphics",
"--debug",
]
opt = parse_command_line(full_args)
assert opt.trainer_config == {}
assert opt.env_path == "./myenvfile"
assert opt.curriculum_config == {}
assert opt.sampler_config == {}
assert opt.keep_checkpoints == 42
assert opt.lesson == 3
assert opt.run_id == "myawesomerun"
assert opt.save_freq == 123456
assert opt.seed == 7890
assert opt.base_port == 4004
assert opt.num_envs == 2
assert opt.no_graphics is True
assert opt.debug is True
assert opt.inference is True
assert opt.resume is True
def test_commandline_args(mock_file):
# No args raises
# with pytest.raises(SystemExit):
# parse_command_line([])
# Test with defaults
opt = parse_command_line(["mytrainerpath"])
assert opt.behaviors == {}
assert opt.env_settings.env_path is None
assert opt.checkpoint_settings.resume is False
assert opt.checkpoint_settings.inference is False
assert opt.checkpoint_settings.run_id == "ppo"
assert opt.checkpoint_settings.initialize_from is None
assert opt.env_settings.seed == -1
assert opt.env_settings.base_port == 5005
assert opt.env_settings.num_envs == 1
assert opt.env_settings.num_areas == 1
assert opt.engine_settings.no_graphics is False
assert opt.debug is False
assert opt.env_settings.env_args is None
full_args = [
"mytrainerpath",
"--env=./myenvfile",
"--inference",
"--run-id=myawesomerun",
"--seed=7890",
"--train",
"--base-port=4004",
"--initialize-from=testdir",
"--num-envs=2",
"--num-areas=2",
"--no-graphics",
"--debug",
]
opt = parse_command_line(full_args)
assert opt.behaviors == {}
assert opt.env_settings.env_path == "./myenvfile"
assert opt.checkpoint_settings.run_id == "myawesomerun"
assert opt.checkpoint_settings.initialize_from == "testdir"
assert opt.env_settings.seed == 7890
assert opt.env_settings.base_port == 4004
assert opt.env_settings.num_envs == 2
assert opt.env_settings.num_areas == 2
assert opt.engine_settings.no_graphics is True
assert opt.debug is True
assert opt.checkpoint_settings.inference is True
assert opt.checkpoint_settings.resume is False
# ignore init if resume is set
full_args.append("--resume")
opt = parse_command_line(full_args)
assert opt.checkpoint_settings.initialize_from is None # ignore init if resume set
assert opt.checkpoint_settings.resume is True
def test_commandline_args(mock_file):
# No args raises
# with pytest.raises(SystemExit):
# parse_command_line([])
# Test with defaults
opt = parse_command_line(["mytrainerpath"])
assert opt.behaviors == {}
assert opt.env_settings.env_path is None
assert opt.parameter_randomization is None
assert opt.checkpoint_settings.lesson == 0
assert opt.checkpoint_settings.resume is False
assert opt.checkpoint_settings.inference is False
assert opt.checkpoint_settings.run_id == "ppo"
assert opt.checkpoint_settings.save_freq == 50000
assert opt.env_settings.seed == -1
assert opt.env_settings.base_port == 5005
assert opt.env_settings.num_envs == 1
assert opt.engine_settings.no_graphics is False
assert opt.debug is False
assert opt.env_settings.env_args is None
full_args = [
"mytrainerpath",
"--env=./myenvfile",
"--lesson=3",
"--resume",
"--inference",
"--run-id=myawesomerun",
"--save-freq=123456",
"--seed=7890",
"--train",
"--base-port=4004",
"--num-envs=2",
"--no-graphics",
"--debug",
]
opt = parse_command_line(full_args)
assert opt.behaviors == {}
assert opt.env_settings.env_path == "./myenvfile"
assert opt.parameter_randomization is None
assert opt.checkpoint_settings.lesson == 3
assert opt.checkpoint_settings.run_id == "myawesomerun"
assert opt.checkpoint_settings.save_freq == 123456
assert opt.env_settings.seed == 7890
assert opt.env_settings.base_port == 4004
assert opt.env_settings.num_envs == 2
assert opt.engine_settings.no_graphics is True
assert opt.debug is True
assert opt.checkpoint_settings.inference is True
assert opt.checkpoint_settings.resume is True
def test_yaml_args(mock_file):
# Test with opts loaded from YAML
DetectDefault.non_default_args.clear()
opt = parse_command_line(["mytrainerpath"])
assert opt.behaviors == {}
assert opt.env_path == "./oldenvfile"
assert opt.parameter_randomization is None
assert opt.keep_checkpoints == 34
assert opt.lesson == 2
assert opt.run_id == "uselessrun"
assert opt.save_freq == 654321
assert opt.seed == 9870
assert opt.base_port == 4001
assert opt.num_envs == 4
assert opt.no_graphics is False
assert opt.debug is False
assert opt.env_args is None
# Test that CLI overrides YAML
full_args = [
"mytrainerpath",
"--env=./myenvfile",
"--keep-checkpoints=42",
"--lesson=3",
"--resume",
"--inference",
"--run-id=myawesomerun",
"--save-freq=123456",
"--seed=7890",
"--train",
"--base-port=4004",
"--num-envs=2",
"--no-graphics",
"--debug",
]
opt = parse_command_line(full_args)
assert opt.behaviors == {}
assert opt.env_path == "./myenvfile"
assert opt.parameter_randomization is None
assert opt.keep_checkpoints == 42
assert opt.lesson == 3
assert opt.run_id == "myawesomerun"
assert opt.save_freq == 123456
assert opt.seed == 7890
assert opt.base_port == 4004
assert opt.num_envs == 2
assert opt.no_graphics is True
assert opt.debug is True
assert opt.inference is True
assert opt.resume is True
def test_yaml_args(mock_file):
# Test with opts loaded from YAML
DetectDefault.non_default_args.clear()
opt = parse_command_line(["mytrainerpath"])
assert opt.behaviors == {}
assert opt.env_settings.env_path == "./oldenvfile"
assert opt.checkpoint_settings.run_id == "uselessrun"
assert opt.checkpoint_settings.initialize_from == "notuselessrun"
assert opt.env_settings.seed == 9870
assert opt.env_settings.base_port == 4001
assert opt.env_settings.num_envs == 4
assert opt.env_settings.num_areas == 4
assert opt.engine_settings.no_graphics is False
assert opt.debug is False
assert opt.env_settings.env_args is None
# Test that CLI overrides YAML
full_args = [
"mytrainerpath",
"--env=./myenvfile",
"--resume",
"--inference",
"--run-id=myawesomerun",
"--seed=7890",
"--train",
"--base-port=4004",
"--num-envs=2",
"--num-areas=2",
"--no-graphics",
"--debug",
"--results-dir=myresults",
]
opt = parse_command_line(full_args)
assert opt.behaviors == {}
assert opt.env_settings.env_path == "./myenvfile"
assert opt.checkpoint_settings.run_id == "myawesomerun"
assert opt.env_settings.seed == 7890
assert opt.env_settings.base_port == 4004
assert opt.env_settings.num_envs == 2
assert opt.env_settings.num_areas == 2
assert opt.engine_settings.no_graphics is True
assert opt.debug is True
assert opt.checkpoint_settings.inference is True
assert opt.checkpoint_settings.resume is True
assert opt.checkpoint_settings.results_dir == "myresults"
def test_env_args(mock_file):
full_args = [
"mytrainerpath",
"--env=./myenvfile",
"--env-args", # Everything after here will be grouped in a list
"--foo=bar",
"--blah",
"baz",
"100",
]
opt = parse_command_line(full_args)
assert opt.env_args == ["--foo=bar", "--blah", "baz", "100"]
def test_sampler_configs(mock_file):
opt = parse_command_line(["mytrainerpath"])
assert opt.parameter_randomization == "sampler1"
def basic_options(extra_args=None):
extra_args = extra_args or {}
args = ["basic_path"]
if extra_args:
args += [f"{k}={v}" for k, v in extra_args.items()]
return parse_command_line(args)
def test_commandline_args():
# No args raises
with pytest.raises(SystemExit):
parse_command_line([])
# Test with defaults
opt = parse_command_line(["mytrainerpath"])
assert opt.trainer_config_path == "mytrainerpath"
assert opt.env_path is None
assert opt.curriculum_folder is None
assert opt.sampler_file_path is None
assert opt.keep_checkpoints == 5
assert opt.lesson == 0
assert opt.load_model is False
assert opt.run_id == "ppo"
assert opt.save_freq == 50000
assert opt.seed == -1
assert opt.train_model is False
assert opt.base_port == 5005
assert opt.num_envs == 1
assert opt.docker_target_name is None
assert opt.no_graphics is False
assert opt.debug is False
assert opt.multi_gpu is False
assert opt.env_args is None
full_args = [
"mytrainerpath",
"--env=./myenvfile",
"--curriculum=./mycurriculum",
"--sampler=./mysample",
"--keep-checkpoints=42",
"--lesson=3",
"--load",
"--run-id=myawesomerun",
"--num-runs=3",
"--save-freq=123456",
"--seed=7890",
"--train",
"--base-port=4004",
"--num-envs=2",
"--docker-target-name=mydockertarget",
"--no-graphics",
"--debug",
"--multi-gpu",
]
opt = parse_command_line(full_args)
assert opt.trainer_config_path == "mytrainerpath"
assert opt.env_path == "./myenvfile"
assert opt.curriculum_folder == "./mycurriculum"
assert opt.sampler_file_path == "./mysample"
assert opt.keep_checkpoints == 42
assert opt.lesson == 3
assert opt.load_model is True
assert opt.run_id == "myawesomerun"
assert opt.save_freq == 123456
assert opt.seed == 7890
assert opt.train_model is True
assert opt.base_port == 4004
assert opt.num_envs == 2
assert opt.docker_target_name == "mydockertarget"
assert opt.no_graphics is True
assert opt.debug is True
assert opt.multi_gpu is True
def test_sampler_configs(mock_file):
opt = parse_command_line(["mytrainerpath"])
assert opt.parameter_randomization == {"sampler1": "foo"}
assert len(opt.curriculum.keys()) == 2
from mlagents_envs.environment import UnityEnvironment
from mlagents.trainers import learn
# This is a non-blocking call that only loads the environment.
# env = UnityEnvironment(file_name=None, seed=1, side_channels=[])
# Start interacting with the evironment.
# env.reset()
# behavior_names = env.behavior_spec.keys()
if __name__ == "__main__":
opts = learn.parse_command_line([
"../../ml-agents/config/trainer_config.yaml", "--run-id=testing_3",
"--force"
])
print(opts)
learn.run_training(1, opts)
def test_sampler_configs(mock_file):
opt = parse_command_line(["mytrainerpath"])
assert isinstance(opt.parameter_randomization["sampler1"], UniformSettings)
assert len(opt.curriculum.keys()) == 2
