def test_get_commit_hash(save_path):
'''Test get_commit_hash function.'''
with pytest.raises(RuntimeError):
utils_file.get_commit_hash(save_path)
subprocess.run(["git", "init"], cwd=save_path)
commit_no = utils_file.get_commit_hash(save_path)
assert commit_no
def run_experiment(parameters):
'''Set up and run an experiment.'''
repository_path = Path(__file__).parent
save_to = parameters['path']
task_name = '{alg}-{learning_rate:.4f}-{gamma:.4f}-{seed:d}'
task_name = task_name.format(**parameters)
save_to = Path(save_to, task_name)
with utils_file.create_directory(save_to, False, False) as log_dir:
parameters['commit'] = utils_file.get_commit_hash(repository_path)
utils_file.save_json(parameters, log_dir / 'hyperparams.json')
parameters['model_path'] = str(log_dir / 'model.pkl')
log_path = str(log_dir / 'monitor_{:d}')
env_name = parameters['env_name']
kwargs = parameters.setdefault('kwargs', {})
env_callable = [
partial(Monitor,
gym.make(env_name, **kwargs),
log_path.format(i),
allow_early_resets=True,
info_keywords=('loss', 'accuracy', 'actions_mean',
'weights_mean', 'actions_std',
'states_mean', 'grads_mean'),
chunk_size=parameters.setdefault('chunk_size', 5))
for i in range(1)
]
try:
run_agent(env_callable, parameters)
except RuntimeError as error:
LOGGER.error('%s, %s', error, parameters)
return parameters
def run_experiment(parameters, trial):
'''Set up and run an experiment.'''
parameters = parameters.copy()
batch_size = [2**i for i in range(5, 12)]
batch_size = int(trial.suggest_categorical('batch_size', batch_size))
obs_version = int(trial.suggest_int('observation_version', 0, 3))
max_history = int(trial.suggest_discrete_uniform('max_history', 5, 50, 5))
learning_rate = float(trial.suggest_loguniform('learning_rate', 1e-5, 1e0))
buffer_size = int(trial.suggest_int('replay_buffer_size', 1e3, 1e5))
parameters.update({
'gamma': float(trial.suggest_uniform('gamma', 0.1, 1.0)),
'replay_buffer_size': buffer_size
})
parameters.setdefault('agent_parameters', {}).update({
'policy': {
'learning_rate': learning_rate
},
'critic': {
'learning_rate': learning_rate
}
})
parameters.setdefault('kwargs', {}).update({
'batch_size':
batch_size,
'version':
int(trial.suggest_int('version', 0, 5)),
'observation_version':
obs_version,
'max_history':
max_history,
'reward_version':
int(trial.suggest_int('reward_version', 0, 1)),
'action_version':
int(trial.suggest_int('action_version', 0, 1))
})
path = Path(parameters['path']) / str(trial.number)
path.mkdir()
parameters['path'] = str(path)
parameters['commit'] = utils_file.get_commit_hash(Path(__file__).parent)
utils_file.save_json(parameters, path / 'parameters.json')
return run_agents(parameters, trial)
def run_experiment(parameters, trial):
'''Set up and run an experiment.'''
parameters = parameters.copy()
parameters.update(get_parameters(trial))
trial_path = Path(parameters['path'], str(trial.number))
trial_path.mkdir()
parameters['path'] = str(trial_path)
parameters['commit'] = utils_file.get_commit_hash(Path(__file__).parent)
log_path = str(trial_path / 'monitor_{:d}')
kwargs = parameters.setdefault('kwargs', {})
utils_file.save_json(parameters, trial_path / 'parameters.json')
wrapped_envs = [
partial(Monitor,
partial(gym.make, parameters['env_name'], **kwargs),
log_path.format(i),
info_keywords=('loss', 'actions_mean', 'weights_mean',
'actions_std', 'states_mean', 'grads_mean'),
chunk_size=parameters.setdefault('chunk_size', 5))
for i in range(1)
]
return -run_agent(wrapped_envs, parameters, trial)
def run_experiment(parameters, trial):
'''Set up and run an experiment.'''
parameters = parameters.copy()
learning_rate = float(trial.suggest_loguniform('learning_rate', 1e-5, 1e0))
buffer_size = int(trial.suggest_int('replay_buffer_size', 1e3, 1e5))
parameters.update({
'gamma': float(trial.suggest_uniform('gamma', 0.1, 1.0)),
'replay_buffer_size': buffer_size
})
parameters.setdefault('agent_parameters', {}).update({
'policy': {
'learning_rate': learning_rate
},
'critic': {
'learning_rate': learning_rate
}
})
path = Path(parameters['path']) / str(trial.number)
path.mkdir()
parameters['path'] = str(path)
parameters['commit'] = utils_file.get_commit_hash(Path(__file__).parent)
utils_file.save_json(parameters, path / 'parameters.json')
return run_agents(parameters, trial)