def setup_bo_basics(self):
if self.num_objs == 1:
self.surrogate_model = build_surrogate(func_str=self.surrogate_type,
config_space=self.config_space,
rng=self.rng,
history_hpo_data=self.history_bo_data)
else: # multi-objectives
self.surrogate_model = [build_surrogate(func_str=self.surrogate_type,
config_space=self.config_space,
rng=self.rng,
history_hpo_data=self.history_bo_data)
for _ in range(self.num_objs)]
if self.num_constraints > 0:
self.constraint_models = [build_surrogate(func_str=self.constraint_surrogate_type,
config_space=self.config_space,
rng=self.rng) for _ in range(self.num_constraints)]
self.acquisition_function = build_acq_func(func_str=self.acq_type, model=self.surrogate_model,
constraint_models=self.constraint_models,
mc_times=self.mc_times, ref_point=self.ref_point)
self.optimizer = build_optimizer(func_str=self.acq_optimizer_type,
acq_func=self.acquisition_function,
config_space=self.config_space,
rng=self.rng)
if self.use_trust_region:
types, bounds = get_types(self.config_space)
cont_dim = np.sum(types == 0)
self.turbo_state = TurboState(cont_dim)
def setup_bo_basics(self, acq_type='ei', acq_optimizer_type='local_random'):
self.surrogate_model = build_surrogate(func_str=self.surrogate_type,
config_space=self.config_space,
rng=self.rng,
history_hpo_data=self.history_bo_data)
self.acquisition_function = build_acq_func(func_str=acq_type, model=self.surrogate_model)
self.optimizer = build_optimizer(func_str=acq_optimizer_type,
acq_func=self.acquisition_function,
config_space=self.config_space,
rng=self.rng)
def setup_bo_basics(self):
"""
Prepare the basic BO components.
Returns
-------
An optimizer object.
"""
if self.num_objs == 1 or self.acq_type == 'parego':
self.surrogate_model = build_surrogate(
func_str=self.surrogate_type,
config_space=self.config_space,
rng=self.rng,
history_hpo_data=self.history_bo_data)
else: # multi-objectives
self.surrogate_model = [
build_surrogate(func_str=self.surrogate_type,
config_space=self.config_space,
rng=self.rng,
history_hpo_data=self.history_bo_data)
for _ in range(self.num_objs)
]
if self.num_constraints > 0:
self.constraint_models = [
build_surrogate(func_str=self.constraint_surrogate_type,
config_space=self.config_space,
rng=self.rng)
for _ in range(self.num_constraints)
]
if self.acq_type in ['mesmo', 'mesmoc', 'mesmoc2', 'usemo']:
types, bounds = get_types(self.config_space)
self.acquisition_function = build_acq_func(
func_str=self.acq_type,
model=self.surrogate_model,
constraint_models=self.constraint_models,
types=types,
bounds=bounds)
else:
self.acquisition_function = build_acq_func(
func_str=self.acq_type,
model=self.surrogate_model,
constraint_models=self.constraint_models,
ref_point=self.ref_point)
if self.acq_type == 'usemo':
self.acq_optimizer_type = 'usemo_optimizer'
elif self.acq_type.startswith('mesmo'):
self.acq_optimizer_type = 'mesmo_optimizer'
self.optimizer = build_optimizer(func_str=self.acq_optimizer_type,
acq_func=self.acquisition_function,
config_space=self.config_space,
rng=self.rng)