class BOOptimizer:
def __init__(self, config):
self.space = SearchSpace(config=config)
self.utility_function = UtilityFunction(config=config.utility_function,
seed=config.seed)
self.num_warmup = config.utility_function.num_warmup or 5
self.num_iterations = config.utility_function.num_iterations or 10
def _maximize(self):
""" Find argmax of the acquisition function."""
if not self.space.is_observations_valid():
return None
y_max = self.space.y.max()
self.utility_function.gaussian_process.fit(self.space.x, self.space.y)
return self.utility_function.max_compute(
y_max=y_max,
bounds=self.space.bounds,
num_warmup=self.num_warmup,
num_iterations=self.num_iterations,
)
def add_observations(self, configs, metrics):
# Turn configs and metrics into data points
self.space.add_observations(configs=configs, metrics=metrics)
def get_suggestion(self):
x = self._maximize()
return self.space.get_suggestion(x)
def __init__(self, config):
self.space = SearchSpace(config=config)
self.utility_function = UtilityFunction(config=config.utility_function,
seed=config.seed)
self.num_warmup = config.utility_function.num_warmup or 5
self.num_iterations = config.utility_function.num_iterations or 10