def GetSuggestions(self, request, context):
"""
Main function to provide suggestion.
"""
algorithm_name, config = OptimizerConfiguration.convertAlgorithmSpec(
request.experiment.spec.algorithm)
if algorithm_name != "bayesianoptimization":
raise Exception(
"Failed to create the algorithm: {}".format(algorithm_name))
if self.is_first_run:
search_space = HyperParameterSearchSpace.convert(
request.experiment)
self.base_service = BaseSkoptService(
base_estimator=config.base_estimator,
n_initial_points=config.n_initial_points,
acq_func=config.acq_func,
acq_optimizer=config.acq_optimizer,
random_state=config.random_state,
search_space=search_space)
self.is_first_run = False
trials = Trial.convert(request.trials)
new_trials = self.base_service.getSuggestions(trials,
request.request_number)
return api_pb2.GetSuggestionsReply(
parameter_assignments=Assignment.generate(new_trials))
class SkoptService(api_pb2_grpc.SuggestionServicer, HealthServicer):
def __init__(self):
super(SkoptService, self).__init__()
self.base_service = None
self.is_first_run = True
def GetSuggestions(self, request, context):
"""
Main function to provide suggestion.
"""
algorithm_name, config = OptimizerConfiguration.convert_algorithm_spec(
request.experiment.spec.algorithm)
if self.is_first_run:
search_space = HyperParameterSearchSpace.convert(
request.experiment)
self.base_service = BaseSkoptService(
base_estimator=config.base_estimator,
n_initial_points=config.n_initial_points,
acq_func=config.acq_func,
acq_optimizer=config.acq_optimizer,
random_state=config.random_state,
search_space=search_space)
self.is_first_run = False
trials = Trial.convert(request.trials)
new_trials = self.base_service.getSuggestions(trials,
request.request_number)
return api_pb2.GetSuggestionsReply(
parameter_assignments=Assignment.generate(new_trials))
def ValidateAlgorithmSettings(self, request, context):
is_valid, message = OptimizerConfiguration.validate_algorithm_spec(
request.experiment.spec.algorithm)
if not is_valid:
context.set_code(grpc.StatusCode.INVALID_ARGUMENT)
context.set_details(message)
logger.error(message)
return api_pb2.ValidateAlgorithmSettingsReply()