def observe(self, points, results):
"""Observe evaluation `results` corresponding to list of `points` in
space.
TODO: document how observe work for this algo
"""
for point, result in zip(points, results):
params = unpack_point(point, self.space)
# Create a trial
trial_id = self.study.storage.create_new_trial(self.study.study_id)
trial = optuna.trial.Trial(self.study, trial_id)
# Set the params
for i, (param_name, _) in enumerate(iterdims(self.space)):
distribution = self.dimensions[param_name]
param_value_internal = distribution.to_internal_repr(params[i])
self.study.storage.set_trial_param(trial_id, param_name,
param_value_internal,
distribution)
# Report the objective
trial.report(result['objective'])
self.study.storage.set_trial_state(
trial_id, optuna.structs.TrialState.COMPLETE)
def observe(self, points, results):
"""Observe evaluation `results` corresponding to list of `points` in
space.
Save current point and gradient corresponding to this point.
"""
self.optimizer.tell(
[unpack_point(point, self.space) for point in points],
[r['objective'] for r in results])