syne_tune.optimizer.schedulers.searchers.searcher_callback module

class syne_tune.optimizer.schedulers.searchers.searcher_callback.StoreResultsAndModelParamsCallback(add_wallclock_time=True)

Bases: StoreResultsCallback

Extends StoreResultsCallback by also storing the current surrogate model parameters in on_trial_result(). This works for schedulers with model-based searchers. For other schedulers, this callback behaves the same as the superclass.

on_tuning_start(tuner)

Called at start of tuning loop

Parameters:

tuner – Tuner object

on_trial_result(trial, status, result, decision)

Called when a new result (reported by a trial) is observed

The arguments here are inputs or outputs of scheduler.on_trial_result (called just before).

Parameters:

• trial (Trial) – Trial whose report has been received

• status (str) – Status of trial before scheduler.on_trial_result has been called

• result (Dict[str, Any]) – Result dict received

• decision (str) – Decision returned by scheduler.on_trial_result

class syne_tune.optimizer.schedulers.searchers.searcher_callback.SimulatorAndModelParamsCallback

Bases: SimulatorCallback

Extends SimulatorCallback by also storing the current surrogate model parameters in on_trial_result(). This works for schedulers with model-based searchers. For other schedulers, this callback behaves the same as the superclass.

on_tuning_start(tuner)

Called at start of tuning loop

Parameters:

tuner – Tuner object

on_trial_result(trial, status, result, decision)

Called when a new result (reported by a trial) is observed

The arguments here are inputs or outputs of scheduler.on_trial_result (called just before).

Parameters:

• trial (Trial) – Trial whose report has been received

• status (str) – Status of trial before scheduler.on_trial_result has been called

• result (Dict[str, Any]) – Result dict received

• decision (str) – Decision returned by scheduler.on_trial_result