smac.optimizer.configuration_chooser.epm_chooser

Classes

EPMChooser(scenario, stats, runhistory, ...)

Interface to train the EPM and generate/choose next configurations.
class smac.optimizer.configuration_chooser.epm_chooser.EPMChooser(scenario, stats, runhistory, runhistory2epm, model, acq_optimizer, acquisition_func, rng, restore_incumbent=None, random_configuration_chooser=<smac.optimizer.configuration_chooser.random_chooser.ChooserNoCoolDown object>, predict_x_best=True, min_samples_model=1, **epm_chooser_kwargs)[source]

Bases: object

Interface to train the EPM and generate/choose next configurations.

Parameters

  • scenario (smac.scenario.scenario.Scenario) – Scenario object

  • stats (smac.stats.stats.Stats) – statistics object with configuration budgets

  • runhistory (smac.runhistory.runhistory.RunHistory) – runhistory with all runs so far

  • model (smac.epm.rf_with_instances.RandomForestWithInstances) – empirical performance model (right now, we support only RandomForestWithInstances)

  • acq_optimizer (smac.optimizer.ei_optimization.AcquisitionFunctionMaximizer) – Optimizer of acquisition function.

  • restore_incumbent (Configuration) – incumbent to be used from the start. ONLY used to restore states.

  • rng (np.random.RandomState) – Random number generator

  • random_configuration_chooser (RandomChooser) –

    Chooser for random configuration – one of

    • ChooserNoCoolDown(modulus)

    • ChooserLinearCoolDown(start_modulus, modulus_increment, end_modulus)

  • predict_x_best (bool) – Choose x_best for computing the acquisition function via the model instead of via the observations.

  • min_samples_model (int) – Minimum number of samples to build a model

  • epm_chooser_kwargs (Any:) – additional arguments passed to EPMChooser (Might be used by its subclasses)

choose_next(incumbent_value=None)[source]

Choose next candidate solution with Bayesian optimization. The suggested configurations depend on the argument acq_optimizer to the SMBO class.

Parameters

incumbent_value (float) – Cost value of incumbent configuration (required for acquisition function); If not given, it will be inferred from runhistory or predicted; if not given and runhistory is empty, it will raise a ValueError.

Return type

Iterator

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