smac.intensifier.successive_halving

Classes

SuccessiveHalving(scenario[, eta, n_seeds, ...])

Implementation of Succesive Halving supporting multi-fidelity, multi-objective, and multi-processing.

Interfaces

class smac.intensifier.successive_halving.SuccessiveHalving(scenario, eta=3, n_seeds=1, instance_seed_order='shuffle_once', max_incumbents=10, incumbent_selection='highest_observed_budget', seed=None)

Bases: AbstractIntensifier

Implementation of Succesive Halving supporting multi-fidelity, multi-objective, and multi-processing. Internally, a tracker keeps track of configurations and their bracket and stage.

The behaviour of this intensifier is as follows:

• First, adds configurations from the runhistory to the tracker. The first stage is always filled-up. For example, the user provided 4 configs with the tell-method but the first stage requires 8 configs: 4 new configs are sampled and added together with the provided configs as a group to the tracker.

• While loop:

  • If a trial in the tracker has not been yielded yet, yield it.

  • If we are running out of trials, we simply add a new batch of configurations to the first stage.

Note

The implementation natively supports brackets from Hyperband. However, in the case of Successive Halving, only one bracket is used.

Parameters:

• eta (int, defaults to 3) – Input that controls the proportion of configurations discarded in each round of Successive Halving.

• n_seeds (int, defaults to 1) – How many seeds to use for each instance.

• instance_seed_order (str, defaults to "shuffle_once") –

  How to order the instance-seed pairs. Can be set to:

  • None: No shuffling at all and use the instance-seed order provided by the user.

  • shuffle_once: Shuffle the instance-seed keys once and use the same order across all runs.

  • shuffle: Shuffles the instance-seed keys for each bracket individually.

• incumbent_selection (str, defaults to "highest_observed_budget") –

  How to select the incumbent when using budgets. Can be set to:

  • any_budget: Incumbent is the best on any budget i.e., best performance regardless of budget.

  • highest_observed_budget: Incumbent is the best in the highest budget run so far.

  • highest_budget: Incumbent is selected only based on the highest budget.

• max_incumbents (int, defaults to 10) – How many incumbents to keep track of in the case of multi-objective.

• seed (int, defaults to None) – Internal seed used for random events like shuffle seeds.

__post_init__()

Post initialization steps after the runhistory has been set.

Return type:

None

get_instance_seed_budget_keys(config, compare=False)

Returns the instance-seed-budget keys for a given configuration. This method supports highest_budget, which only returns the instance-seed-budget keys for the highest budget (if specified). In this case, the incumbents in update_incumbents are only changed if the costs on the highest budget are lower.

Parameters:

• config (Configuration) – The Configuration to be queried

• compare (bool, defaults to False) – Get rid of the budget information for comparing if the configuration was evaluated on the same instance-seed keys.

Return type:

list[InstanceSeedBudgetKey]

get_state()

The current state of the intensifier. Used to restore the state of the intensifier when continuing a run.

Return type:

dict[str, Any]

get_trials_of_interest(config, *, validate=False, seed=None)

Returns the trials of interest for a given configuration. Expands the keys from get_instance_seed_keys_of_interest with the config.

Return type:

list[TrialInfo]

property meta: dict[str, Any]

Returns the meta data of the created object.

print_tracker()

Prints the number of configurations in each bracket/stage.

Return type:

None

reset()

Reset the internal variables of the intensifier including the tracker.

Return type:

None

set_state(state)

Sets the state of the intensifier. Used to restore the state of the intensifier when continuing a run.

Return type:

None

property uses_budgets: bool

If the intensifier needs to make use of budgets.

property uses_instances: bool

If the intensifier needs to make use of instances.

property uses_seeds: bool

If the intensifier needs to make use of seeds.

previous

smac.intensifier.intensifier

next

smac.initial_design