Class PercentilePruner

Namespace

OptunaSharp.Pruners

Assembly

OptunaSharp.dll

Pruner to keep the specified percentile of the trials. Port of optuna/pruners/_percentile.py: PercentilePruner.

Prune if the best intermediate value is in the bottom percentile among trials at the same step.

public class PercentilePruner : BasePruner

Inheritance

object

BasePruner

PercentilePruner

Derived

MedianPruner

Inherited Members

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Constructors

PercentilePruner(double, int, int, int, int)

Configures the reference percentile and evidence required before comparing trials.

public PercentilePruner(double percentile, int nStartupTrials = 5, int nWarmupSteps = 0, int intervalSteps = 1, int nMinTrials = 1)

Parameters

percentile double

Percentile which must be between 0 and 100 inclusive (e.g., when given 25.0, top of 25th percentile trials are kept).

nStartupTrials int

Pruning is disabled until the given number of trials finish in the same study.

nWarmupSteps int

Pruning is disabled while the current step is less than nWarmupSteps; the earliest a trial can be pruned is at step == nWarmupSteps.

intervalSteps int

Interval in number of steps between the pruning checks, offset by the warmup steps. If no value has been reported at the time of a pruning check, that particular check will be postponed until a value is reported. Value must be at least 1.

nMinTrials int

Minimum number of reported trial results at a step to judge whether to prune. If the number of reported intermediate values from all trials at the current step is less than nMinTrials, the trial will not be pruned.

Exceptions

ValueError

The percentile is outside [0, 100], a startup/warmup count is negative, or an interval/minimum count is below one.

Methods

Prune(Study, FrozenTrial)

Judge whether the trial should be pruned based on the reported values.

Note that this method is not supposed to be called by library users. Instead, Report(double, long) and ShouldPrune() provide user interfaces to implement pruning mechanism in an objective function.

public override bool Prune(Study study, FrozenTrial trial)

Parameters

study Study

Study object of the target study.

trial FrozenTrial

FrozenTrial object of the target trial. Take a copy before modifying this object.

Returns

bool

A boolean value representing whether the trial should be pruned.

Exceptions

RuntimeError

The study has multiple objectives and the pruning rule requests its scalar direction.

See Also

Official Optuna PercentilePruner reference.