Class JanusSmsEmoaCmixSampler

Namespace

OptunaSharp.Samplers

Assembly

OptunaSharp.dll

SMS-EMOA with JANUS-style CMIX candidate generation — the hypervolume-hosted sibling of JanusMooCmixSampler, for low-objective (2–3) suites. SMS-EMOA keeps full control of its steady-state hypervolume selection; past a warm-up a small fraction of children are replaced by an inverse-curvature Gaussian sample (from component_losses or a diagonal-quadratic scalar fallback). See JanusMooCmixSampler for the CMIX parameters and the RNG divergence.

public sealed class JanusSmsEmoaCmixSampler : SmsEmoaSampler

Inheritance

object

BaseSampler

SmsEmoaSampler

JanusSmsEmoaCmixSampler

Inherited Members

SmsEmoaSampler.ReseedRng()

SmsEmoaSampler.InferRelativeSearchSpace(Study, FrozenTrial)

SmsEmoaSampler.SampleIndependent(Study, FrozenTrial, string, BaseDistribution)

SmsEmoaSampler.BeforeTrial(Study, FrozenTrial)

SmsEmoaSampler.AfterTrial(Study, FrozenTrial, TrialState, IReadOnlyList<double>)

BaseSampler.ToString()

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.ReferenceEquals(object, object)

Constructors

JanusSmsEmoaCmixSampler(int, int?, double, string, double, double, double, int, int?, string, string, BaseMutation?, double?, BaseCrossover?, double, double, double)

Configures curvature-informed candidate injection into SMS-EMOA offspring.

public JanusSmsEmoaCmixSampler(int populationSize = 50, int? seed = null, double cmixProb = 0.02, string cmixWindow = "auto", double cmixRidge = 1, double cmixLambda = 1, double cmixSigma = 0.002, int cmixStartGeneration = 3, int? cmixStartTrial = 100, string componentAttr = "component_losses", string scalarFallback = "diag_quadratic", BaseMutation? mutation = null, double? mutationProb = null, BaseCrossover? crossover = null, double crossoverProb = 0.9, double swappingProb = 0.5, double hvReferenceEps = 10)

Parameters

populationSize int

SMS-EMOA population size (default 50).

seed int?

Random seed (seeds both SMS-EMOA and, separately, the CMIX stream).

cmixProb double

Probability a child is replaced by a CMIX sample past the warm-up (default 0.02).

cmixWindow string

Recent-window size for the metric fit: "auto" (= 3·populationSize) or an integer string.

cmixRidge double

Ridge regularization for the metric regression (default 1.0).

cmixLambda double

Levenberg–Marquardt damping added before inverting the metric (default 1.0).

cmixSigma double

Normalized step size scaling the inverse-curvature covariance (default 0.002).

cmixStartGeneration int

Warm-up in generations, used only when cmixStartTrial is null (default 3).

cmixStartTrial int?

Warm-up in trials before CMIX may fire; null derives it from cmixStartGeneration (default 100).

componentAttr string

User-attribute key the CMIX metric reads each trial's residual vector from. The default is component_losses, the key trial.SetComponentLosses writes.

A custom key is read exactly as given, so store the vector with trial.SetUserAttr(componentAttr, …). Only the default key also accepts the legacy rae alias.

CMIX fits the component metric only when every trial in its window carries a numeric vector under this key; otherwise it uses scalarFallback. null turns the component channel off.

scalarFallback string

Scalar metric when no components are present: diag_quadratic (default) or none.

mutation BaseMutation

SMS-EMOA mutation (forwarded).

mutationProb double?

SMS-EMOA mutation probability (forwarded).

crossover BaseCrossover

SMS-EMOA crossover (forwarded).

crossoverProb double

SMS-EMOA crossover probability (forwarded, default 0.9).

swappingProb double

SMS-EMOA swapping probability (forwarded, default 0.5).

hvReferenceEps double

Hypervolume reference-point epsilon (forwarded).

Methods

SampleRelative(Study, FrozenTrial, OrderedDict<string, BaseDistribution>)

Sample parameters in a given search space.

The trial invokes this method lazily when it first needs relative parameters and caches the result for its remaining suggestions. This method is suitable for sampling algorithms that use relationship between parameters such as Gaussian Process and CMA-ES.

public override OrderedDict<string, object?> SampleRelative(Study study, FrozenTrial trial, OrderedDict<string, BaseDistribution> searchSpace)

Parameters

study Study

Study supplying trial history, directions, and storage.

trial FrozenTrial

Current trial snapshot; copy it before modifying its contents.

searchSpace OrderedDict<string, BaseDistribution>

Distributions returned by InferRelativeSearchSpace(Study, FrozenTrial).

Returns

OrderedDict<string, object>

Jointly sampled external parameter values; omitted parameters use independent sampling.