io.improbable.keanu.vertices

Interface SamplableWithManyScalars<T extends Tensor<?>>

All Superinterfaces:

HasShape, Samplable<T>, SamplableWithShape<T>

All Known Implementing Classes:

BernoulliVertex, BetaVertex, BinomialVertex, CauchyVertex, ChiSquaredVertex, DirichletVertex, ExponentialVertex, GammaVertex, GaussianVertex, GeometricVertex, HalfCauchyVertex, HalfGaussianVertex, InverseGammaVertex, LaplaceVertex, LogisticVertex, LogNormalVertex, MultinomialVertex, MultivariateGaussianVertex, ParetoVertex, PoissonVertex, SmoothUniformVertex, StudentTVertex, TriangularVertex, UniformIntVertex, UniformVertex

public interface SamplableWithManyScalars<T extends Tensor<?>>
extends Samplable<T>, SamplableWithShape<T>, HasShape

Method Summary

Modifier and Type	Method and Description
default T	sample(KeanuRandom random)
default T	sampleManyScalars(long[] shape)
default T	sampleManyScalars(long[] shape, KeanuRandom random)

Methods inherited from interface io.improbable.keanu.vertices.Samplable

sample

Methods inherited from interface io.improbable.keanu.vertices.SamplableWithShape

sampleWithShape, sampleWithShape

Methods inherited from interface io.improbable.keanu.algorithms.variational.optimizer.HasShape

getShape

Method Detail

sampleManyScalars

default T sampleManyScalars(long[] shape,
                            KeanuRandom random)

sampleManyScalars

default T sampleManyScalars(long[] shape)

sample

default T sample(KeanuRandom random)

Specified by:

sample in interface Samplable<T extends Tensor<?>>

Parameters:

random - source of randomness

Returns:

a sample from the vertex's distribution. For non-probabilistic vertices, this will always be the same value.