org.deeplearning4j.nn.conf.distribution.Distributions Maven / Gradle / Ivy
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package org.deeplearning4j.nn.conf.distribution;
import org.nd4j.linalg.factory.Nd4j;
public class Distributions {
private Distributions() {}
public static org.nd4j.linalg.api.rng.distribution.Distribution createDistribution(Distribution dist) {
if (dist == null)
return null;
if (dist instanceof NormalDistribution) {
NormalDistribution nd = (NormalDistribution) dist;
return Nd4j.getDistributions().createNormal(nd.getMean(), nd.getStd());
}
if (dist instanceof GaussianDistribution) {
GaussianDistribution nd = (GaussianDistribution) dist;
return Nd4j.getDistributions().createNormal(nd.getMean(), nd.getStd());
}
if (dist instanceof UniformDistribution) {
UniformDistribution ud = (UniformDistribution) dist;
return Nd4j.getDistributions().createUniform(ud.getLower(), ud.getUpper());
}
if (dist instanceof BinomialDistribution) {
BinomialDistribution bd = (BinomialDistribution) dist;
return Nd4j.getDistributions().createBinomial(bd.getNumberOfTrials(), bd.getProbabilityOfSuccess());
}
if (dist instanceof LogNormalDistribution) {
LogNormalDistribution lnd = (LogNormalDistribution) dist;
return Nd4j.getDistributions().createLogNormal(lnd.getMean(), lnd.getStd());
}
if (dist instanceof TruncatedNormalDistribution) {
TruncatedNormalDistribution tnd = (TruncatedNormalDistribution) dist;
return Nd4j.getDistributions().createTruncatedNormal(tnd.getMean(), tnd.getStd());
}
if (dist instanceof OrthogonalDistribution) {
OrthogonalDistribution od = (OrthogonalDistribution) dist;
return Nd4j.getDistributions().createOrthogonal(od.getGain());
}
if (dist instanceof ConstantDistribution) {
ConstantDistribution od = (ConstantDistribution) dist;
return Nd4j.getDistributions().createConstant(od.getValue());
}
throw new RuntimeException("unknown distribution type: " + dist.getClass());
}
}