org.deeplearning4j.nn.params.EmbeddingLayerParamInitializer Maven / Gradle / Ivy
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package org.deeplearning4j.nn.params;
import lombok.val;
import org.deeplearning4j.nn.weights.IWeightInit;
import org.deeplearning4j.nn.weights.WeightInitUtil;
import org.nd4j.linalg.api.ndarray.INDArray;
public class EmbeddingLayerParamInitializer extends DefaultParamInitializer {
private static final EmbeddingLayerParamInitializer INSTANCE = new EmbeddingLayerParamInitializer();
public static EmbeddingLayerParamInitializer getInstance() {
return INSTANCE;
}
protected INDArray createWeightMatrix(long nIn, long nOut, IWeightInit weightInit,
INDArray weightParamView, boolean initializeParameters) {
val shape = new long[] {nIn, nOut};
if (initializeParameters) {
INDArray ret = weightInit.init(1, //Fan in - note that fanIn=1 for embedding layer... if we used layer nIn (i.e., vocab size) the init would depend on vocab size (which doesn't make sense)
nOut, //Fan out
shape, IWeightInit.DEFAULT_WEIGHT_INIT_ORDER, weightParamView);
return ret;
} else {
return WeightInitUtil.reshapeWeights(shape, weightParamView);
}
}
}