/**
* Apply the regularization
*
* @param layer
* @param gradient
* @param param
*/
public void postApply(Layer layer, INDArray gradient, String param) {
NeuralNetConfiguration conf = layer.conf();
INDArray params = layer.getParam(param);
if (conf.isUseRegularization()
&& conf.getLayer().getL2() > 0
&& !(param.equals(DefaultParamInitializer.BIAS_KEY)))
gradient.addi(
params.mul(
conf.getLayer()
.getL2())); // dC/dw = dC0/dw + lambda/n * w where C0 is pre-l2 cost function
if (conf.isUseRegularization()
&& conf.getLayer().getL1() > 0
&& !(param.equals(DefaultParamInitializer.BIAS_KEY)))
gradient.addi(Transforms.sign(params).muli(conf.getLayer().getL1()));
if (conf.isMiniBatch()) gradient.divi(layer.getInputMiniBatchSize());
if (conf.isConstrainGradientToUnitNorm()) gradient.divi(gradient.norm2(Integer.MAX_VALUE));
}
