Package ai.djl.training.loss

Class L1WeightDecay

java.lang.Object

ai.djl.training.evaluator.Evaluator

ai.djl.training.loss.Loss

ai.djl.training.loss.L1WeightDecay

public class L1WeightDecay
extends Loss

L1WeightDecay calculates L1 penalty of a set of parameters. Used for regularization.

L1 loss is defined as \(L1 = \lambda \sum_i \vert W_i\vert\).

Field Summary

Fields inherited from class ai.djl.training.evaluator.Evaluator

totalInstances

Constructor Summary

Constructors

Constructor	Description
L1WeightDecay(NDList parameters)	Calculates L1 weight decay for regularization.
L1WeightDecay(java.lang.String name, NDList parameters)	Calculates L1 weight decay for regularization.
L1WeightDecay(java.lang.String name, NDList parameters, float lambda)	Calculates L1 weight decay for regularization.

Method Summary

Modifier and Type	Method	Description
NDArray	evaluate(NDList label, NDList prediction)	Calculates the evaluation between the labels and the predictions.

Methods inherited from class ai.djl.training.loss.Loss

addAccumulator, elasticNetWeightedDecay, elasticNetWeightedDecay, elasticNetWeightedDecay, elasticNetWeightedDecay, getAccumulator, hingeLoss, hingeLoss, hingeLoss, l1Loss, l1Loss, l1Loss, l1WeightedDecay, l1WeightedDecay, l1WeightedDecay, l2Loss, l2Loss, l2Loss, l2WeightedDecay, l2WeightedDecay, l2WeightedDecay, maskedSoftmaxCrossEntropyLoss, maskedSoftmaxCrossEntropyLoss, maskedSoftmaxCrossEntropyLoss, quantileL1Loss, quantileL1Loss, resetAccumulator, sigmoidBinaryCrossEntropyLoss, sigmoidBinaryCrossEntropyLoss, sigmoidBinaryCrossEntropyLoss, softmaxCrossEntropyLoss, softmaxCrossEntropyLoss, softmaxCrossEntropyLoss, updateAccumulator

Methods inherited from class ai.djl.training.evaluator.Evaluator

checkLabelShapes, checkLabelShapes, getName

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

L1WeightDecay

public L1WeightDecay(NDList parameters)

Calculates L1 weight decay for regularization.

Parameters:

parameters - holds the model weights that will be penalized

L1WeightDecay

public L1WeightDecay(java.lang.String name,
                     NDList parameters)

Calculates L1 weight decay for regularization.

Parameters:

name - the name of the penalty

parameters - holds the model weights that will be penalized

L1WeightDecay

public L1WeightDecay(java.lang.String name,
                     NDList parameters,
                     float lambda)

Calculates L1 weight decay for regularization.

Parameters:

name - the name of the penalty

parameters - holds the model weights that will be penalized

lambda - the weight to apply to the penalty value, default 1

Method Detail

evaluate

public NDArray evaluate(NDList label,
                        NDList prediction)

Calculates the evaluation between the labels and the predictions.

Specified by:

evaluate in class Evaluator

Parameters:

label - the correct values

prediction - the predicted values

Returns:

the evaluation result