Package ai.djl.training.loss

Contains classes for measuring the Loss of a model.

See: Description

Class Summary

Class	Description
AbstractCompositeLoss	AbstractCompositeLoss is a Loss class that can combine other Losses together to make a larger loss.
HingeLoss	HingeLoss is a type of Loss.
L1Loss	L1Loss calculates L1 loss between label and prediction.
L2Loss	Calculates L2Loss between label and prediction, a.k.a.
Loss	Loss functions (or Cost functions) are used to evaluate the model predictions against true labels for optimization.
MaskedSoftmaxCrossEntropyLoss	MaskedSoftmaxCrossEntropyLoss is an implementation of Loss that only considers a specific number of values for the loss computations, and masks the rest according to the given sequence.
SigmoidBinaryCrossEntropyLoss	SigmoidBinaryCrossEntropyLoss is a type of Loss.
SimpleCompositeLoss	SimpleCompositeLoss is an implementation of the Loss abstract class that can combine different Loss functions by adding the individual losses together.
SingleShotDetectionLoss	SingleShotDetectionLoss is an implementation of Loss.
SoftmaxCrossEntropyLoss	SoftmaxCrossEntropyLoss is a type of Loss that calculates the softmax cross entropy loss.

Package ai.djl.training.loss Description

Contains classes for measuring the Loss of a model.

It contains a main interface Loss and various losses that extend it.