Package ai.djl.training.optimizer

package ai.djl.training.optimizer

Contains classes for optimizing a neural network Block.

It contains a main interface Optimizer and various optimizers that extend it. There are also the helpers for learning rates in ai.djl.training.tracker.

Related Packages

Package	Description
ai.djl.training	Contains classes and implementations to train a neural network.

Classes

Class	Description
Adadelta	Adadelta is an Adadelta Optimizer.
Adadelta.Builder	The Builder to construct an Adadelta object.
Adagrad	Adagrad is an AdaGrad Optimizer.
Adagrad.Builder	The Builder to construct an Adagrad object.
Adam	Adam is a generalization of the AdaGrad Optimizer.
Adam.Builder	The Builder to construct an Adam object.
AdamW	Adam is a generalization of the AdaGrad Optimizer.
AdamW.Builder	The Builder to construct an AdamW object.
Nag	Nag is a Nesterov accelerated gradient optimizer.
Nag.Builder	The Builder to construct an Nag object.
Optimizer	An Optimizer updates the weight parameters to minimize the loss function.
Optimizer.OptimizerBuilder<T extends Optimizer.OptimizerBuilder>	The Builder to construct an Optimizer.
RmsProp	The RMSProp Optimizer.
RmsProp.Builder	The Builder to construct an RmsProp object.
Sgd	Sgd is a Stochastic Gradient Descent (SGD) optimizer.
Sgd.Builder	The Builder to construct an Sgd object.