AdaGradDA

public class AdaGradDA

Optimizer that implements the Adagrad Dual-Averaging algorithm.

This optimizer takes care of regularization of unseen features in a mini batch by updating them when they are seen with a closed form update rule that is equivalent to having updated them on every mini-batch.

AdagradDA is typically used when there is a need for large sparsity in the trained model. This optimizer only guarantees sparsity for linear models. Be careful when using AdagradDA for deep networks as it will require careful initialization of the gradient accumulators for it to train.

Constants

String	ACCUMULATOR
float	INITIAL_ACCUMULATOR_DEFAULT
float	L1_STRENGTH_DEFAULT
float	L2_STRENGTH_DEFAULT
float	LEARNING_RATE_DEFAULT
String	SQUARED_ACCUMULATOR

Inherited Constants

From class org.tensorflow.framework.optimizers.Optimizer

String VARIABLE_V2

Public Constructors

	AdaGradDA(Graph graph) Creates an AdaGradDA Optimizer
	AdaGradDA(Graph graph, float learningRate) Creates an AdaGradDA Optimizer
	AdaGradDA(Graph graph, float learningRate, float initialAccumulatorValue, float l1Strength, float l2Strength) Creates an AdaGradDA Optimizer
	AdaGradDA(Graph graph, String name, float learningRate) Creates an AdaGradDA Optimizer
	AdaGradDA(Graph graph, String name, float learningRate, float initialAccumulatorValue, float l1Strength, float l2Strength) Creates an AdaGradDA Optimizer

Public Methods

String	getOptimizerName() Get the Name of the optimizer.
String	toString()

Inherited Methods

From class org.tensorflow.framework.optimizers.Optimizer

Op	applyGradients(List<GradAndVar<? extends TType>> gradsAndVars, String name) Applies gradients to variables
<T extends TType> List<GradAndVar<?>>	computeGradients(Operand<?> loss) Computes the gradients based on a loss operand.
static String	createName(Output<? extends TType> variable, String slotName) Creates a name by combining a variable name and a slot name
abstract String	getOptimizerName() Get the Name of the optimizer.
<T extends TType> Optional<Variable<T>>	getSlot(Output<T> var, String slotName) Gets the slot associated with the specified variable and slot name.
final Ops	getTF() Gets the Optimizer's Ops instance
Op	minimize(Operand<?> loss) Minimizes the loss by updating the variables
Op	minimize(Operand<?> loss, String name) Minimizes the loss by updating the variables

From class java.lang.Object

boolean	equals(Object arg0)
final Class<?>	getClass()
int	hashCode()
final void	notify()
final void	notifyAll()
String	toString()
final void	wait(long arg0, int arg1)
final void	wait(long arg0)
final void	wait()

Constants

public static final String ACCUMULATOR

Constant Value: "gradient_accumulator"

public static final float INITIAL_ACCUMULATOR_DEFAULT

Constant Value: 0.1

public static final float L1_STRENGTH_DEFAULT

Constant Value: 0.0

public static final float L2_STRENGTH_DEFAULT

Constant Value: 0.0

public static final float LEARNING_RATE_DEFAULT

Constant Value: 0.001