AdaGrad

public class AdaGrad

Optimizer that implements the Adagrad algorithm.

Adagrad is an optimizer with parameter-specific learning rates, which are adapted relative to how frequently a parameter gets updated during training. The more updates a parameter receives, the smaller the updates.

See Also

• Duchi, J, et al., 2011, Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
• Duchi, J, et al., 2013, Proximal and First-Order Methods for Convex Optimization, Introduction Section 1

Constants

String	ACCUMULATOR
float	INITIAL_ACCUMULATOR_DEFAULT
float	LEARNING_RATE_DEFAULT

Inherited Constants

From class org.tensorflow.framework.optimizers.Optimizer

String

VARIABLE_V2

Public Constructors

	AdaGrad(Graph graph) Creates an AdaGrad Optimizer
	AdaGrad(Graph graph, float learningRate) Creates an AdaGrad Optimizer
	AdaGrad(Graph graph, float learningRate, float initialAccumulatorValue) Creates an AdaGrad Optimizer
	AdaGrad(Graph graph, String name, float learningRate) Creates an AdaGrad Optimizer
	AdaGrad(Graph graph, String name, float learningRate, float initialAccumulatorValue) Creates an AdaGrad 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: "accumulator"

public static final float INITIAL_ACCUMULATOR_DEFAULT

Constant Value: 0.01

public static final float LEARNING_RATE_DEFAULT

Constant Value: 0.001

Public Constructors

public AdaGrad (Graph graph)

Creates an AdaGrad Optimizer

Parameters

graph	the TensorFlow Graph

public AdaGrad (Graph graph, float learningRate)

Creates an AdaGrad Optimizer

Parameters

graph	the TensorFlow Graph
learningRate	the learning rate

public AdaGrad (Graph graph, float learningRate, float initialAccumulatorValue)

Creates an AdaGrad Optimizer

Parameters

graph	the TensorFlow Graph
learningRate	the learning rate
initialAccumulatorValue	Starting value for the accumulators, must be non-negative.

Throws

IllegalArgumentException	if initialAccumulatorValue is negative

public AdaGrad (Graph graph, String name, float learningRate)

Creates an AdaGrad Optimizer

Parameters

graph	the TensorFlow Graph
name	the name for this Optimizer (defaults to 'Adagrad')
learningRate	the learning rate

public AdaGrad (Graph graph, String name, float learningRate, float initialAccumulatorValue)

Creates an AdaGrad Optimizer

Parameters

graph	the TensorFlow Graph
name	the name for this Optimizer (defaults to 'Adagrad')
learningRate	the learning rate
initialAccumulatorValue	Starting value for the accumulators, must be non-negative.

Throws

IllegalArgumentException	if initialAccumulatorValue is negative

Public Methods

public String getOptimizerName ()

Get the Name of the optimizer.

Returns

• The optimizer name.

public String toString ()