org.deeplearning4j.optimize

Class VectorizedDeepLearningGradientAscent

java.lang.Object

org.deeplearning4j.optimize.VectorizedDeepLearningGradientAscent

All Implemented Interfaces:

OptimizerMatrix

public class VectorizedDeepLearningGradientAscent
extends Object
implements OptimizerMatrix

Vectorized Stochastic Gradient Ascent

Author:

Adam Gibson

Constructor Summary

Constructors

Constructor and Description
VectorizedDeepLearningGradientAscent(OptimizableByGradientValueMatrix function)
VectorizedDeepLearningGradientAscent(OptimizableByGradientValueMatrix function, double initialStepSize)
VectorizedDeepLearningGradientAscent(OptimizableByGradientValueMatrix function, double initialStepSize, NeuralNetEpochListener listener)
VectorizedDeepLearningGradientAscent(OptimizableByGradientValueMatrix function, NeuralNetEpochListener listener)

Method Summary

Methods

Modifier and Type	Method and Description
double	getInitialStepSize()
VectorizedBackTrackLineSearch	getLineMaximizer()
OptimizableByGradientValueMatrix	getOptimizable()
double	getStpmax()
boolean	isConverged()
boolean	optimize()
boolean	optimize(int numIterations)
void	setInitialStepSize(double initialStepSize)
void	setMaxStepSize(double v)
void	setStpmax(double stpmax)
void	setTolerance(double tolerance) Sets the tolerance in the convergence test: 2.0*|value-old_value| <= tolerance*(|value|+|old_value|+eps) Default value is 0.001.

Methods inherited from class java.lang.Object

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

Constructor Detail

VectorizedDeepLearningGradientAscent

public VectorizedDeepLearningGradientAscent(OptimizableByGradientValueMatrix function,
                                    double initialStepSize)

VectorizedDeepLearningGradientAscent

public VectorizedDeepLearningGradientAscent(OptimizableByGradientValueMatrix function,
                                    NeuralNetEpochListener listener)

VectorizedDeepLearningGradientAscent

public VectorizedDeepLearningGradientAscent(OptimizableByGradientValueMatrix function,
                                    double initialStepSize,
                                    NeuralNetEpochListener listener)

VectorizedDeepLearningGradientAscent

public VectorizedDeepLearningGradientAscent(OptimizableByGradientValueMatrix function)

Method Detail

getOptimizable

public OptimizableByGradientValueMatrix getOptimizable()

isConverged

public boolean isConverged()

Specified by:

isConverged in interface OptimizerMatrix

getLineMaximizer

public VectorizedBackTrackLineSearch getLineMaximizer()

setTolerance

public void setTolerance(double tolerance)

Sets the tolerance in the convergence test: 2.0*|value-old_value| <= tolerance*(|value|+|old_value|+eps) Default value is 0.001.

Parameters:

tolerance - tolerance for convergence test

getInitialStepSize

public double getInitialStepSize()

setInitialStepSize

public void setInitialStepSize(double initialStepSize)

getStpmax

public double getStpmax()

setStpmax

public void setStpmax(double stpmax)

optimize

public boolean optimize()

Specified by:

optimize in interface OptimizerMatrix

optimize

public boolean optimize(int numIterations)

Specified by:

optimize in interface OptimizerMatrix

setMaxStepSize

public void setMaxStepSize(double v)