org.deeplearning4j.optimize.solvers

Class IterationGradientDescent

java.lang.Object

org.deeplearning4j.optimize.solvers.BaseOptimizer

org.deeplearning4j.optimize.solvers.IterationGradientDescent

All Implemented Interfaces:

Serializable, ConvexOptimizer

public class IterationGradientDescent
extends BaseOptimizer

No line search gradient descent

Author:

Adam Gibson

See Also:

Serialized Form

Field Summary

Fields inherited from class org.deeplearning4j.optimize.solvers.BaseOptimizer

adaGrad, adaGradForVariable, conf, GRADIENT_KEY, iteration, iterationListeners, lineMaximizer, log, model, oldScore, PARAMS_KEY, score, SCORE_KEY, searchState, step, stepFunction, stpMax, terminationConditions

Constructor Summary

Constructors

Constructor and Description
IterationGradientDescent(NeuralNetConfiguration conf, StepFunction stepFunction, Collection<IterationListener> iterationListeners, Collection<TerminationCondition> terminationConditions, Model model)
IterationGradientDescent(NeuralNetConfiguration conf, StepFunction stepFunction, Collection<IterationListener> iterationListeners, Model model)

Method Summary

Modifier and Type	Method and Description
boolean	optimize() Optimize call.
void	postStep() Post step (conjugate gradient among other methods needs this)
void	preProcessLine(org.nd4j.linalg.api.ndarray.INDArray line) Pre process the line (scaling and the like)

Methods inherited from class org.deeplearning4j.optimize.solvers.BaseOptimizer

adaGradForVariables, batchSize, getAdaGrad, getAdaGradForVariable, gradientAndScore, postFirstStep, preFirstStepProcess, score, setBatchSize, setupSearchState, updateGradientAccordingToParams, updateGradientAccordingToParams

Methods inherited from class java.lang.Object

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

Constructor Detail

IterationGradientDescent

public IterationGradientDescent(NeuralNetConfiguration conf,
                                StepFunction stepFunction,
                                Collection<IterationListener> iterationListeners,
                                Model model)

IterationGradientDescent

public IterationGradientDescent(NeuralNetConfiguration conf,
                                StepFunction stepFunction,
                                Collection<IterationListener> iterationListeners,
                                Collection<TerminationCondition> terminationConditions,
                                Model model)

Method Detail

optimize

public boolean optimize()

Description copied from class: BaseOptimizer

Optimize call. This runs the optimizer.

Specified by:

optimize in interface ConvexOptimizer

Overrides:

optimize in class BaseOptimizer

Returns:

whether it converged or not

preProcessLine

public void preProcessLine(org.nd4j.linalg.api.ndarray.INDArray line)

Description copied from class: BaseOptimizer

Pre process the line (scaling and the like)

Specified by:

preProcessLine in interface ConvexOptimizer

Overrides:

preProcessLine in class BaseOptimizer

Parameters:

line - the line to pre process

postStep

public void postStep()

Description copied from class: BaseOptimizer

Post step (conjugate gradient among other methods needs this)

Specified by:

postStep in interface ConvexOptimizer

Overrides:

postStep in class BaseOptimizer