org.deeplearning4j.earlystopping.scorecalc

Class DataSetLossCalculator

java.lang.Object

org.deeplearning4j.earlystopping.scorecalc.base.BaseScoreCalculator<Model>

org.deeplearning4j.earlystopping.scorecalc.DataSetLossCalculator

All Implemented Interfaces:

Serializable, ScoreCalculator<Model>

public class DataSetLossCalculator
extends BaseScoreCalculator<Model>

Given a DataSetIterator: calculate the total loss for the model on that data set. Can be used for both MultiLayerNetwork and ComputationGraph

Author:

Alex Black

See Also:

Serialized Form

Field Summary

Fields inherited from class org.deeplearning4j.earlystopping.scorecalc.base.BaseScoreCalculator

exampleCount, iterator, mdsIterator, minibatchCount, scoreSum

Constructor Summary

Constructors

Constructor and Description
DataSetLossCalculator(DataSetIterator dataSetIterator, boolean average) Calculate the score (loss function value) on a given data set (usually a test set)
DataSetLossCalculator(MultiDataSetIterator dataSetIterator, boolean average) Calculate the score (loss function value) on a given data set (usually a test set)

Method Summary

Modifier and Type	Method and Description
protected double	finalScore(double scoreSum, int minibatchCount, int exampleCount)
boolean	minimizeScore()
protected INDArray[]	output(Model network, INDArray[] input, INDArray[] fMask, INDArray[] lMask)
protected INDArray	output(Model network, INDArray input, INDArray fMask, INDArray lMask)
protected void	reset()
protected double	scoreMinibatch(Model network, INDArray[] features, INDArray[] labels, INDArray[] fMask, INDArray[] lMask, INDArray[] output)
String	toString()

Methods inherited from class org.deeplearning4j.earlystopping.scorecalc.base.BaseScoreCalculator

arr, calculateScore, get0, scoreMinibatch

Methods inherited from class java.lang.Object

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

Constructor Detail

DataSetLossCalculator

public DataSetLossCalculator(DataSetIterator dataSetIterator,
                             boolean average)

Calculate the score (loss function value) on a given data set (usually a test set)

Parameters:

dataSetIterator - Data set to calculate the score for

average - Whether to return the average (sum of loss / N) or just (sum of loss)

DataSetLossCalculator

public DataSetLossCalculator(MultiDataSetIterator dataSetIterator,
                             boolean average)

Calculate the score (loss function value) on a given data set (usually a test set)

Parameters:

dataSetIterator - Data set to calculate the score for

average - Whether to return the average (sum of loss / N) or just (sum of loss)

Method Detail

toString

public String toString()

Overrides:

toString in class Object

reset

protected void reset()

Specified by:

reset in class BaseScoreCalculator<Model>

output

protected INDArray output(Model network,
                          INDArray input,
                          INDArray fMask,
                          INDArray lMask)

Specified by:

output in class BaseScoreCalculator<Model>

output

protected INDArray[] output(Model network,
                            INDArray[] input,
                            INDArray[] fMask,
                            INDArray[] lMask)

Specified by:

output in class BaseScoreCalculator<Model>

scoreMinibatch

protected double scoreMinibatch(Model network,
                                INDArray[] features,
                                INDArray[] labels,
                                INDArray[] fMask,
                                INDArray[] lMask,
                                INDArray[] output)

Specified by:

scoreMinibatch in class BaseScoreCalculator<Model>

finalScore

protected double finalScore(double scoreSum,
                            int minibatchCount,
                            int exampleCount)

Specified by:

finalScore in class BaseScoreCalculator<Model>

minimizeScore

public boolean minimizeScore()

Returns:

If true: the score should be minimized. If false: the score should be maximized.