org.encog.neural.networks.training.concurrent.jobs
Class TrainingJob

java.lang.Object
  org.encog.neural.networks.training.concurrent.jobs.TrainingJob

Direct Known Subclasses:

BPROPJob, RPROPJob

public abstract class TrainingJob
extends Object

Base class for all concurrent training jobs.

Constructor Summary

TrainingJob(BasicNetwork network, NeuralDataSet training, boolean loadToMemory)
Construct a training job.

Method Summary

abstract void	createTrainer(OpenCLTrainingProfile profile, boolean singleThreaded) Create a trainer to use.
Throwable	getError()
int	getGlobalRatio()
int	getIterationsPer()
double	getLocalRatio()
BasicNetwork	getNetwork()
double	getSegmentationRatio()
List<Strategy>	getStrategies()
Train	getTrain()
NeuralDataSet	getTraining()
boolean	isLoadToMemory()
void	setError(Throwable error)
void	setGlobalRatio(int globalRatio)
void	setIterationsPer(int iterationsPer)
void	setLoadToMemory(boolean loadToMemory)
void	setLocalRatio(double localRatio)
void	setNetwork(BasicNetwork network)
void	setSegmentationRatio(double segmentationRatio)
void	setTrain(Train train)
void	setTraining(NeuralDataSet training)
boolean	shouldContinue()

Methods inherited from class java.lang.Object

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

Constructor Detail

TrainingJob

public TrainingJob(BasicNetwork network,
                   NeuralDataSet training,
                   boolean loadToMemory)

Construct a training job.

Parameters:

network - The network to train.

training - The training data to use.

loadToMemory - True, if binary data should be loaded to memory.

Method Detail

createTrainer

public abstract void createTrainer(OpenCLTrainingProfile profile,
                                   boolean singleThreaded)

Create a trainer to use.

Parameters:

profile - The OpenCL training profile to use.

getError

public Throwable getError()

Returns:

the error

getNetwork

public BasicNetwork getNetwork()

Returns:

the network

getStrategies

public List<Strategy> getStrategies()

Returns:

the strategies

getTrain

public Train getTrain()

Returns:

the train

getTraining

public NeuralDataSet getTraining()

Returns:

the training

isLoadToMemory

public boolean isLoadToMemory()

Returns:

the loadToMemory

setError

public void setError(Throwable error)

Parameters:

error - the error to set

setLoadToMemory

public void setLoadToMemory(boolean loadToMemory)

Parameters:

loadToMemory - the loadToMemory to set

setNetwork

public void setNetwork(BasicNetwork network)

Parameters:

network - the network to set

setTrain

public void setTrain(Train train)

Parameters:

train - the train to set

setTraining

public void setTraining(NeuralDataSet training)

Parameters:

training - the training to set

shouldContinue

public boolean shouldContinue()

Returns:

True, if training should continue.

getIterationsPer

public int getIterationsPer()

Returns:

the iterationsPer

setIterationsPer

public void setIterationsPer(int iterationsPer)

Parameters:

iterationsPer - the iterationsPer to set

getLocalRatio

public double getLocalRatio()

setLocalRatio

public void setLocalRatio(double localRatio)

getGlobalRatio

public int getGlobalRatio()

setGlobalRatio

public void setGlobalRatio(int globalRatio)

getSegmentationRatio

public double getSegmentationRatio()

setSegmentationRatio

public void setSegmentationRatio(double segmentationRatio)