org.deeplearning4j.nn.conf

Class NeuralNetConfiguration.Builder

java.lang.Object

org.deeplearning4j.nn.conf.NeuralNetConfiguration.Builder

All Implemented Interfaces:

Cloneable

Enclosing class:

NeuralNetConfiguration

public static class NeuralNetConfiguration.Builder
extends Object
implements Cloneable

Constructor Summary

Constructors

Constructor and Description
Builder()

Method Summary

Modifier and Type	Method and Description
NeuralNetConfiguration.Builder	batchSize(int batchSize)
NeuralNetConfiguration	build() Return a configuration based on this builder
NeuralNetConfiguration.Builder	clone()
NeuralNetConfiguration.Builder	constrainGradientToUnitNorm(boolean constrainGradientToUnitNorm)
NeuralNetConfiguration.Builder	iterations(int numIterations)
NeuralNetConfiguration.Builder	l1(double l1)
NeuralNetConfiguration.Builder	l2(double l2)
NeuralNetConfiguration.Builder	layer(Layer layer)
NeuralNetConfiguration.Builder	learningRate(double lr)
NeuralNetConfiguration.ListBuilder	list(int size)
NeuralNetConfiguration.Builder	maxNumLineSearchIterations(int maxNumLineSearchIterations)
NeuralNetConfiguration.Builder	miniBatch(boolean miniBatch)
NeuralNetConfiguration.Builder	minimize(boolean minimize)
NeuralNetConfiguration.Builder	momentum(double momentum)
NeuralNetConfiguration.Builder	momentumAfter(Map<Integer,Double> momentumAfter)
NeuralNetConfiguration.Builder	optimizationAlgo(OptimizationAlgorithm optimizationAlgo)
NeuralNetConfiguration.Builder	regularization(boolean useRegularization)
NeuralNetConfiguration.Builder	rho(double rho) Ada delta coefficient
NeuralNetConfiguration.Builder	rmsDecay(double rmsDecay)
NeuralNetConfiguration.Builder	seed(int seed)
NeuralNetConfiguration.Builder	seed(long seed)
NeuralNetConfiguration.Builder	stepFunction(StepFunction stepFunction)
NeuralNetConfiguration.Builder	timeSeriesLength(int timeSeriesLength) + * Time series length + * @param timeSeriesLength + * @return +
NeuralNetConfiguration.Builder	useDropConnect(boolean useDropConnect) Use drop connect: multiply the coefficients by a binomial sampling wrt the dropout probability

Methods inherited from class java.lang.Object

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

Constructor Detail

Builder

public Builder()

Method Detail

timeSeriesLength

public NeuralNetConfiguration.Builder timeSeriesLength(int timeSeriesLength)

+ * Time series length + * @param timeSeriesLength + * @return +

rho

public NeuralNetConfiguration.Builder rho(double rho)

Ada delta coefficient

Parameters:

rho -

Returns:

miniBatch

public NeuralNetConfiguration.Builder miniBatch(boolean miniBatch)

useDropConnect

public NeuralNetConfiguration.Builder useDropConnect(boolean useDropConnect)

Use drop connect: multiply the coefficients by a binomial sampling wrt the dropout probability

Parameters:

useDropConnect - whether to use drop connect or not

Returns:

the

l1

public NeuralNetConfiguration.Builder l1(double l1)

rmsDecay

public NeuralNetConfiguration.Builder rmsDecay(double rmsDecay)

minimize

public NeuralNetConfiguration.Builder minimize(boolean minimize)

maxNumLineSearchIterations

public NeuralNetConfiguration.Builder maxNumLineSearchIterations(int maxNumLineSearchIterations)

batchSize

public NeuralNetConfiguration.Builder batchSize(int batchSize)

layer

public NeuralNetConfiguration.Builder layer(Layer layer)

stepFunction

public NeuralNetConfiguration.Builder stepFunction(StepFunction stepFunction)

list

public NeuralNetConfiguration.ListBuilder list(int size)

clone

public NeuralNetConfiguration.Builder clone()

Overrides:

clone in class Object

iterations

public NeuralNetConfiguration.Builder iterations(int numIterations)

learningRate

public NeuralNetConfiguration.Builder learningRate(double lr)

momentum

public NeuralNetConfiguration.Builder momentum(double momentum)

momentumAfter

public NeuralNetConfiguration.Builder momentumAfter(Map<Integer,Double> momentumAfter)

seed

public NeuralNetConfiguration.Builder seed(int seed)

seed

public NeuralNetConfiguration.Builder seed(long seed)

l2

public NeuralNetConfiguration.Builder l2(double l2)

regularization

public NeuralNetConfiguration.Builder regularization(boolean useRegularization)

optimizationAlgo

public NeuralNetConfiguration.Builder optimizationAlgo(OptimizationAlgorithm optimizationAlgo)

constrainGradientToUnitNorm

public NeuralNetConfiguration.Builder constrainGradientToUnitNorm(boolean constrainGradientToUnitNorm)

build

public NeuralNetConfiguration build()

Return a configuration based on this builder

Returns: