Package org.deeplearning4j.nn.conf.layers

Class BaseOutputLayer.Builder<T extends BaseOutputLayer.Builder<T>>

java.lang.Object

org.deeplearning4j.nn.conf.layers.Layer.Builder<T>

org.deeplearning4j.nn.conf.layers.BaseLayer.Builder<T>

org.deeplearning4j.nn.conf.layers.FeedForwardLayer.Builder<T>

org.deeplearning4j.nn.conf.layers.BaseOutputLayer.Builder<T>

Direct Known Subclasses:

CenterLossOutputLayer.Builder, Cnn3DLossLayer.Builder, CnnLossLayer.Builder, LossLayer.Builder, OCNNOutputLayer.Builder, OutputLayer.Builder, RnnLossLayer.Builder, RnnOutputLayer.Builder

Enclosing class:

BaseOutputLayer

public abstract static class BaseOutputLayer.Builder<T extends BaseOutputLayer.Builder<T>>
extends FeedForwardLayer.Builder<T>

Field Summary

Fields

Modifier and Type	Field	Description
protected ILossFunction	lossFn	Loss function for the output layer

Fields inherited from class org.deeplearning4j.nn.conf.layers.FeedForwardLayer.Builder

nIn, nOut

Fields inherited from class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder

activationFn, biasInit, biasUpdater, gainInit, gradientNormalization, gradientNormalizationThreshold, iupdater, regularization, regularizationBias, weightInitFn, weightNoise

Fields inherited from class org.deeplearning4j.nn.conf.layers.Layer.Builder

allParamConstraints, biasConstraints, iDropout, layerName, weightConstraints

Constructor Summary

Constructors

Constructor	Description
Builder()
Builder(ILossFunction lossFunction)
Builder(LossFunctions.LossFunction lossFunction)

Method Summary

Modifier and Type	Method	Description
T	hasBias(boolean hasBias)	If true (default): include bias parameters in the model.
T	lossFunction(ILossFunction lossFunction)
T	lossFunction(LossFunctions.LossFunction lossFunction)

Methods inherited from class org.deeplearning4j.nn.conf.layers.FeedForwardLayer.Builder

nIn, nIn, nOut, nOut, units

Methods inherited from class org.deeplearning4j.nn.conf.layers.BaseLayer.Builder

activation, activation, biasInit, biasUpdater, dist, gainInit, gradientNormalization, gradientNormalizationThreshold, l1, l1Bias, l2, l2Bias, regularization, regularizationBias, updater, updater, weightDecay, weightDecay, weightDecayBias, weightDecayBias, weightInit, weightInit, weightInit, weightNoise

Methods inherited from class org.deeplearning4j.nn.conf.layers.Layer.Builder

build, constrainAllParameters, constrainBias, constrainWeights, dropOut, dropOut, name

Methods inherited from class java.lang.Object

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

Field Detail

lossFn

protected ILossFunction lossFn

Loss function for the output layer

Constructor Detail

Builder

public Builder()

Builder

public Builder(LossFunctions.LossFunction lossFunction)

Parameters:

lossFunction - Loss function for the output layer

Builder

public Builder(ILossFunction lossFunction)

Parameters:

lossFunction - Loss function for the output layer

Method Detail

lossFunction

public T lossFunction(LossFunctions.LossFunction lossFunction)

Parameters:

lossFunction - Loss function for the output layer

hasBias

public T hasBias(boolean hasBias)

If true (default): include bias parameters in the model. False: no bias.

Parameters:

hasBias - If true: include bias parameters in this model

lossFunction

public T lossFunction(ILossFunction lossFunction)

Parameters:

lossFunction - Loss function for the output layer