org.deeplearning4j.nn.conf.layers

Class BaseLayer

java.lang.Object

org.deeplearning4j.nn.conf.layers.Layer

org.deeplearning4j.nn.conf.layers.BaseLayer

All Implemented Interfaces:

Serializable, Cloneable, TrainingConfig

Direct Known Subclasses:

FeedForwardLayer

public abstract class BaseLayer
extends Layer
implements Serializable, Cloneable

A neural network layer.

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	BaseLayer.Builder<T extends BaseLayer.Builder<T>>

Field Summary

Fields

Modifier and Type	Field and Description
protected IActivation	activationFn
protected double	biasInit
protected IUpdater	biasUpdater
protected Distribution	dist
protected GradientNormalization	gradientNormalization
protected double	gradientNormalizationThreshold
protected IUpdater	iUpdater
protected double	l1
protected double	l1Bias
protected double	l2
protected double	l2Bias
protected WeightInit	weightInit
protected IWeightNoise	weightNoise

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

constraints, iDropout, layerName

Constructor Summary

Constructors

Constructor and Description
BaseLayer(BaseLayer.Builder builder)

Method Summary

Modifier and Type	Method and Description
BaseLayer	clone()
GradientNormalization	getGradientNormalization()
IUpdater	getUpdaterByParam(String paramName) Get the updater for the given parameter.
void	resetLayerDefaultConfig() Reset the learning related configs of the layer to default.

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

getL1ByParam, getL2ByParam, getMemoryReport, getOutputType, getPreProcessorForInputType, initializeConstraints, initializer, instantiate, isPretrainParam, setNIn, setPretrain

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.deeplearning4j.nn.api.TrainingConfig

getGradientNormalizationThreshold, getLayerName, isPretrain

Field Detail

activationFn

protected IActivation activationFn

weightInit

protected WeightInit weightInit

biasInit

protected double biasInit

dist

protected Distribution dist

l1

protected double l1

l2

protected double l2

l1Bias

protected double l1Bias

l2Bias

protected double l2Bias

iUpdater

protected IUpdater iUpdater

biasUpdater

protected IUpdater biasUpdater

weightNoise

protected IWeightNoise weightNoise

gradientNormalization

protected GradientNormalization gradientNormalization

gradientNormalizationThreshold

protected double gradientNormalizationThreshold

Constructor Detail

BaseLayer

public BaseLayer(BaseLayer.Builder builder)

Method Detail

resetLayerDefaultConfig

public void resetLayerDefaultConfig()

Reset the learning related configs of the layer to default. When instantiated with a global neural network configuration the parameters specified in the neural network configuration will be used. For internal use with the transfer learning API. Users should not have to call this method directly.

Overrides:

resetLayerDefaultConfig in class Layer

clone

public BaseLayer clone()

Overrides:

clone in class Layer

getUpdaterByParam

public IUpdater getUpdaterByParam(String paramName)

Get the updater for the given parameter. Typically the same updater will be used for all updaters, but this is not necessarily the case

Specified by:

getUpdaterByParam in interface TrainingConfig

Overrides:

getUpdaterByParam in class Layer

Parameters:

paramName - Parameter name

Returns:

IUpdater for the parameter

getGradientNormalization

public GradientNormalization getGradientNormalization()

Specified by:

getGradientNormalization in interface TrainingConfig

Returns:

The gradient normalization configuration