org.deeplearning4j.nn.layers.feedforward.autoencoder

Class AutoEncoder

java.lang.Object

org.deeplearning4j.nn.layers.BaseLayer<LayerConfT>

org.deeplearning4j.nn.layers.BasePretrainNetwork<AutoEncoder>

org.deeplearning4j.nn.layers.feedforward.autoencoder.AutoEncoder

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, Layer, Model

public class AutoEncoder
extends BasePretrainNetwork<AutoEncoder>

Autoencoder. Add Gaussian noise to input and learn a reconstruction function.

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from interface org.deeplearning4j.nn.api.Layer

Layer.TrainingMode, Layer.Type

Field Summary

Fields inherited from class org.deeplearning4j.nn.layers.BasePretrainNetwork

trainingListeners

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

conf, dropoutApplied, dropoutMask, gradient, gradientsFlattened, gradientViews, index, input, iterationListeners, maskArray, maskState, optimizer, params, paramsFlattened, score, solver

Constructor Summary

Constructors

Constructor and Description
AutoEncoder(NeuralNetConfiguration conf)
AutoEncoder(NeuralNetConfiguration conf, org.nd4j.linalg.api.ndarray.INDArray input)

Method Summary

Modifier and Type	Method and Description
org.nd4j.linalg.api.ndarray.INDArray	activate() Trigger an activation with the last specified input
org.nd4j.linalg.api.ndarray.INDArray	activate(boolean training) Trigger an activation with the last specified input
org.nd4j.linalg.api.ndarray.INDArray	activate(org.nd4j.linalg.api.ndarray.INDArray input) Initialize the layer with the given input and return the activation for this layer given this input
org.nd4j.linalg.api.ndarray.INDArray	activate(org.nd4j.linalg.api.ndarray.INDArray input, boolean training) Initialize the layer with the given input and return the activation for this layer given this input
void	computeGradientAndScore() Update the score
org.nd4j.linalg.api.ndarray.INDArray	decode(org.nd4j.linalg.api.ndarray.INDArray y)
org.nd4j.linalg.api.ndarray.INDArray	encode(org.nd4j.linalg.api.ndarray.INDArray v, boolean training)
boolean	isPretrainLayer() Returns true if the layer can be trained in an unsupervised/pretrain manner (VAE, RBMs etc)
Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>	sampleHiddenGivenVisible(org.nd4j.linalg.api.ndarray.INDArray v) Sample the hidden distribution given the visible
Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray>	sampleVisibleGivenHidden(org.nd4j.linalg.api.ndarray.INDArray h) Sample the visible distribution given the hidden

Methods inherited from class org.deeplearning4j.nn.layers.BasePretrainNetwork

backpropGradient, calcL1, calcL2, createGradient, getCorruptedInput, numParams, numParams, params, paramTable, setListeners, setListeners, setParams, setScoreWithZ

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

accumulateScore, activate, activate, activationMean, applyDropOutIfNecessary, applyLearningRateScoreDecay, applyMask, batchSize, calcGradient, clear, clone, conf, createGradient, derivativeActivation, error, feedForwardMaskArray, fit, fit, getIndex, getInput, getInputMiniBatchSize, getListeners, getMaskArray, getOptimizer, getParam, gradient, gradientAndScore, init, initParams, input, iterate, layerConf, layerNameAndIndex, merge, paramTable, preOutput, preOutput, preOutput, preOutput, score, setBackpropGradientsViewArray, setConf, setIndex, setInput, setInputMiniBatchSize, setMaskArray, setParam, setParams, setParamsViewArray, setParamTable, toString, transpose, type, update, update, validateInput

Methods inherited from class java.lang.Object

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

Constructor Detail

AutoEncoder

public AutoEncoder(NeuralNetConfiguration conf)

AutoEncoder

public AutoEncoder(NeuralNetConfiguration conf,
                   org.nd4j.linalg.api.ndarray.INDArray input)

Method Detail

sampleHiddenGivenVisible

public Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray> sampleHiddenGivenVisible(org.nd4j.linalg.api.ndarray.INDArray v)

Description copied from class: BasePretrainNetwork

Sample the hidden distribution given the visible

Specified by:

sampleHiddenGivenVisible in class BasePretrainNetwork<AutoEncoder>

Parameters:

v - the visible to sample from

Returns:

the hidden mean and sample

sampleVisibleGivenHidden

public Pair<org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray> sampleVisibleGivenHidden(org.nd4j.linalg.api.ndarray.INDArray h)

Description copied from class: BasePretrainNetwork

Sample the visible distribution given the hidden

Specified by:

sampleVisibleGivenHidden in class BasePretrainNetwork<AutoEncoder>

Parameters:

h - the hidden to sample from

Returns:

the mean and sample

encode

public org.nd4j.linalg.api.ndarray.INDArray encode(org.nd4j.linalg.api.ndarray.INDArray v,
                                                   boolean training)

decode

public org.nd4j.linalg.api.ndarray.INDArray decode(org.nd4j.linalg.api.ndarray.INDArray y)

activate

public org.nd4j.linalg.api.ndarray.INDArray activate(org.nd4j.linalg.api.ndarray.INDArray input,
                                                     boolean training)

Description copied from interface: Layer

Initialize the layer with the given input and return the activation for this layer given this input

Specified by:

activate in interface Layer

Overrides:

activate in class BaseLayer<AutoEncoder>

Parameters:

input - the input to use

training - train or test mode

Returns:

activate

public org.nd4j.linalg.api.ndarray.INDArray activate(org.nd4j.linalg.api.ndarray.INDArray input)

Description copied from interface: Layer

Initialize the layer with the given input and return the activation for this layer given this input

Specified by:

activate in interface Layer

Overrides:

activate in class BaseLayer<AutoEncoder>

Parameters:

input - the input to use

Returns:

isPretrainLayer

public boolean isPretrainLayer()

Description copied from interface: Layer

Returns true if the layer can be trained in an unsupervised/pretrain manner (VAE, RBMs etc)

Returns:

true if the layer can be pretrained (using fit(INDArray), false otherwise

activate

public org.nd4j.linalg.api.ndarray.INDArray activate(boolean training)

Description copied from interface: Layer

Trigger an activation with the last specified input

Specified by:

activate in interface Layer

Overrides:

activate in class BaseLayer<AutoEncoder>

Parameters:

training - training or test mode

Returns:

the activation of the last specified input

activate

public org.nd4j.linalg.api.ndarray.INDArray activate()

Description copied from interface: Layer

Trigger an activation with the last specified input

Specified by:

activate in interface Layer

Overrides:

activate in class BaseLayer<AutoEncoder>

Returns:

the activation of the last specified input

computeGradientAndScore

public void computeGradientAndScore()

Description copied from interface: Model

Update the score

Specified by:

computeGradientAndScore in interface Model

Overrides:

computeGradientAndScore in class BaseLayer<AutoEncoder>