org.deeplearning4j.nn.layers

Class BasePretrainNetwork<LayerConfT extends BasePretrainNetwork>

java.lang.Object

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

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

All Implemented Interfaces:

Serializable, Cloneable, Layer, Model

Direct Known Subclasses:

AutoEncoder, RBM

public abstract class BasePretrainNetwork<LayerConfT extends BasePretrainNetwork>
extends BaseLayer<LayerConfT>

Baseline class for any Neural Network used as a layer in a deep network *

Author:

Adam Gibson

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.BaseLayer

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

Constructor Summary

Constructors

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

Method Summary

Modifier and Type	Method and Description
protected Gradient	createGradient(org.nd4j.linalg.api.ndarray.INDArray wGradient, org.nd4j.linalg.api.ndarray.INDArray vBiasGradient, org.nd4j.linalg.api.ndarray.INDArray hBiasGradient)
org.nd4j.linalg.api.ndarray.INDArray	getCorruptedInput(org.nd4j.linalg.api.ndarray.INDArray x, double corruptionLevel) Corrupts the given input by doing a binomial sampling given the corruption level
int	numParams() The number of parameters for the model, for backprop (i.e., excluding visible bias)
int	numParams(boolean backwards) the number of parameters for the model
org.nd4j.linalg.api.ndarray.INDArray	params() Returns the parameters of the neural network as a flattened row vector
org.nd4j.linalg.api.ndarray.INDArray	params(boolean backprop)
abstract 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
abstract 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
void	setParams(org.nd4j.linalg.api.ndarray.INDArray params) Set the parameters for this model.
protected void	setScoreWithZ(org.nd4j.linalg.api.ndarray.INDArray z)

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

accumulateScore, activate, activate, activate, activate, activate, activate, activationMean, applyDropOutIfNecessary, applyLearningRateScoreDecay, backpropGradient, batchSize, calcGradient, calcL1, calcL2, clear, clone, computeGradientAndScore, conf, createGradient, derivativeActivation, error, fit, fit, getIndex, getInput, getInputMiniBatchSize, getListeners, getMaskArray, getOptimizer, getParam, gradient, gradientAndScore, initParams, input, iterate, layerConf, merge, paramTable, preOutput, preOutput, preOutput, preOutput, score, setBackpropGradientsViewArray, setConf, setIndex, setInput, setInputMiniBatchSize, setListeners, setListeners, 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

BasePretrainNetwork

public BasePretrainNetwork(NeuralNetConfiguration conf)

BasePretrainNetwork

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

Method Detail

getCorruptedInput

public org.nd4j.linalg.api.ndarray.INDArray getCorruptedInput(org.nd4j.linalg.api.ndarray.INDArray x,
                                                              double corruptionLevel)

Corrupts the given input by doing a binomial sampling given the corruption level

Parameters:

x - the input to corrupt

corruptionLevel - the corruption value

Returns:

the binomial sampled corrupted input

createGradient

protected Gradient createGradient(org.nd4j.linalg.api.ndarray.INDArray wGradient,
                                  org.nd4j.linalg.api.ndarray.INDArray vBiasGradient,
                                  org.nd4j.linalg.api.ndarray.INDArray hBiasGradient)

numParams

public int numParams(boolean backwards)

Description copied from interface: Model

the number of parameters for the model

Specified by:

numParams in interface Model

Overrides:

numParams in class BaseLayer<LayerConfT extends BasePretrainNetwork>

Returns:

the number of parameters for the model

sampleHiddenGivenVisible

public abstract 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

Parameters:

v - the visible to sample from

Returns:

the hidden mean and sample

sampleVisibleGivenHidden

public abstract 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

Parameters:

h - the hidden to sample from

Returns:

the mean and sample

setScoreWithZ

protected void setScoreWithZ(org.nd4j.linalg.api.ndarray.INDArray z)

Overrides:

setScoreWithZ in class BaseLayer<LayerConfT extends BasePretrainNetwork>

params

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

Description copied from class: BaseLayer

Returns the parameters of the neural network as a flattened row vector

Specified by:

params in interface Model

Overrides:

params in class BaseLayer<LayerConfT extends BasePretrainNetwork>

Returns:

the parameters of the neural network

params

public org.nd4j.linalg.api.ndarray.INDArray params(boolean backprop)

numParams

public int numParams()

The number of parameters for the model, for backprop (i.e., excluding visible bias)

Specified by:

numParams in interface Model

Overrides:

numParams in class BaseLayer<LayerConfT extends BasePretrainNetwork>

Returns:

the number of parameters for the model (ex. visible bias)

setParams

public void setParams(org.nd4j.linalg.api.ndarray.INDArray params)

Description copied from interface: Model

Set the parameters for this model. This expects a linear ndarray which then be unpacked internally relative to the expected ordering of the model

Specified by:

setParams in interface Model

Overrides:

setParams in class BaseLayer<LayerConfT extends BasePretrainNetwork>

Parameters:

params - the parameters for the model