public class AutoEncoder extends BasePretrainNetwork<AutoEncoder>
Layer.TrainingMode, Layer.Typegradient, gradientsFlattened, gradientViews, optimizer, params, paramsFlattened, score, solver, weightNoiseParamscacheMode, conf, dataType, dropoutApplied, epochCount, index, input, inputModificationAllowed, iterationCount, maskArray, maskState, preOutput, trainingListeners| Constructor and Description |
|---|
AutoEncoder(NeuralNetConfiguration conf,
DataType dataType) |
| Modifier and Type | Method and Description |
|---|---|
INDArray |
activate(boolean training,
LayerWorkspaceMgr workspaceMgr)
Perform forward pass and return the activations array with the last set input
|
INDArray |
activate(INDArray input,
boolean training,
LayerWorkspaceMgr workspaceMgr)
Perform forward pass and return the activations array with the specified input
|
void |
computeGradientAndScore(LayerWorkspaceMgr workspaceMgr)
Update the score
|
INDArray |
decode(INDArray y,
LayerWorkspaceMgr workspaceMgr) |
INDArray |
encode(INDArray v,
boolean training,
LayerWorkspaceMgr workspaceMgr) |
boolean |
isPretrainLayer()
Returns true if the layer can be trained in an unsupervised/pretrain manner (AE, VAE, etc)
|
Pair<INDArray,INDArray> |
sampleHiddenGivenVisible(INDArray v)
Sample the hidden distribution given the visible
|
Pair<INDArray,INDArray> |
sampleVisibleGivenHidden(INDArray h)
Sample the visible distribution given the hidden
|
backpropGradient, calcRegularizationScore, createGradient, getCorruptedInput, numParams, numParams, params, paramTable, setParams, setScoreWithZclear, clearNoiseWeightParams, clone, fit, fit, getGradientsViewArray, getOptimizer, getParam, getParamWithNoise, gradient, hasBias, hasLayerNorm, layerConf, paramTable, preOutput, preOutputWithPreNorm, score, setBackpropGradientsViewArray, setParam, setParams, setParamsViewArray, setParamTable, toString, update, updateaddListeners, allowInputModification, applyConstraints, applyDropOutIfNecessary, applyMask, assertInputSet, backpropDropOutIfPresent, batchSize, close, conf, feedForwardMaskArray, getConfig, getEpochCount, getHelper, getIndex, getInput, getInputMiniBatchSize, getListeners, getMaskArray, gradientAndScore, init, input, layerId, setCacheMode, setConf, setEpochCount, setIndex, setInput, setInputMiniBatchSize, setListeners, setListeners, setMaskArray, type, updaterDivideByMinibatchequals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitgetIterationCount, setIterationCountpublic AutoEncoder(NeuralNetConfiguration conf, DataType dataType)
public Pair<INDArray,INDArray> sampleHiddenGivenVisible(INDArray v)
BasePretrainNetworksampleHiddenGivenVisible in class BasePretrainNetwork<AutoEncoder>v - the visible to sample frompublic Pair<INDArray,INDArray> sampleVisibleGivenHidden(INDArray h)
BasePretrainNetworksampleVisibleGivenHidden in class BasePretrainNetwork<AutoEncoder>h - the hidden to sample frompublic INDArray encode(INDArray v, boolean training, LayerWorkspaceMgr workspaceMgr)
public INDArray decode(INDArray y, LayerWorkspaceMgr workspaceMgr)
public INDArray activate(INDArray input, boolean training, LayerWorkspaceMgr workspaceMgr)
Layeractivate in interface Layeractivate in class AbstractLayer<AutoEncoder>input - the input to usetraining - train or test modeworkspaceMgr - Workspace manager.ArrayType.ACTIVATIONS workspace via the workspace managerpublic boolean isPretrainLayer()
Layerpublic INDArray activate(boolean training, LayerWorkspaceMgr workspaceMgr)
Layeractivate in interface Layeractivate in class BaseLayer<AutoEncoder>training - training or test modeworkspaceMgr - Workspace managerArrayType.ACTIVATIONS workspace via the workspace managerpublic void computeGradientAndScore(LayerWorkspaceMgr workspaceMgr)
ModelcomputeGradientAndScore in interface ModelcomputeGradientAndScore in class BaseLayer<AutoEncoder>Copyright © 2020. All rights reserved.