public class CustomLayerImpl extends BaseLayer<CustomLayer>
Layer.TrainingMode, Layer.Typeconf, dropoutApplied, dropoutMask, gradient, gradientsFlattened, gradientViews, index, input, iterationListeners, maskArray, maskState, optimizer, params, paramsFlattened, score, solver| Constructor and Description |
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CustomLayerImpl(NeuralNetConfiguration conf) |
| Modifier and Type | Method and Description |
|---|---|
boolean |
isPretrainLayer()
Returns true if the layer can be trained in an unsupervised/pretrain manner (VAE, RBMs etc)
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accumulateScore, activate, activate, activate, activate, activate, activate, activationMean, applyDropOutIfNecessary, applyLearningRateScoreDecay, applyMask, backpropGradient, batchSize, calcGradient, calcL1, calcL2, clear, clone, computeGradientAndScore, conf, createGradient, derivativeActivation, error, feedForwardMaskArray, fit, fit, getIndex, getInput, getInputMiniBatchSize, getListeners, getMaskArray, getOptimizer, getParam, gradient, gradientAndScore, init, initParams, input, iterate, layerConf, layerNameAndIndex, merge, numParams, numParams, params, paramTable, paramTable, preOutput, preOutput, preOutput, preOutput, score, setBackpropGradientsViewArray, setConf, setIndex, setInput, setInputMiniBatchSize, setListeners, setListeners, setMaskArray, setParam, setParams, setParams, setParamsViewArray, setParamTable, setScoreWithZ, toString, transpose, type, update, update, validateInputpublic CustomLayerImpl(NeuralNetConfiguration conf)
public boolean isPretrainLayer()
Layer