org.deeplearning4j.nn.layers.convolution.upsampling

Class Upsampling1D

java.lang.Object

org.deeplearning4j.nn.layers.AbstractLayer<Upsampling2D>

org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D

org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling1D

All Implemented Interfaces:

Serializable, Cloneable, Layer, Model

public class Upsampling1D
extends Upsampling2D

1D Upsampling layer.

Used for upsampling a 1D convolution. Currently derived from 2D version. For forward and backward pass we add a dummy dimension, apply the 2D version and strip the extra dimension again. Eventually, we will want to migrate to a proper 1D version without this overhead.

Author:

Max Pumperla

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.AbstractLayer

cacheMode, conf, dropoutApplied, dropoutMask, epochCount, index, input, iterationCount, iterationListeners, maskArray, maskState, preOutput

Constructor Summary

Constructors

Constructor and Description
Upsampling1D(NeuralNetConfiguration conf)
Upsampling1D(NeuralNetConfiguration conf, org.nd4j.linalg.api.ndarray.INDArray input)

Method Summary

Modifier and Type	Method and Description
org.nd4j.linalg.primitives.Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray>	backpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon) Calculate the gradient relative to the error in the next layer
protected int	getSize()
org.nd4j.linalg.api.ndarray.INDArray	preOutput(boolean training)
org.nd4j.linalg.api.ndarray.INDArray	preOutput(boolean training, boolean forBackprop)

Methods inherited from class org.deeplearning4j.nn.layers.convolution.upsampling.Upsampling2D

accumulateScore, activate, calcL1, calcL2, clearNoiseWeightParams, clone, computeGradientAndScore, fit, fit, getParam, gradient, isPretrainLayer, iterate, numParams, params, score, setParams, transpose, type, update

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

activate, activate, activate, activate, activate, addListeners, applyConstraints, applyDropOutIfNecessary, applyMask, batchSize, clear, conf, feedForwardMaskArray, getGradientsViewArray, getIndex, getInput, getInputMiniBatchSize, getListeners, getMaskArray, getOptimizer, gradientAndScore, init, initParams, input, layerConf, layerId, migrateInput, numParams, paramTable, paramTable, preOutput, preOutput, preOutput, setBackpropGradientsViewArray, setCacheMode, setConf, setIndex, setInput, setInputMiniBatchSize, setListeners, setListeners, setMaskArray, setParam, setParams, setParamsViewArray, setParamTable, update, validateInput

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.Layer

getEpochCount, getIterationCount, setEpochCount, setIterationCount

Constructor Detail

Upsampling1D

public Upsampling1D(NeuralNetConfiguration conf)

Upsampling1D

public Upsampling1D(NeuralNetConfiguration conf,
                    org.nd4j.linalg.api.ndarray.INDArray input)

Method Detail

backpropGradient

public org.nd4j.linalg.primitives.Pair<Gradient,org.nd4j.linalg.api.ndarray.INDArray> backpropGradient(org.nd4j.linalg.api.ndarray.INDArray epsilon)

Description copied from interface: Layer

Calculate the gradient relative to the error in the next layer

Specified by:

backpropGradient in interface Layer

Overrides:

backpropGradient in class Upsampling2D

Parameters:

epsilon - w^(L+1)*delta^(L+1). Or, equiv: dC/da, i.e., (dC/dz)*(dz/da) = dC/da, where C is cost function a=sigma(z) is activation.

Returns:

Pair where Gradient is gradient for this layer, INDArray is epsilon needed by next layer, but before element-wise multiply by sigmaPrime(z). So for standard feed-forward layer, if this layer is L, then return.getSecond() == (w^(L)*(delta^(L))^T)^T

getSize

protected int getSize()

Overrides:

getSize in class Upsampling2D

preOutput

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

Overrides:

preOutput in class Upsampling2D

preOutput

public org.nd4j.linalg.api.ndarray.INDArray preOutput(boolean training,
                                                      boolean forBackprop)

Overrides:

preOutput in class Upsampling2D