org.deeplearning4j.nn.conf.layers

Class Deconvolution2D

java.lang.Object

org.deeplearning4j.nn.conf.layers.Layer

org.deeplearning4j.nn.conf.layers.BaseLayer

org.deeplearning4j.nn.conf.layers.FeedForwardLayer

org.deeplearning4j.nn.conf.layers.ConvolutionLayer

org.deeplearning4j.nn.conf.layers.Deconvolution2D

All Implemented Interfaces:

Serializable, Cloneable, TrainingConfig

public class Deconvolution2D
extends ConvolutionLayer

2D deconvolution layer configuration
Deconvolutions are also known as transpose convolutions or fractionally strided convolutions. In essence, deconvolutions swap forward and backward pass with regular 2D convolutions. See the paper by Matt Zeiler for details: http://www.matthewzeiler.com/wp-content/uploads/2017/07/cvpr2010.pdf For an intuitive guide to convolution arithmetic and shapes, see: https://arxiv.org/abs/1603.07285v1

Author:

Max Pumperla

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	Deconvolution2D.Builder

Nested classes/interfaces inherited from class org.deeplearning4j.nn.conf.layers.ConvolutionLayer

ConvolutionLayer.AlgoMode, ConvolutionLayer.BaseConvBuilder<T extends ConvolutionLayer.BaseConvBuilder<T>>, ConvolutionLayer.BwdDataAlgo, ConvolutionLayer.BwdFilterAlgo, ConvolutionLayer.FwdAlgo

Field Summary

Fields inherited from class org.deeplearning4j.nn.conf.layers.ConvolutionLayer

cnn2dDataFormat, convolutionMode, cudnnAlgoMode, cudnnAllowFallback, cudnnBwdDataAlgo, cudnnBwdFilterAlgo, cudnnFwdAlgo, dilation, hasBias, kernelSize, padding, stride

Fields inherited from class org.deeplearning4j.nn.conf.layers.FeedForwardLayer

nIn, nOut, timeDistributedFormat

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

activationFn, biasInit, biasUpdater, gainInit, gradientNormalization, gradientNormalizationThreshold, iUpdater, regularization, regularizationBias, weightInitFn, weightNoise

Fields inherited from class org.deeplearning4j.nn.conf.layers.Layer

constraints, iDropout, layerName

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	Deconvolution2D(ConvolutionLayer.BaseConvBuilder<?> builder) Deconvolution2D layer nIn in the input layer is the number of channels nOut is the number of filters to be used in the net or in other words the channels The builder specifies the filter/kernel size, the stride and padding The pooling layer takes the kernel size

Method Summary

Modifier and Type	Method and Description
Deconvolution2D	clone()
InputType	getOutputType(int layerIndex, InputType inputType) For a given type of input to this layer, what is the type of the output?
boolean	hasBias()
ParamInitializer	initializer()
Layer	instantiate(NeuralNetConfiguration conf, Collection<TrainingListener> trainingListeners, int layerIndex, INDArray layerParamsView, boolean initializeParams, DataType networkDataType)

Methods inherited from class org.deeplearning4j.nn.conf.layers.ConvolutionLayer

getMemoryReport, getPreProcessorForInputType, setNIn

Methods inherited from class org.deeplearning4j.nn.conf.layers.FeedForwardLayer

isPretrainParam

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

getGradientNormalization, getRegularizationByParam, getUpdaterByParam, resetLayerDefaultConfig

Methods inherited from class org.deeplearning4j.nn.conf.layers.Layer

initializeConstraints, setDataType

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.TrainingConfig

getGradientNormalizationThreshold, getLayerName

Constructor Detail

Deconvolution2D

protected Deconvolution2D(ConvolutionLayer.BaseConvBuilder<?> builder)

Deconvolution2D layer nIn in the input layer is the number of channels nOut is the number of filters to be used in the net or in other words the channels The builder specifies the filter/kernel size, the stride and padding The pooling layer takes the kernel size

Method Detail

hasBias

public boolean hasBias()

Overrides:

hasBias in class ConvolutionLayer

clone

public Deconvolution2D clone()

Overrides:

clone in class ConvolutionLayer

instantiate

public Layer instantiate(NeuralNetConfiguration conf,
                         Collection<TrainingListener> trainingListeners,
                         int layerIndex,
                         INDArray layerParamsView,
                         boolean initializeParams,
                         DataType networkDataType)

Overrides:

instantiate in class ConvolutionLayer

initializer

public ParamInitializer initializer()

Overrides:

initializer in class ConvolutionLayer

Returns:

The parameter initializer for this model

getOutputType

public InputType getOutputType(int layerIndex,
                               InputType inputType)

Description copied from class: Layer

For a given type of input to this layer, what is the type of the output?

Overrides:

getOutputType in class ConvolutionLayer

Parameters:

layerIndex - Index of the layer

inputType - Type of input for the layer

Returns:

Type of output from the layer