org.deeplearning4j.nn.conf.layers

Class ConvolutionLayer.BaseConvBuilder<T extends ConvolutionLayer.BaseConvBuilder<T>>

java.lang.Object

org.deeplearning4j.nn.conf.layers.Layer.Builder<T>

org.deeplearning4j.nn.conf.layers.BaseLayer.Builder<T>

org.deeplearning4j.nn.conf.layers.FeedForwardLayer.Builder<T>

org.deeplearning4j.nn.conf.layers.ConvolutionLayer.BaseConvBuilder<T>

Direct Known Subclasses:

Convolution1DLayer.Builder, Convolution3D.Builder, ConvolutionLayer.Builder, Deconvolution2D.Builder, DepthwiseConvolution2D.Builder, SeparableConvolution2D.Builder

Enclosing class:

ConvolutionLayer

protected abstract static class ConvolutionLayer.BaseConvBuilder<T extends ConvolutionLayer.BaseConvBuilder<T>>
extends FeedForwardLayer.Builder<T>

Field Summary

Fields

Modifier and Type	Field and Description
protected int	convolutionDim
protected ConvolutionMode	convolutionMode
protected ConvolutionLayer.AlgoMode	cudnnAlgoMode
protected boolean	cudnnAllowFallback
protected ConvolutionLayer.BwdDataAlgo	cudnnBwdDataAlgo
protected ConvolutionLayer.BwdFilterAlgo	cudnnBwdFilterAlgo
protected ConvolutionLayer.FwdAlgo	cudnnFwdAlgo
protected int[]	dilation
protected boolean	hasBias
int[]	kernelSize
protected int[]	padding
protected int[]	stride

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

nIn, nOut

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

activationFn, biasInit, biasUpdater, dist, gradientNormalization, gradientNormalizationThreshold, iupdater, l1, l1Bias, l2, l2Bias, weightInit, weightNoise

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

allParamConstraints, biasConstraints, iDropout, layerName, weightConstraints

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	BaseConvBuilder()
protected	BaseConvBuilder(int... kernelSize)
protected	BaseConvBuilder(int[] kernelSize, int[] stride)
protected	BaseConvBuilder(int[] kernelSize, int[] stride, int dim)
protected	BaseConvBuilder(int[] kernelSize, int[] stride, int[] padding)
protected	BaseConvBuilder(int[] kernelSize, int[] stride, int[] padding, int dim)
protected	BaseConvBuilder(int[] kernelSize, int[] stride, int[] padding, int[] dilation)
protected	BaseConvBuilder(int[] kernelSize, int[] stride, int[] padding, int[] dilation, int dim)
protected	BaseConvBuilder(int dim, int... kernelSize)

Method Summary

Modifier and Type	Method and Description
T	convolutionMode(ConvolutionMode convolutionMode) Set the convolution mode for the Convolution layer.
T	cudnnAlgoMode(ConvolutionLayer.AlgoMode cudnnAlgoMode) Defaults to "PREFER_FASTEST", but "NO_WORKSPACE" uses less memory.
T	cudnnAllowFallback(boolean allowFallback) When using CuDNN and an error is encountered, should fallback to the non-CuDNN implementatation be allowed? If set to false, an exception in CuDNN will be propagated back to the user.
T	cudnnBwdDataMode(ConvolutionLayer.BwdDataAlgo cudnnBwdDataAlgo)
T	cudnnBwdFilterMode(ConvolutionLayer.BwdFilterAlgo cudnnBwdFilterAlgo)
T	cudnnFwdMode(ConvolutionLayer.FwdAlgo cudnnFwdAlgo)
T	dilation(int... dilation) Kernel dilation.
T	hasBias(boolean hasBias) If true (default): include bias parameters in the model.

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

nIn, nOut, units

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

activation, activation, biasInit, biasUpdater, dist, gradientNormalization, gradientNormalizationThreshold, l1, l1Bias, l2, l2Bias, updater, updater, weightInit, weightInit, weightNoise

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

build, constrainAllParameters, constrainBias, constrainWeights, dropOut, dropOut, name

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

convolutionDim

protected int convolutionDim

hasBias

protected boolean hasBias

convolutionMode

protected ConvolutionMode convolutionMode

dilation

protected int[] dilation

kernelSize

public int[] kernelSize

stride

protected int[] stride

padding

protected int[] padding

cudnnAlgoMode

protected ConvolutionLayer.AlgoMode cudnnAlgoMode

cudnnFwdAlgo

protected ConvolutionLayer.FwdAlgo cudnnFwdAlgo

cudnnBwdFilterAlgo

protected ConvolutionLayer.BwdFilterAlgo cudnnBwdFilterAlgo

cudnnBwdDataAlgo

protected ConvolutionLayer.BwdDataAlgo cudnnBwdDataAlgo

cudnnAllowFallback

protected boolean cudnnAllowFallback

Constructor Detail

BaseConvBuilder

protected BaseConvBuilder(int[] kernelSize,
                          int[] stride,
                          int[] padding,
                          int[] dilation,
                          int dim)

BaseConvBuilder

protected BaseConvBuilder(int[] kernelSize,
                          int[] stride,
                          int[] padding,
                          int[] dilation)

BaseConvBuilder

protected BaseConvBuilder(int[] kernelSize,
                          int[] stride,
                          int[] padding,
                          int dim)

BaseConvBuilder

protected BaseConvBuilder(int[] kernelSize,
                          int[] stride,
                          int[] padding)

BaseConvBuilder

protected BaseConvBuilder(int[] kernelSize,
                          int[] stride,
                          int dim)

BaseConvBuilder

protected BaseConvBuilder(int[] kernelSize,
                          int[] stride)

BaseConvBuilder

protected BaseConvBuilder(int dim,
                          int... kernelSize)

BaseConvBuilder

protected BaseConvBuilder(int... kernelSize)

BaseConvBuilder

protected BaseConvBuilder()

Method Detail

hasBias

public T hasBias(boolean hasBias)

If true (default): include bias parameters in the model. False: no bias.

Parameters:

hasBias - If true: include bias parameters in this model

convolutionMode

public T convolutionMode(ConvolutionMode convolutionMode)

Set the convolution mode for the Convolution layer. See ConvolutionMode for more details

Parameters:

convolutionMode - Convolution mode for layer

dilation

public T dilation(int... dilation)

Kernel dilation. Default: {1, 1}, which is standard convolutions. Used for implementing dilated convolutions, which are also known as atrous convolutions. For more details, see: Yu and Koltun (2014) and Chen et al. (2014), as well as http://deeplearning.net/software/theano/tutorial/conv_arithmetic.html#dilated-convolutions

Parameters:

dilation - Dilation for kernel

cudnnAlgoMode

public T cudnnAlgoMode(ConvolutionLayer.AlgoMode cudnnAlgoMode)

Defaults to "PREFER_FASTEST", but "NO_WORKSPACE" uses less memory.

cudnnFwdMode

public T cudnnFwdMode(ConvolutionLayer.FwdAlgo cudnnFwdAlgo)

cudnnBwdFilterMode

public T cudnnBwdFilterMode(ConvolutionLayer.BwdFilterAlgo cudnnBwdFilterAlgo)

cudnnBwdDataMode

public T cudnnBwdDataMode(ConvolutionLayer.BwdDataAlgo cudnnBwdDataAlgo)

cudnnAllowFallback

public T cudnnAllowFallback(boolean allowFallback)

When using CuDNN and an error is encountered, should fallback to the non-CuDNN implementatation be allowed? If set to false, an exception in CuDNN will be propagated back to the user. If false, the built-in (non-CuDNN) implementation for ConvolutionLayer will be used

Parameters:

allowFallback - Whether fallback to non-CuDNN implementation should be used