Uses of Class
org.deeplearning4j.nn.weights.WeightInit

Packages that use WeightInit

Package	Description
org.deeplearning4j.nn.conf
org.deeplearning4j.nn.conf.graph
org.deeplearning4j.nn.conf.layers
org.deeplearning4j.nn.conf.layers.samediff
org.deeplearning4j.nn.transferlearning
org.deeplearning4j.nn.weights

Uses of WeightInit in org.deeplearning4j.nn.conf

Methods in org.deeplearning4j.nn.conf with parameters of type WeightInit

Modifier and Type	Method and Description
NeuralNetConfiguration.Builder	NeuralNetConfiguration.Builder.weightInit(WeightInit weightInit) Weight initialization scheme to use, for initial weight values Note: values set by this method will be applied to all applicable layers in the network, unless a different value is explicitly set on a given layer.

Uses of WeightInit in org.deeplearning4j.nn.conf.graph

Fields in org.deeplearning4j.nn.conf.graph declared as WeightInit

Modifier and Type	Field and Description
protected WeightInit	AttentionVertex.weightInit
protected WeightInit	AttentionVertex.Builder.weightInit Weight initialization scheme

Methods in org.deeplearning4j.nn.conf.graph with parameters of type WeightInit

Modifier and Type	Method and Description
AttentionVertex.Builder	AttentionVertex.Builder.weightInit(WeightInit weightInit) Weight initialization scheme

Uses of WeightInit in org.deeplearning4j.nn.conf.layers

Methods in org.deeplearning4j.nn.conf.layers with parameters of type WeightInit

Modifier and Type	Method and Description
T	BaseLayer.Builder.weightInit(WeightInit weightInit) Weight initialization scheme to use, for initial weight values
T	BaseRecurrentLayer.Builder.weightInitRecurrent(WeightInit weightInit) Set the weight initialization for the recurrent weights.

Uses of WeightInit in org.deeplearning4j.nn.conf.layers.samediff

Fields in org.deeplearning4j.nn.conf.layers.samediff declared as WeightInit

Modifier and Type	Field and Description
protected WeightInit	SameDiffLayer.weightInit
protected WeightInit	SameDiffLayer.Builder.weightInit

Methods in org.deeplearning4j.nn.conf.layers.samediff with parameters of type WeightInit

Modifier and Type	Method and Description
protected void	AbstractSameDiffLayer.initWeights(int fanIn, int fanOut, WeightInit weightInit, INDArray array)
T	SameDiffLayer.Builder.weightInit(WeightInit weightInit)

Uses of WeightInit in org.deeplearning4j.nn.transferlearning

Methods in org.deeplearning4j.nn.transferlearning with parameters of type WeightInit

Modifier and Type	Method and Description
TransferLearning.Builder	TransferLearning.Builder.nInReplace(int layerNum, int nIn, WeightInit scheme) Modify the architecture of a vertex layer by changing nIn of the specified layer. Note that only the specified layer will be modified - all other layers will not be changed by this call.
TransferLearning.Builder	TransferLearning.Builder.nInReplace(int layerNum, int nIn, WeightInit scheme, Distribution dist) Modify the architecture of a vertex layer by changing nIn of the specified layer. Note that only the specified layer will be modified - all other layers will not be changed by this call.
TransferLearning.GraphBuilder	TransferLearning.GraphBuilder.nInReplace(String layerName, int nIn, WeightInit scheme) Modify the architecture of a vertex layer by changing nIn of the specified layer. Note that only the specified layer will be modified - all other layers will not be changed by this call.
TransferLearning.GraphBuilder	TransferLearning.GraphBuilder.nInReplace(String layerName, int nIn, WeightInit scheme, Distribution dist) Modify the architecture of a vertex layer by changing nIn of the specified layer. Note that only the specified layer will be modified - all other layers will not be changed by this call.
TransferLearning.Builder	TransferLearning.Builder.nOutReplace(int layerNum, int nOut, Distribution dist, WeightInit schemeNext) Modify the architecture of a layer by changing nOut Note this will also affect the layer that follows the layer specified, unless it is the output layer Can specify different weight init schemes for the specified layer and the layer that follows it.
TransferLearning.Builder	TransferLearning.Builder.nOutReplace(int layerNum, int nOut, WeightInit scheme) Modify the architecture of a layer by changing nOut Note this will also affect the layer that follows the layer specified, unless it is the output layer
TransferLearning.Builder	TransferLearning.Builder.nOutReplace(int layerNum, int nOut, WeightInit scheme, Distribution distNext) Modify the architecture of a layer by changing nOut Note this will also affect the layer that follows the layer specified, unless it is the output layer Can specify different weight init schemes for the specified layer and the layer that follows it.
TransferLearning.Builder	TransferLearning.Builder.nOutReplace(int layerNum, int nOut, WeightInit scheme, WeightInit schemeNext) Modify the architecture of a layer by changing nOut Note this will also affect the layer that follows the layer specified, unless it is the output layer Can specify different weight init schemes for the specified layer and the layer that follows it.
TransferLearning.GraphBuilder	TransferLearning.GraphBuilder.nOutReplace(String layerName, int nOut, Distribution dist, WeightInit scheme)
TransferLearning.GraphBuilder	TransferLearning.GraphBuilder.nOutReplace(String layerName, int nOut, WeightInit scheme) Modify the architecture of a vertex layer by changing nOut Note this will also affect the vertex layer that follows the layer specified, unless it is the output layer Currently does not support modifying nOut of layers that feed into non-layer vertices like merge, subset etc To modify nOut for such vertices use remove vertex, followed by add vertex Can specify different weight init schemes for the specified layer and the layer that follows it.
TransferLearning.GraphBuilder	TransferLearning.GraphBuilder.nOutReplace(String layerName, int nOut, WeightInit scheme, Distribution dist)
TransferLearning.GraphBuilder	TransferLearning.GraphBuilder.nOutReplace(String layerName, int nOut, WeightInit scheme, WeightInit schemeNext)
FineTuneConfiguration.Builder	FineTuneConfiguration.Builder.weightInit(WeightInit weightInit) Weight initialization scheme to use, for initial weight values

Uses of WeightInit in org.deeplearning4j.nn.weights

Methods in org.deeplearning4j.nn.weights that return WeightInit

Modifier and Type	Method and Description
static WeightInit	WeightInit.valueOf(String name) Returns the enum constant of this type with the specified name.
static WeightInit[]	WeightInit.values() Returns an array containing the constants of this enum type, in the order they are declared.

Methods in org.deeplearning4j.nn.weights with parameters of type WeightInit

Modifier and Type	Method and Description
static INDArray	WeightInitUtil.initWeights(double fanIn, double fanOut, int[] shape, WeightInit initScheme, Distribution dist, char order, INDArray paramView) Deprecated.
static INDArray	WeightInitUtil.initWeights(double fanIn, double fanOut, int[] shape, WeightInit initScheme, Distribution dist, INDArray paramView) Deprecated.
static INDArray	WeightInitUtil.initWeights(double fanIn, double fanOut, long[] shape, WeightInit initScheme, Distribution dist, char order, INDArray paramView)
static INDArray	WeightInitUtil.initWeights(double fanIn, double fanOut, long[] shape, WeightInit initScheme, Distribution dist, INDArray paramView) Initializes a matrix with the given weight initialization scheme.