Uses of Interface
org.deeplearning4j.nn.weights.IWeightInit
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Uses of IWeightInit in org.deeplearning4j.nn.conf
Fields in org.deeplearning4j.nn.conf declared as IWeightInit Modifier and Type Field Description protected IWeightInit
NeuralNetConfiguration.Builder. weightInitFn
Methods in org.deeplearning4j.nn.conf with parameters of type IWeightInit Modifier and Type Method Description NeuralNetConfiguration.Builder
NeuralNetConfiguration.Builder. weightInit(IWeightInit 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 IWeightInit in org.deeplearning4j.nn.conf.layers
Fields in org.deeplearning4j.nn.conf.layers declared as IWeightInit Modifier and Type Field Description protected IWeightInit
BaseLayer.Builder. weightInitFn
Weight initialization scheme to use, for initial weight valuesprotected IWeightInit
BaseLayer. weightInitFn
protected IWeightInit
BaseRecurrentLayer.Builder. weightInitFnRecurrent
Set the weight initialization for the recurrent weights.protected IWeightInit
BaseRecurrentLayer. weightInitFnRecurrent
Methods in org.deeplearning4j.nn.conf.layers with parameters of type IWeightInit Modifier and Type Method Description void
EmbeddingSequenceLayer.Builder. setWeightInitFn(IWeightInit weightInit)
T
BaseLayer.Builder. weightInit(IWeightInit weightInit)
Weight initialization scheme to use, for initial weight valuesEmbeddingLayer.Builder
EmbeddingLayer.Builder. weightInit(IWeightInit weightInit)
EmbeddingSequenceLayer.Builder
EmbeddingSequenceLayer.Builder. weightInit(IWeightInit weightInit)
T
BaseRecurrentLayer.Builder. weightInitRecurrent(IWeightInit weightInit)
Set the weight initialization for the recurrent weights. -
Uses of IWeightInit in org.deeplearning4j.nn.conf.layers.samediff
Fields in org.deeplearning4j.nn.conf.layers.samediff with type parameters of type IWeightInit Modifier and Type Field Description protected Map<String,IWeightInit>
SameDiffLayer.Builder. paramWeightInit
protected Map<String,IWeightInit>
SameDiffLayer. paramWeightInit
Methods in org.deeplearning4j.nn.conf.layers.samediff with parameters of type IWeightInit Modifier and Type Method Description T
SameDiffLayer.Builder. weightInit(@NonNull String param, @NonNull IWeightInit weightInit)
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Uses of IWeightInit in org.deeplearning4j.nn.params
Methods in org.deeplearning4j.nn.params with parameters of type IWeightInit Modifier and Type Method Description protected INDArray
DefaultParamInitializer. createWeightMatrix(long nIn, long nOut, IWeightInit weightInit, INDArray weightParamView, boolean initializeParameters)
protected INDArray
ElementWiseParamInitializer. createWeightMatrix(long nIn, long nOut, IWeightInit weightInit, INDArray weightParamView, boolean initializeParameters)
protected INDArray
EmbeddingLayerParamInitializer. createWeightMatrix(long nIn, long nOut, IWeightInit weightInit, INDArray weightParamView, boolean initializeParameters)
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Uses of IWeightInit in org.deeplearning4j.nn.transferlearning
Fields in org.deeplearning4j.nn.transferlearning declared as IWeightInit Modifier and Type Field Description protected IWeightInit
FineTuneConfiguration. weightInitFn
Methods in org.deeplearning4j.nn.transferlearning with parameters of type IWeightInit Modifier and Type Method Description TransferLearning.Builder
TransferLearning.Builder. nInReplace(int layerNum, int nIn, IWeightInit 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, IWeightInit 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. nOutReplace(int layerNum, int nOut, IWeightInit scheme, IWeightInit 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.FineTuneConfiguration.Builder
FineTuneConfiguration.Builder. weightInit(IWeightInit weightInit)
Weight initialization scheme to use, for initial weight values -
Uses of IWeightInit in org.deeplearning4j.nn.weights
Classes in org.deeplearning4j.nn.weights that implement IWeightInit Modifier and Type Class Description class
WeightInitConstant
class
WeightInitDistribution
class
WeightInitIdentity
class
WeightInitLecunUniform
Uniform U[-a,a] with a=3/sqrt(fanIn).class
WeightInitNormal
Normal/Gaussian distribution, with mean 0 and standard deviation 1/sqrt(fanIn).class
WeightInitRelu
class
WeightInitReluUniform
class
WeightInitSigmoidUniform
class
WeightInitUniform
class
WeightInitVarScalingNormalFanAvg
class
WeightInitVarScalingNormalFanIn
class
WeightInitVarScalingNormalFanOut
class
WeightInitVarScalingUniformFanAvg
Uniform U[-a,a] with a=3.0/((fanIn + fanOut)/2)class
WeightInitVarScalingUniformFanIn
class
WeightInitVarScalingUniformFanOut
class
WeightInitXavier
class
WeightInitXavierLegacy
Xavier weight init in DL4J up to 0.6.0.class
WeightInitXavierUniform
As per Glorot and Bengio 2010: Uniform distribution U(-s,s) with s = sqrt(6/(fanIn + fanOut))Methods in org.deeplearning4j.nn.weights that return IWeightInit Modifier and Type Method Description IWeightInit
WeightInit. getWeightInitFunction()
Create an instance of the weight initialization functionIWeightInit
WeightInit. getWeightInitFunction(Distribution distribution)
Create an instance of the weight initialization function -
Uses of IWeightInit in org.deeplearning4j.nn.weights.embeddings
Classes in org.deeplearning4j.nn.weights.embeddings that implement IWeightInit Modifier and Type Class Description class
WeightInitEmbedding
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