Uses of Interface
org.deeplearning4j.nn.api.ParamInitializer

Packages that use ParamInitializer

Package	Description
org.deeplearning4j.nn.conf.layers
org.deeplearning4j.nn.params

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

Methods in org.deeplearning4j.nn.conf.layers that return ParamInitializer

Modifier and Type	Method and Description
ParamInitializer	SubsamplingLayer.initializer()
ParamInitializer	OutputLayer.initializer()
ParamInitializer	BatchNormalization.initializer()
ParamInitializer	GravesLSTM.initializer()
ParamInitializer	EmbeddingLayer.initializer()
ParamInitializer	ConvolutionLayer.initializer()
ParamInitializer	AutoEncoder.initializer()
abstract ParamInitializer	Layer.initializer()
ParamInitializer	GravesBidirectionalLSTM.initializer()
ParamInitializer	RBM.initializer()
ParamInitializer	LocalResponseNormalization.initializer()
ParamInitializer	RnnOutputLayer.initializer()
ParamInitializer	DenseLayer.initializer()
ParamInitializer	ActivationLayer.initializer()

Uses of ParamInitializer in org.deeplearning4j.nn.params

Classes in org.deeplearning4j.nn.params that implement ParamInitializer

Modifier and Type	Class and Description
class	BatchNormalizationParamInitializer Batch normalization variable init
class	ConvolutionParamInitializer Initialize convolution params.
class	DefaultParamInitializer Static weight initializer with just a weight matrix and a bias
class	EmptyParamInitializer
class	GravesBidirectionalLSTMParamInitializer LSTM Parameter initializer, for LSTM based on Graves: Supervised Sequence Labelling with Recurrent Neural Networks http://www.cs.toronto.edu/~graves/phd.pdf
class	GravesLSTMParamInitializer LSTM Parameter initializer, for LSTM based on Graves: Supervised Sequence Labelling with Recurrent Neural Networks http://www.cs.toronto.edu/~graves/phd.pdf
class	PretrainParamInitializer Pretrain weight initializer.