Uses of Package
org.deeplearning4j.nn.weights

Packages that use org.deeplearning4j.nn.weights

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

Classes in org.deeplearning4j.nn.weights used by org.deeplearning4j.nn.conf

Class and Description

WeightInit Weight initialization scheme Distribution: Sample weights from a distribution based on shape of input Normalized: Normalize sample weights Size: Sample weights from bound uniform distribution using shape for min and max Uniform: Sample weights from bound uniform distribution (specify min and max) VI: Sample weights from variance normalized initialization (Glorot) Zeros: Generate weights as zeros Xavier: RELU: N(0,2/nIn): He et al.

Classes in org.deeplearning4j.nn.weights used by org.deeplearning4j.nn.conf.layers

Class and Description

WeightInit Weight initialization scheme Distribution: Sample weights from a distribution based on shape of input Normalized: Normalize sample weights Size: Sample weights from bound uniform distribution using shape for min and max Uniform: Sample weights from bound uniform distribution (specify min and max) VI: Sample weights from variance normalized initialization (Glorot) Zeros: Generate weights as zeros Xavier: RELU: N(0,2/nIn): He et al.

Classes in org.deeplearning4j.nn.weights used by org.deeplearning4j.nn.weights

Class and Description

WeightInit Weight initialization scheme Distribution: Sample weights from a distribution based on shape of input Normalized: Normalize sample weights Size: Sample weights from bound uniform distribution using shape for min and max Uniform: Sample weights from bound uniform distribution (specify min and max) VI: Sample weights from variance normalized initialization (Glorot) Zeros: Generate weights as zeros Xavier: RELU: N(0,2/nIn): He et al.