Package ai.djl.nn.core

Contains classes that define simple neural network operations.

Interface Summary

Interface	Description
AbstractEmbedding<T>	An Embedding maps elements of type T to a 1-Dimensional representative NDArrays.
AbstractIndexedEmbedding<T>	An AbstractEmbedding where each embedded item can be assigned an integer index.

Class Summary

Class	Description
ConstantEmbedding	An AbstractIndexedEmbedding that always returns a constant value.
Embedding<T>	An Embedding block map a collection of items to 1-Dimensional representative NDArrays.
Embedding.BaseBuilder<T,B extends Embedding.BaseBuilder<T,B>>	The Builder to construct a Embedding type of Block.
Linear	A Linear block applies a linear transformation \(Y = XW^T + b\).
Linear.Builder	The Builder to construct a Linear type of Block.
LinearCollection	A LinearCollection block applies \(m\) linear transformations \(Y_i = X_i W_i + b_i\) for each \(i \in [1, \ldots, m]\) and \(m = \prod_{j=1}^t s_j\).
LinearCollection.Builder	The Builder to construct a LinearCollection type of Block.
Multiplication	A Multiplication block performs an element-wise multiplication of inputs and weights as opposed to a Linear block which additionally sums up each element-wise multiplication.
Multiplication.Builder	The Builder to construct a Multiplication type of Block.
Prelu	Applies Leaky Parametric ReLU activation element-wise to the input.
SparseMax	SparseMax contains a generic implementation of sparsemax function the definition of SparseMax can be referred to https://arxiv.org/pdf/1602.02068.pdf.