Package ai.djl.nn.core

Class SparseMax

java.lang.Object

ai.djl.nn.AbstractBaseBlock

ai.djl.nn.AbstractBlock

ai.djl.nn.core.SparseMax

All Implemented Interfaces:

Block

public class SparseMax
extends AbstractBlock

SparseMax contains a generic implementation of sparsemax function the definition of SparseMax can be referred to https://arxiv.org/pdf/1602.02068.pdf. SparseMax is a simpler implementation of sparseMax function, where we set K as a hyperParameter(default 3). We only do softmax on those max-K data, and we set all the other value as 0.

Field Summary

Fields inherited from class ai.djl.nn.AbstractBlock

children, parameters

Fields inherited from class ai.djl.nn.AbstractBaseBlock

inputNames, inputShapes, outputDataTypes, version

Constructor Summary

Constructors

Constructor	Description
SparseMax()	Creates a sparseMax activation function for the last axis and 3 elements.
SparseMax(int axis)	Creates a sparseMax activation function along a given axis for 3 elements.
SparseMax(int axis, int topK)	Creates a sparseMax activation function along a given axis and number of elements.

Method Summary

Modifier and Type	Method	Description
protected NDList	forwardInternal(ParameterStore parameterStore, NDList inputs, boolean training, ai.djl.util.PairList<String,Object> params)	A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.
Shape[]	getOutputShapes(Shape[] inputShapes)	Returns the expected output shapes of the block for the specified input shapes.

Methods inherited from class ai.djl.nn.AbstractBlock

addChildBlock, addChildBlock, addChildBlockSingleton, addParameter, getChildren, getDirectParameters

Methods inherited from class ai.djl.nn.AbstractBaseBlock

beforeInitialize, cast, clear, describeInput, forward, forward, forwardInternal, getInputShapes, getOutputDataTypes, getParameters, initialize, initializeChildBlocks, isInitialized, loadMetadata, loadParameters, prepare, readInputShapes, saveInputShapes, saveMetadata, saveParameters, setInitializer, setInitializer, setInitializer, toString

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface ai.djl.nn.Block

forward, freezeParameters, freezeParameters, getOutputShapes

Constructor Details

SparseMax

public SparseMax()

Creates a sparseMax activation function for the last axis and 3 elements.

SparseMax

public SparseMax(int axis)

Creates a sparseMax activation function along a given axis for 3 elements.

Parameters:

axis - the axis to do sparseMax for

SparseMax

public SparseMax(int axis,
 int topK)

Creates a sparseMax activation function along a given axis and number of elements.

Parameters:

axis - the axis to do sparseMax for

topK - hyperParameter K

Method Details

getOutputShapes

public Shape[] getOutputShapes(Shape[] inputShapes)

Returns the expected output shapes of the block for the specified input shapes.

Parameters:

inputShapes - the shapes of the inputs

Returns:

the expected output shapes of the block

forwardInternal

protected NDList forwardInternal(ParameterStore parameterStore,
 NDList inputs,
 boolean training,
 ai.djl.util.PairList<String,Object> params)

A helper for Block.forward(ParameterStore, NDList, boolean, PairList) after initialization.

Specified by:

forwardInternal in class AbstractBaseBlock

Parameters:

parameterStore - the parameter store

inputs - the input NDList

training - true for a training forward pass

params - optional parameters

Returns:

the output of the forward pass