edu.stanford.nlp.sentiment

Class SentimentCostAndGradient

java.lang.Object

edu.stanford.nlp.optimization.AbstractCachingDiffFunction

edu.stanford.nlp.sentiment.SentimentCostAndGradient

All Implemented Interfaces:

DiffFunction, Function, HasInitial

public class SentimentCostAndGradient
extends AbstractCachingDiffFunction

Field Summary

Fields inherited from class edu.stanford.nlp.optimization.AbstractCachingDiffFunction

derivative, value

Constructor Summary

Constructors

Constructor and Description
SentimentCostAndGradient(SentimentModel model, java.util.List<Tree> trainingBatch)

Method Summary

Modifier and Type	Method and Description
void	calculate(double[] theta) Calculate the value at x and the derivative and save them in the respective fields.
int	domainDimension() Returns the number of dimensions in the function's domain
void	forwardPropagateTree(Tree tree) This is the method to call for assigning labels and node vectors to the Tree.

Methods inherited from class edu.stanford.nlp.optimization.AbstractCachingDiffFunction

clearCache, copy, derivativeAt, ensure, getDerivative, gradientCheck, gradientCheck, initial, lastValue, randomInitial, valueAt

Methods inherited from class java.lang.Object

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

Constructor Detail

SentimentCostAndGradient

public SentimentCostAndGradient(SentimentModel model,
                                java.util.List<Tree> trainingBatch)

Method Detail

domainDimension

public int domainDimension()

Description copied from interface: Function

Returns the number of dimensions in the function's domain

Returns:

the number of domain dimensions

calculate

public void calculate(double[] theta)

Description copied from class: AbstractCachingDiffFunction

Calculate the value at x and the derivative and save them in the respective fields.

Specified by:

calculate in class AbstractCachingDiffFunction

Parameters:

theta - The point at which to calculate the function

forwardPropagateTree

public void forwardPropagateTree(Tree tree)

This is the method to call for assigning labels and node vectors to the Tree. After calling this, each of the non-leaf nodes will have the node vector and the predictions of their classes assigned to that subtree's node. The annotations filled in are the RNNCoreAnnotations.NodeVector, Predictions, and PredictedClass. In general, PredictedClass will be the most useful annotation except when training.