/* Copyright (C) 2010 Univ. of Massachusetts Amherst, Computer Science Dept. This file is part of "MALLET" (MAchine Learning for LanguagE Toolkit). http://www.cs.umass.edu/~mccallum/mallet This software is provided under the terms of the Common Public License, version 1.0, as published by http://www.opensource.org. For further information, see the file `LICENSE' included with this distribution. */ package cc.mallet.fst.semi_supervised.constraints; import cc.mallet.fst.SumLattice; import cc.mallet.fst.semi_supervised.StateLabelMap; import cc.mallet.types.FeatureVector; import cc.mallet.types.InstanceList; import java.util.ArrayList; import java.util.BitSet; /** * Interface for GE constraint that considers * either one or two states. * * @author Gregory Druck */ public interface GEConstraint { /** * Computes the composite constraint feature value * (over all constraint features) for FeatureVector fv * and a transition from state li1 to li2. * * @param input FeatureVector on transition * @param inputPosition Position of input in sequence * @param srcIndex Source state index for transition * @param destIndex Destination state index for transition * @return Constraint feature value */ double getCompositeConstraintFeatureValue(FeatureVector input, int inputPosition, int srcIndex, int destIndex); /** * Returns the total constraint value. * * @return Constraint value */ double getValue(); /** * Compute expectations using cached lattices. * * @param lattices Cached SumLattices * @param data Unlabeled data */ void computeExpectations(ArrayList<SumLattice> lattices); /** * Zero expectation values. Called before re-computing gradient. */ void zeroExpectations(); /** * Sets that map between the state indices and label indices. * * @param map StateLabelMap */ void setStateLabelMap(StateLabelMap map); /** * This is used in multi-threading. * * @return A copy of the GEConstraint. */ GEConstraint copy(); /** * @return true if constraint feature only considers one state */ boolean isOneStateConstraint(); /** * @param data Unlabeled data * @return Returns a bitset of the size of the data, with the bit set if a constraint feature fires in that instance. */ BitSet preProcess(InstanceList data); /** * Gives the constraint the option to do some caching * using only the FeatureVector. For example, the * constrained input features could be cached. * * @param input FeatureVector input */ void preProcess(FeatureVector input); }