public Lattice(model m, inference inf, dataSeq x) { _w = x.Count; _h = m.NTag; _logBel = new belief(_w, _h); List <dMatrix> YYlist = new List <dMatrix>(); List <List <double> > Ylist = new List <List <double> >(); inf.getYYandY(m, x, YYlist, Ylist); for (int i = 0; i < _w; i++) { _logBel.belState[i] = new List <double>(Ylist[i]); if (i > 0) { _logBel.belEdge[i] = new dMatrix(YYlist[i]); } } _heuListList = new List <List <double> >(); for (int i = 0; i < _w; i++) { _heuListList.Add(new List <double>(new double[_h])); } Viterbi _bwdViterbi = new Viterbi(_w, _h); for (int i = 0; i < _w; i++) { _bwdViterbi.setScores(i, Ylist[i], YYlist[i]); } List <int> tags = new List <int>(); _bwdViterbi.runViterbi(ref tags); //update the viterbiHeuristicMap for (int i = 0; i < _w; i++) { for (int j = 0; j < _h; j++) { double h = _bwdViterbi.getPathScore(i, j); setHeuMap(i, j, h); } } //get zGold ZGold = 0; for (int i = 0; i < x.Count; i++) { int s = x.getTags(i); ZGold += Ylist[i][s]; if (i > 0) { int sPre = x.getTags(i - 1); ZGold += YYlist[i][sPre, s]; } } }
//the scalar version virtual public void getLogYY(double scalar, model m, dataSeq x, int i, ref dMatrix YY, ref List <double> Y, bool takeExp, bool mask) { YY.set(0); listTool.listSet(ref Y, 0); List <double> w = m.W; List <featureTemp> fList = _fGene.getFeatureTemp(x, i); int nTag = m.NTag; for (int j = 0; j < fList.Count; j++) { featureTemp ptr = fList[j]; int id = ptr.id; double v = ptr.val; for (int s = 0; s < nTag; s++) { int f = _fGene.getNodeFeatID(id, s); Y[s] += w[f] * scalar * v; } } if (i > 0) { for (int s = 0; s < nTag; s++) { for (int sPre = 0; sPre < nTag; sPre++) { int f = _fGene.getEdgeFeatID(sPre, s); YY[sPre, s] += w[f] * scalar; } } } double maskValue = double.MinValue; if (takeExp) { listTool.listExp(ref Y); YY.eltExp(); maskValue = 0; } if (mask) { List <int> tagList = x.getTags(); for (int s = 0; s < Y.Count; s++) { if (tagList[i] != s) { Y[s] = maskValue; } } } }
public void getYYandY(model m, dataSeq x, List <dMatrix> YYlist, List <List <double> > Ylist, List <dMatrix> maskYYlist, List <List <double> > maskYlist) { int nNodes = x.Count; //int nTag = m.NTag; int nState = m.NState; double[] dAry = new double[nState]; bool mask = false; try { //Global.rwlock.AcquireReaderLock(Global.readWaitTime); for (int i = 0; i < nNodes; i++) { dMatrix YYi = new dMatrix(nState, nState); List <double> Yi = new List <double>(dAry); //compute the Mi matrix getLogYY(m, x, i, ref YYi, ref Yi, false, mask); YYlist.Add(YYi); Ylist.Add(Yi); maskYYlist.Add(new dMatrix(YYi)); maskYlist.Add(new List <double>(Yi)); } //Global.rwlock.ReleaseReaderLock(); } catch (ApplicationException) { Console.WriteLine("read out time!"); } //get the masked YY and Y double maskValue = double.MinValue; dMatrix statesPerNodes = m.getStatesPerNode(x); for (int i = 0; i < nNodes; i++) { List <double> Y = maskYlist[i]; List <int> tagList = x.getTags(); for (int s = 0; s < Y.Count; s++) { if (statesPerNodes[i, s] == 0) { Y[s] = maskValue; } } } }
virtual public void getLogYY(model m, dataSeq x, int i, ref dMatrix YY, ref List <double> Y, bool takeExp, bool mask) { YY.set(0); listTool.listSet(ref Y, 0); float[] w = m.W; List <featureTemp> fList = _fGene.getFeatureTemp(x, i); int nTag = m.NTag; foreach (featureTemp ft in fList) { for (int s = 0; s < nTag; s++) { int f = _fGene.getNodeFeatID(ft.id, s); Y[s] += w[f] * ft.val; } } if (i > 0) { for (int s = 0; s < nTag; s++) { for (int sPre = 0; sPre < nTag; sPre++) { int f = _fGene.getEdgeFeatID(sPre, s); YY[sPre, s] += w[f]; } } } double maskValue = double.MinValue; if (takeExp) { listTool.listExp(ref Y); YY.eltExp(); maskValue = 0; } if (mask) { List <int> tagList = x.getTags(); for (int s = 0; s < Y.Count; s++) { if (tagList[i] != s) { Y[s] = maskValue; } } } }
public dMatrix getStatesPerNode(dataSeq x) { int n = x.Count; dMatrix spn = x.GoldStatesPerNode; if (spn == null || spn.R == 0) { List <int> tList = x.getTags(); spn = new dMatrix(tList.Count, _nTag); for (int i = 0; i < tList.Count; i++) { int tag = tList[i]; spn[i, tag] = 1; } x.GoldStatesPerNode = spn; } return(spn); }
public dMatrix getStatesPerNode(dataSeq x) { int n = x.Count; dMatrix spn = x.GoldStatesPerNode; if (spn == null || spn.R == 0) { List <int> tList = x.getTags(); spn = new dMatrix(tList.Count, _nHiddenState); for (int i = 0; i < tList.Count; i++) { int tag = tList[i]; List <int> states = tagToHiddenStates(tag); foreach (int s in states) { spn[i, s] = 1; } } x.GoldStatesPerNode = spn; } return(spn); }
//the scalar version override public void getLogYY(double scalar, model m, dataSeq x, int i, ref dMatrix YY, ref List <double> Y, bool takeExp, bool mask) { YY.set(0); listTool.listSet(ref Y, 0); float[] w = m.W; List <featureTemp> fList = _fGene.getFeatureTemp(x, i); int nTag = m.NTag; foreach (featureTemp ft in fList) { for (int s = 0; s < nTag; s++) { int f = _fGene.getNodeFeatID(ft.id, s); Y[s] += w[f] * scalar * ft.val; } } if (i > 0) { //non-rich if (Global.useTraditionalEdge) { for (int s = 0; s < nTag; s++) { for (int sPre = 0; sPre < nTag; sPre++) { int f = _fGene.getEdgeFeatID(sPre, s); YY[sPre, s] += w[f] * scalar; } } } //rich foreach (featureTemp im in fList) { int id = im.id; if (id < _fGene.getNRichFeatTemp()) { for (int s = 0; s < nTag; s++) { for (int sPre = 0; sPre < nTag; sPre++) { int f = _fGene.getEdgeFeatID(id, sPre, s); YY[sPre, s] += w[f] * scalar * im.val; } } } } } double maskValue = double.MinValue; if (takeExp) { listTool.listExp(ref Y); YY.eltExp(); maskValue = 0; } if (mask) { List <int> tagList = x.getTags(); for (int s = 0; s < Y.Count; s++) { if (tagList[i] != s) { Y[s] = maskValue; } } } }