1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
|
/*
Copyright (C) 2000,2001 Franz Josef Och (RWTH Aachen - Lehrstuhl fuer Informatik VI)
This file is part of GIZA++ ( extension of GIZA ).
This program is free software; you can redistribute it and/or
modify it under the terms of the GNU General Public License
as published by the Free Software Foundation; either version 2
of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program; if not, write to the Free Software
Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307,
USA.
*/
#ifndef transpair_modelhmm_h_fjo_defined
#define transpair_modelhmm_h_fjo_defined
#include "Array2.h"
#include "defs.h"
#include "Vector.h"
#include "NTables.h"
#include "ATables.h"
#include "TTables.h"
#include "alignment.h"
#include <math.h>
#include "transpair_model2.h"
#include "ForwardBackward.h"
#include "hmm.h"
class transpair_modelhmm : public transpair_model2
{
public:
typedef transpair_modelhmm simpler_transpair_model;
HMMNetwork*net;
transpair_modelhmm(const Vector<WordIndex>&es, const Vector<WordIndex>&fs, const tmodel<COUNT, PROB>&tTable,
const amodel<PROB>&aTable,const amodel<PROB>&,const nmodel<PROB>&,
double, double,const hmm*h)
: transpair_model2(es,fs,tTable,aTable),net(h->makeHMMNetwork(es,fs,0))
{}
~transpair_modelhmm() { delete net; }
int modelnr()const{return 6;}
LogProb scoreOfMove(const alignment&a, WordIndex _new_i, WordIndex j,double=-1.0)const
{
int new_i=_new_i;
LogProb change=1.0;
int old_i=a(j);
if (old_i == new_i)
change=1.0;
else
{
int theJ=j-1;
old_i--;
new_i--;
int jj=j-1;
while(jj>0&&a(jj)==0)
jj--;
int theIPrev= (jj>0)?(a(jj)-1):0;
if( j>1&&a(j-1)==0 )
theIPrev+=l;
if( old_i==-1 ){old_i = theIPrev;if(old_i<int(l))old_i+=l;}
if( new_i==-1 ){new_i = theIPrev;if(new_i<int(l))new_i+=l;}
int theIPrevOld=theIPrev,theIPrevNew=theIPrev;
if( theJ==0 )
{
change*=net->getAlphainit(new_i)/net->getAlphainit(old_i);
}
do
{
if( new_i!=old_i )
{
change*=net->nodeProb(new_i,theJ)/net->nodeProb(old_i,theJ);
}
if( theJ>0)
change*=net->outProb(theJ,theIPrevNew,new_i)/net->outProb(theJ,theIPrevOld,old_i);
theIPrevOld=old_i;
theIPrevNew=new_i;
theJ++;
if( theJ<int(m) && a(theJ+1)==0 )
{
if( new_i<int(l)) new_i+=l;
if( old_i<int(l)) old_i+=l;
}
} while( theJ<int(m) && a(theJ+1)==0 );
if(theJ==int(m))
{
change*=net->getBetainit(new_i)/net->getBetainit(old_i);
}
else
{
new_i=a(theJ+1)-1;
if( new_i==-1)
new_i=theIPrevNew;
change*=net->outProb(theJ,theIPrevNew,new_i)/net->outProb(theJ,theIPrevOld,new_i);
}
}
return change;
}
LogProb scoreOfAlignmentForChange(const alignment&)const
{return -1.0; }
LogProb scoreOfSwap(const alignment&a, WordIndex j1, WordIndex j2,double=-1.0)const
{
return _scoreOfSwap(a,j1,j2);
}
LogProb _scoreOfMove(const alignment&a, WordIndex new_i, WordIndex j,double=-1.0)const
{
alignment b(a);
b.set(j, new_i);
LogProb a_prob=prob_of_target_and_alignment_given_source(a);
LogProb b_prob=prob_of_target_and_alignment_given_source(b);
if( a_prob )
return b_prob/a_prob;
else if( b_prob )
return 1e20;
else
return 1.0;
}
LogProb _scoreOfSwap(const alignment&a, WordIndex j1, WordIndex j2,double=-1.0)const
{
WordIndex aj1=a(j1),aj2=a(j2);
if( aj1==aj2 )
return 1.0;
LogProb a_prob=prob_of_target_and_alignment_given_source(a);
/*alignment b(a);
b.set(j1, a(j2));
b.set(j2, a(j1));
LogProb b_prob=prob_of_target_and_alignment_given_source(b);*/
const_cast<alignment&>(a).set(j1,aj2);
const_cast<alignment&>(a).set(j2,aj1);
LogProb b_prob=prob_of_target_and_alignment_given_source(a);
const_cast<alignment&>(a).set(j1,aj1);
const_cast<alignment&>(a).set(j2,aj2);
if( a_prob )
return b_prob/a_prob;
else if( b_prob )
return 1e20;
else
return 1.0;
}
inline friend ostream&operator<<(ostream&out, const transpair_modelhmm&)
{
return out << "NO-OUTPUT for transpair_modelhmm\n";
}
LogProb prob_of_target_and_alignment_given_source(const alignment&al,bool verbose=0)const
{
double prob=1.0;
int theIPrev=0;
for(unsigned int j=1;j<=m;j++)
{
int theJ=j-1;
int theI=al(j)-1;
if( theI==-1 )
theI=(theIPrev%l)+l;
prob*=net->nodeProb(theI,theJ);
if( verbose )
cout << "NP " << net->nodeProb(theI,theJ) << ' ';
if( j==1 )
{
prob*=net->getAlphainit(theI);
if( verbose )
cout << "AP0 " << net->getAlphainit(theI) << ' ';
}
else
{
prob*=net->outProb(theJ,theIPrev,theI);
if( verbose )
cout << "AP1 " << net->outProb(theJ,theIPrev,theI) << ' ';
}
theIPrev=theI;
if( j==m )
{
prob*=net->getBetainit(theI);
if( verbose )
cout << "AP2 " << net->getBetainit(theI) << ' ';
}
if( verbose )
cout << "j:"<<theJ<<" i:"<<theI << "; ";
}
if( verbose )
cout << '\n';
return prob*net->finalMultiply;
}
void computeScores(const alignment&al,vector<double>&d)const
{
double prob1=1.0,prob2=1.0;
int theIPrev=0;
for(unsigned int j=1;j<=m;j++)
{
int theJ=j-1;
int theI=al(j)-1;
if( theI==-1 )
theI=(theIPrev%l)+l;
prob1*=net->nodeProb(theI,theJ);
if( j==1 )
{
prob2*=net->getAlphainit(theI);
}
else
{
prob2*=net->outProb(theJ,theIPrev,theI);
}
theIPrev=theI;
if( j==m )
{
prob2*=net->getBetainit(theI);
}
}
d.push_back(prob1);
d.push_back(prob2);
}
bool isSubOptimal()const{return 0;}
};
#endif
|
