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/*
EGYPT Toolkit for Statistical Machine Translation
Written by Yaser Al-Onaizan, Jan Curin, Michael Jahr, Kevin Knight, John Lafferty, Dan Melamed, David Purdy, Franz Och, Noah Smith, and David Yarowsky.
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 _model3_h
#define _model3_h 1
#include <cassert>
#include <iostream>
#include <algorithm>
#include <functional>
#include <map>
#include <set>
#include "Vector.h"
#include <utility>
#if __GNUC__>2
#include <ext/hash_map>
using __gnu_cxx::hash_map;
#else
#include <hash_map>
#endif
#include <ctime>
#include <fstream>
#include <cmath>
#include "MoveSwapMatrix.h"
#include "TTables.h"
#include "ATables.h"
#include "NTables.h"
#include "getSentence.h"
#include "defs.h"
#include "model2.h"
#include "Perplexity.h"
#include "transpair_model3.h"
#include "transpair_modelhmm.h"
#include "alignment.h"
#include "vocab.h"
#include "D4Tables.h"
#include "AlignTables.h"
class model3 : public model2
{
public:
amodel<PROB> dTable;
amodel<COUNT> dCountTable;
PROB p0,p1;
double p0_count, p1_count ;
nmodel<PROB> nTable;
nmodel<COUNT> nCountTable;
hmm*h;
public:
void setHMM(hmm*_h){h=_h;}
model3(model2& m2);
~model3();
// methods
void transfer(sentenceHandler&, bool, Perplexity&, Perplexity&,bool updateT=1);
void transferSimple(sentenceHandler&, bool, Perplexity&, Perplexity&,bool updateT=1);
void load_tables(const char *nfile, const char *dfile, const char *p0file);
void em(int, sentenceHandler&);
int viterbi(int, int, int,int);
private:
LogProb prob_of_special(Vector<WordIndex>&,
Vector<WordIndex>&,
tmodel<COUNT, PROB>&,
Vector<WordIndex>&,
Vector<WordIndex>&);
LogProb prob_of_target_and_alignment_given_source(Vector<WordIndex>&,
Vector<WordIndex>&,
tmodel<COUNT, PROB>&,
Vector<WordIndex>&,
Vector<WordIndex>&);
LogProb prob_of_target_given_source(tmodel<COUNT, PROB>&,
Vector<WordIndex>&,
Vector<WordIndex>&);
LogProb scoreOfMove(Vector<WordIndex>&, Vector<WordIndex>&,
Vector<WordIndex>&, Vector<WordIndex>&,
tmodel<COUNT, PROB>&, WordIndex, WordIndex);
LogProb scoreOfSwap(Vector<WordIndex>&, Vector<WordIndex>&,
Vector<WordIndex>&, tmodel<COUNT, PROB>&, int, int);
void hillClimb(Vector<WordIndex>&, Vector<WordIndex>&,
Vector<WordIndex>&, Vector<WordIndex>&,
LogProb&, tmodel<COUNT, PROB>&, int, int);
void findBestAlignment(Vector<WordIndex>&, Vector<WordIndex>&,
Vector<WordIndex>&, Vector<WordIndex>&,
LogProb&,int , int);
void findAlignmentsNeighborhood( Vector<WordIndex>&,
Vector<WordIndex>&,
LogProb&align_total_count,
alignmodel&neighborhood,
int, int);
void collectCountsOverAlignement(const Vector<WordIndex>& es,
const Vector<WordIndex>& fs,
const Vector<WordIndex>&,
LogProb , float count);
LogProb viterbi_model2(const transpair_model3&ef, alignment&output, int pair_no,int i_peg = -1 , int j_peg = -1 )const;
LogProb _viterbi_model2(const transpair_model2&ef, alignment&output, int i_peg = -1 , int j_peg = -1 )const;
LogProb viterbi_model2(const transpair_modelhmm&ef, alignment&output, int pair_no,int i_peg = -1 , int j_peg = -1 )const;
private:
void estimate_t_a_d(sentenceHandler& sHandler1, Perplexity& perp1, Perplexity& perp2,bool simple, bool dump_files,bool updateT);
void viterbi_loop(Perplexity&, Perplexity&, sentenceHandler&, bool, const char*,bool,string model);
template<class MODEL_TYPE, class A,class B>
void viterbi_loop_with_tricks(Perplexity&, Perplexity&, sentenceHandler&,
bool, const char*, bool, string model, bool final,A*d4m,B*d5m);
};
#endif
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