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// -*- c++ -*-
// Sampling phrase table implementation based on memory-mapped suffix arrays.
// Design and code by Ulrich Germann.
#pragma once
#include <boost/thread.hpp>
#include <boost/scoped_ptr.hpp>
#include "moses/TypeDef.h"
#include "moses/TranslationModel/UG/generic/sorting/VectorIndexSorter.h"
#include "moses/TranslationModel/UG/generic/sampling/Sampling.h"
#include "moses/TranslationModel/UG/generic/file_io/ug_stream.h"
#include "moses/TranslationModel/UG/mm/ug_mm_ttrack.h"
#include "moses/TranslationModel/UG/mm/ug_mm_tsa.h"
#include "moses/TranslationModel/UG/mm/tpt_tokenindex.h"
#include "moses/TranslationModel/UG/mm/ug_corpus_token.h"
#include "moses/TranslationModel/UG/mm/ug_typedefs.h"
#include "moses/TranslationModel/UG/mm/tpt_pickler.h"
#include "moses/TranslationModel/UG/mm/ug_bitext.h"
#include "moses/TranslationModel/UG/mm/ug_lexical_phrase_scorer2.h"
#include "moses/TranslationModel/UG/TargetPhraseCollectionCache.h"
#include "moses/FF/LexicalReordering/LexicalReordering.h"
#include "moses/InputFileStream.h"
#include "moses/FactorTypeSet.h"
#include "moses/TargetPhrase.h"
#include <boost/dynamic_bitset.hpp>
#include "moses/TargetPhraseCollection.h"
#include "util/usage.hh"
#include <map>
#include "moses/TranslationModel/PhraseDictionary.h"
#include "sapt_phrase_scorers.h"
// TO DO:
// - make lexical phrase scorer take addition to the "dynamic overlay" into account
// - switch to pool of sapts, where each sapt has its own provenance feature
// RESEARCH QUESTION: is this more effective than having multiple phrase tables,
// each with its own set of features?
namespace Moses
{
using namespace bitext;
class Mmsapt
#ifndef NO_MOSES
: public PhraseDictionary
#endif
{
// using namespace std;
class TPCOllCache;
friend class Alignment;
std::map<std::string,std::string> param;
std::string m_name;
public:
typedef L2R_Token<SimpleWordId> Token;
typedef mmBitext<Token> mmbitext;
typedef imBitext<Token> imbitext;
typedef Bitext<Token> bitext;
typedef TSA<Token> tsa;
typedef PhraseScorer<Token> pscorer;
private:
// vector<sptr<bitext> > shards;
mmbitext btfix;
sptr<imbitext> btdyn;
std::string m_bname, m_extra_data, m_bias_file,m_bias_server;
std::string L1;
std::string L2;
float m_lbop_conf; // confidence level for lbop smoothing
float m_lex_alpha; // alpha paramter (j+a)/(m+a) for lexical smoothing
// alpha parameter for lexical smoothing (joint+alpha)/(marg + alpha)
// must be > 0 if dynamic
size_t m_default_sample_size;
size_t m_workers; // number of worker threads for sampling the bitexts
std::vector<std::string> m_feature_set_names; // one or more of: standard, datasource
std::string m_bias_logfile;
boost::scoped_ptr<ofstream> m_bias_logger; // for logging to a file
ostream* m_bias_log;
int m_bias_loglevel;
LexicalReordering* m_lr_func; // associated lexical reordering function
string m_lr_func_name; // name of associated lexical reordering function
public:
void* const cache_key; // for getting cache from ttask
void* const context_key; // for context scope from ttask
private:
boost::shared_ptr<SamplingBias> m_bias; // for global default bias
boost::shared_ptr<TPCollCache> m_cache; // for global default bias
size_t m_cache_size; //
size_t input_factor; //
size_t output_factor; // we can actually return entire Tokens!
// for display for human inspection (ttable dumps):
std::vector<std::string> m_feature_names; // names of features activated
std::vector<bool> m_is_logval; // keeps track of which features are log valued
std::vector<bool> m_is_integer; // keeps track of which features are integer valued
std::vector<sptr<pscorer > > m_active_ff_fix; // activated feature functions (fix)
std::vector<sptr<pscorer > > m_active_ff_dyn; // activated feature functions (dyn)
std::vector<sptr<pscorer > > m_active_ff_common;
// activated feature functions (dyn)
void
register_ff(sptr<pscorer> const& ff, std::vector<sptr<pscorer> > & registry);
template<typename fftype>
void
check_ff(std::string const ffname,std::vector<sptr<pscorer> >* registry = NULL);
// add feature function if specified
template<typename fftype>
void
check_ff(std::string const ffname, float const xtra,
std::vector<sptr<pscorer> >* registry = NULL);
// add feature function if specified
void
add_corpus_specific_features(std::vector<sptr<pscorer > >& ffvec);
// built-in feature functions
// PScorePfwd<Token> calc_pfwd_fix, calc_pfwd_dyn;
// PScorePbwd<Token> calc_pbwd_fix, calc_pbwd_dyn;
// PScoreLex<Token> calc_lex;
// this one I'd like to see as an external ff eventually
// PScorePC<Token> apply_pp; // apply phrase penalty
// PScoreLogCounts<Token> add_logcounts_fix;
// PScoreLogCounts<Token> add_logcounts_dyn;
void init(std::string const& line);
mutable boost::shared_mutex m_lock;
// mutable boost::shared_mutex m_cache_lock;
// for more complex operations on the cache
bool withPbwd;
bool poolCounts;
std::vector<FactorType> ofactor;
void setup_local_feature_functions();
private:
void read_config_file(std::string fname, std::map<std::string,std::string>& param);
// phrase table feature weights for alignment:
std::vector<float> feature_weights;
std::vector<std::vector<id_type> > wlex21;
// word translation lexicon (without counts, get these from calc_lex.COOC)
typedef mm2dTable<id_type,id_type,uint32_t,uint32_t> mm2dtable_t;
mm2dtable_t COOCraw;
TargetPhrase*
mkTPhrase(Phrase const& src,
Moses::bitext::PhrasePair<Token>* fix,
Moses::bitext::PhrasePair<Token>* dyn,
sptr<Bitext<Token> > const& dynbt) const;
void
process_pstats
(Phrase const& src,
uint64_t const pid1,
pstats const& stats,
Bitext<Token> const & bt,
TargetPhraseCollection* tpcoll
) const;
bool
pool_pstats
(Phrase const& src,
uint64_t const pid1a, pstats * statsa, Bitext<Token> const & bta,
uint64_t const pid1b, pstats const* statsb, Bitext<Token> const & btb,
TargetPhraseCollection* tpcoll) const;
bool
combine_pstats
(Phrase const& src,
uint64_t const pid1a, pstats* statsa, Bitext<Token> const & bta,
uint64_t const pid1b, pstats const* statsb, Bitext<Token> const & btb,
TargetPhraseCollection* tpcoll) const;
void load_extra_data(std::string bname, bool locking);
void load_bias(std::string bname);
public:
// Mmsapt(std::string const& description, std::string const& line);
Mmsapt(std::string const& line);
void Load();
void Load(bool with_checks);
size_t SetTableLimit(size_t limit); // returns the prior table limit
std::string const& GetName() const;
#ifndef NO_MOSES
TargetPhraseCollection const*
GetTargetPhraseCollectionLEGACY(ttasksptr const& ttask, const Phrase& src) const;
TargetPhraseCollection const*
GetTargetPhraseCollectionLEGACY(const Phrase& src) const;
void
GetTargetPhraseCollectionBatch(ttasksptr const& ttask,
const InputPathList &inputPathQueue) const;
//! Create a sentence-specific manager for SCFG rule lookup.
ChartRuleLookupManager*
CreateRuleLookupManager(const ChartParser &, const ChartCellCollectionBase &);
ChartRuleLookupManager*
CreateRuleLookupManager(const ChartParser &, const ChartCellCollectionBase &,
std::size_t);
#endif
void add(std::string const& s1, std::string const& s2, std::string const& a);
// add a new sentence pair to the dynamic bitext
void setWeights(std::vector<float> const& w);
void Release(ttasksptr const& ttask, TargetPhraseCollection*& tpc) const;
// some consumer lets me know that *tpc isn't needed any more
bool ProvidesPrefixCheck() const; // return true if prefix /phrase/ check exists
// bool PrefixExists(Phrase const& phrase, SamplingBias const* const bias) const;
bool PrefixExists(ttasksptr const& ttask, Phrase const& phrase) const;
bool isLogVal(int i) const;
bool isInteger(int i) const;
// task setup and takedown functions
void InitializeForInput(ttasksptr const& ttask);
// void CleanUpAfterSentenceProcessing(const InputType& source);
void CleanUpAfterSentenceProcessing(ttasksptr const& ttask);
// align two new sentences
sptr<std::vector<int> >
align(std::string const& src, std::string const& trg) const;
std::vector<std::string> const&
GetFeatureNames() const;
sptr<DocumentBias>
setupDocumentBias(std::map<std::string,float> const& bias) const;
vector<float> DefaultWeights() const;
};
} // end namespace
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