mosesdecoder/moses/FF/LexicalReordering/SparseReordering.h
2015-02-15 16:34:54 +00:00

134 lines
5.2 KiB
C++

#ifndef moses_FF_LexicalReordering_SparseReordering_h
#define moses_FF_LexicalReordering_SparseReordering_h
/**
* Sparse reordering features for phrase-based MT, following Cherry (NAACL, 2013)
**/
#include <functional>
#include <map>
#include <string>
#include <vector>
#include <boost/unordered_set.hpp>
#include "util/murmur_hash.hh"
#include "util/pool.hh"
#include "util/string_piece.hh"
#include "moses/FeatureVector.h"
#include "moses/ScoreComponentCollection.h"
#include "LexicalReorderingState.h"
/**
Configuration of sparse reordering:
The sparse reordering feature is configured using sparse-* configs in the lexical reordering line.
sparse-words-(source|target)-<id>=<filename> -- Features which fire for the words in the list
sparse-clusters-(source|target)-<id>=<filename> -- Features which fire for clusters in the list. Format
of cluster file TBD
sparse-phrase -- Add features which depend on the current phrase (backward)
sparse-stack -- Add features which depend on the previous phrase, or
top of stack. (forward)
sparse-between -- Add features which depend on words between previous phrase
(or top of stack) and current phrase.
**/
namespace Moses
{
/**
* Used to store pre-calculated feature names.
**/
struct SparseReorderingFeatureKey {
size_t id;
enum Type {Stack, Phrase, Between} type;
const Factor* word;
bool isCluster;
enum Position {First, Last} position;
enum Side {Source, Target} side;
LRState::ReorderingType reoType;
SparseReorderingFeatureKey(size_t id_, Type type_, const Factor* word_, bool isCluster_,
Position position_, Side side_, LRState::ReorderingType reoType_)
: id(id_), type(type_), word(word_), isCluster(isCluster_),
position(position_), side(side_), reoType(reoType_) {
}
const std::string& Name(const std::string& wordListId) ;
};
struct HashSparseReorderingFeatureKey : public std::unary_function<SparseReorderingFeatureKey, std::size_t> {
std::size_t operator()(const SparseReorderingFeatureKey& key) const {
//TODO: can we just hash the memory?
//not sure, there could be random padding
std::size_t seed = 0;
seed = util::MurmurHashNative(&key.id, sizeof(key.id), seed);
seed = util::MurmurHashNative(&key.type, sizeof(key.type), seed);
seed = util::MurmurHashNative(&key.word, sizeof(key.word), seed);
seed = util::MurmurHashNative(&key.isCluster, sizeof(key.isCluster), seed);
seed = util::MurmurHashNative(&key.position, sizeof(key.position), seed);
seed = util::MurmurHashNative(&key.side, sizeof(key.side), seed);
seed = util::MurmurHashNative(&key.reoType, sizeof(key.reoType), seed);
return seed;
}
};
struct EqualsSparseReorderingFeatureKey :
public std::binary_function<SparseReorderingFeatureKey, SparseReorderingFeatureKey, bool> {
bool operator()(const SparseReorderingFeatureKey& left, const SparseReorderingFeatureKey& right) const {
//TODO: Can we just compare the memory?
return left.id == right.id && left.type == right.type && left.word == right.word &&
left.position == right.position && left.side == right.side &&
left.reoType == right.reoType;
}
};
class SparseReordering
{
public:
SparseReordering(const std::map<std::string,std::string>& config, const LexicalReordering* producer);
//If direction is backward the options will be different, for forward they will be the same
void CopyScores(const TranslationOption& currentOpt,
const TranslationOption* previousOpt,
const InputType& input,
LRState::ReorderingType reoType,
LRModel::Direction direction,
ScoreComponentCollection* scores) const ;
private:
const LexicalReordering* m_producer;
typedef std::pair<std::string, boost::unordered_set<const Factor*> > WordList; //id and list
std::vector<WordList> m_sourceWordLists;
std::vector<WordList> m_targetWordLists;
typedef std::pair<std::string, boost::unordered_map<const Factor*, const Factor*> > ClusterMap; //id and map
std::vector<ClusterMap> m_sourceClusterMaps;
std::vector<ClusterMap> m_targetClusterMaps;
bool m_usePhrase;
bool m_useBetween;
bool m_useStack;
typedef boost::unordered_map<SparseReorderingFeatureKey, FName, HashSparseReorderingFeatureKey, EqualsSparseReorderingFeatureKey> FeatureMap;
FeatureMap m_featureMap;
void ReadWordList(const std::string& filename, const std::string& id,
SparseReorderingFeatureKey::Side side, std::vector<WordList>* pWordLists);
void ReadClusterMap(const std::string& filename, const std::string& id, SparseReorderingFeatureKey::Side side, std::vector<ClusterMap>* pClusterMaps);
void PreCalculateFeatureNames(size_t index, const std::string& id, SparseReorderingFeatureKey::Side side, const Factor* factor, bool isCluster);
void AddFeatures(
SparseReorderingFeatureKey::Type type, SparseReorderingFeatureKey::Side side,
const Word& word, SparseReorderingFeatureKey::Position position,
LRState::ReorderingType reoType,
ScoreComponentCollection* scores) const;
};
} //namespace
#endif