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-rw-r--r--gi/pf/base_measures.h247
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diff --git a/gi/pf/base_measures.h b/gi/pf/base_measures.h
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--- a/gi/pf/base_measures.h
+++ /dev/null
@@ -1,247 +0,0 @@
-#ifndef _BASE_MEASURES_H_
-#define _BASE_MEASURES_H_
-
-#include <vector>
-#include <map>
-#include <string>
-#include <cmath>
-#include <iostream>
-
-#include "unigrams.h"
-#include "trule.h"
-#include "prob.h"
-#include "tdict.h"
-#include "sampler.h"
-
-inline double log_poisson(unsigned x, const double& lambda) {
- assert(lambda > 0.0);
- return log(lambda) * x - lgamma(x + 1) - lambda;
-}
-
-inline std::ostream& operator<<(std::ostream& os, const std::vector<WordID>& p) {
- os << '[';
- for (int i = 0; i < p.size(); ++i)
- os << (i==0 ? "" : " ") << TD::Convert(p[i]);
- return os << ']';
-}
-
-struct Model1 {
- explicit Model1(const std::string& fname) :
- kNULL(TD::Convert("<eps>")),
- kZERO() {
- LoadModel1(fname);
- }
-
- void LoadModel1(const std::string& fname);
-
- // returns prob 0 if src or trg is not found
- const prob_t& operator()(WordID src, WordID trg) const {
- if (src == 0) src = kNULL;
- if (src < ttable.size()) {
- const std::map<WordID, prob_t>& cpd = ttable[src];
- const std::map<WordID, prob_t>::const_iterator it = cpd.find(trg);
- if (it != cpd.end())
- return it->second;
- }
- return kZERO;
- }
-
- const WordID kNULL;
- const prob_t kZERO;
- std::vector<std::map<WordID, prob_t> > ttable;
-};
-
-struct PoissonUniformUninformativeBase {
- explicit PoissonUniformUninformativeBase(const unsigned ves) : kUNIFORM(1.0 / ves) {}
- prob_t operator()(const TRule& r) const {
- prob_t p; p.logeq(log_poisson(r.e_.size(), 1.0));
- prob_t q = kUNIFORM; q.poweq(r.e_.size());
- p *= q;
- return p;
- }
- void Summary() const {}
- void ResampleHyperparameters(MT19937*) {}
- void Increment(const TRule&) {}
- void Decrement(const TRule&) {}
- prob_t Likelihood() const { return prob_t::One(); }
- const prob_t kUNIFORM;
-};
-
-struct CompletelyUniformBase {
- explicit CompletelyUniformBase(const unsigned ves) : kUNIFORM(1.0 / ves) {}
- prob_t operator()(const TRule&) const {
- return kUNIFORM;
- }
- void Summary() const {}
- void ResampleHyperparameters(MT19937*) {}
- void Increment(const TRule&) {}
- void Decrement(const TRule&) {}
- prob_t Likelihood() const { return prob_t::One(); }
- const prob_t kUNIFORM;
-};
-
-struct UnigramWordBase {
- explicit UnigramWordBase(const std::string& fname) : un(fname) {}
- prob_t operator()(const TRule& r) const {
- return un(r.e_);
- }
- const UnigramWordModel un;
-};
-
-struct RuleHasher {
- size_t operator()(const TRule& r) const {
- return hash_value(r);
- }
-};
-
-struct TableLookupBase {
- TableLookupBase(const std::string& fname);
-
- prob_t operator()(const TRule& rule) const {
- const std::tr1::unordered_map<TRule,prob_t>::const_iterator it = table.find(rule);
- if (it == table.end()) {
- std::cerr << rule << " not found\n";
- abort();
- }
- return it->second;
- }
-
- void ResampleHyperparameters(MT19937*) {}
- void Increment(const TRule&) {}
- void Decrement(const TRule&) {}
- prob_t Likelihood() const { return prob_t::One(); }
- void Summary() const {}
-
- std::tr1::unordered_map<TRule,prob_t,RuleHasher> table;
-};
-
-struct PhraseConditionalUninformativeBase {
- explicit PhraseConditionalUninformativeBase(const unsigned vocab_e_size) :
- kUNIFORM_TARGET(1.0 / vocab_e_size) {
- assert(vocab_e_size > 0);
- }
-
- // return p0 of rule.e_ | rule.f_
- prob_t operator()(const TRule& rule) const {
- return p0(rule.f_, rule.e_, 0, 0);
- }
-
- prob_t p0(const std::vector<WordID>& vsrc, const std::vector<WordID>& vtrg, int start_src, int start_trg) const;
-
- void Summary() const {}
- void ResampleHyperparameters(MT19937*) {}
- void Increment(const TRule&) {}
- void Decrement(const TRule&) {}
- prob_t Likelihood() const { return prob_t::One(); }
- const prob_t kUNIFORM_TARGET;
-};
-
-struct PhraseConditionalUninformativeUnigramBase {
- explicit PhraseConditionalUninformativeUnigramBase(const std::string& file, const unsigned vocab_e_size) : u(file, vocab_e_size) {}
-
- // return p0 of rule.e_ | rule.f_
- prob_t operator()(const TRule& rule) const {
- return p0(rule.f_, rule.e_, 0, 0);
- }
-
- prob_t p0(const std::vector<WordID>& vsrc, const std::vector<WordID>& vtrg, int start_src, int start_trg) const;
-
- const UnigramModel u;
-};
-
-struct PhraseConditionalBase {
- explicit PhraseConditionalBase(const Model1& m1, const double m1mixture, const unsigned vocab_e_size) :
- model1(m1),
- kM1MIXTURE(m1mixture),
- kUNIFORM_MIXTURE(1.0 - m1mixture),
- kUNIFORM_TARGET(1.0 / vocab_e_size) {
- assert(m1mixture >= 0.0 && m1mixture <= 1.0);
- assert(vocab_e_size > 0);
- }
-
- // return p0 of rule.e_ | rule.f_
- prob_t operator()(const TRule& rule) const {
- return p0(rule.f_, rule.e_, 0, 0);
- }
-
- prob_t p0(const std::vector<WordID>& vsrc, const std::vector<WordID>& vtrg, int start_src, int start_trg) const;
-
- const Model1& model1;
- const prob_t kM1MIXTURE; // Model 1 mixture component
- const prob_t kUNIFORM_MIXTURE; // uniform mixture component
- const prob_t kUNIFORM_TARGET;
-};
-
-struct PhraseJointBase {
- explicit PhraseJointBase(const Model1& m1, const double m1mixture, const unsigned vocab_e_size, const unsigned vocab_f_size) :
- model1(m1),
- kM1MIXTURE(m1mixture),
- kUNIFORM_MIXTURE(1.0 - m1mixture),
- kUNIFORM_SOURCE(1.0 / vocab_f_size),
- kUNIFORM_TARGET(1.0 / vocab_e_size) {
- assert(m1mixture >= 0.0 && m1mixture <= 1.0);
- assert(vocab_e_size > 0);
- }
-
- // return p0 of rule.e_ , rule.f_
- prob_t operator()(const TRule& rule) const {
- return p0(rule.f_, rule.e_, 0, 0);
- }
-
- prob_t p0(const std::vector<WordID>& vsrc, const std::vector<WordID>& vtrg, int start_src, int start_trg) const;
-
- const Model1& model1;
- const prob_t kM1MIXTURE; // Model 1 mixture component
- const prob_t kUNIFORM_MIXTURE; // uniform mixture component
- const prob_t kUNIFORM_SOURCE;
- const prob_t kUNIFORM_TARGET;
-};
-
-struct PhraseJointBase_BiDir {
- explicit PhraseJointBase_BiDir(const Model1& m1,
- const Model1& im1,
- const double m1mixture,
- const unsigned vocab_e_size,
- const unsigned vocab_f_size) :
- model1(m1),
- invmodel1(im1),
- kM1MIXTURE(m1mixture),
- kUNIFORM_MIXTURE(1.0 - m1mixture),
- kUNIFORM_SOURCE(1.0 / vocab_f_size),
- kUNIFORM_TARGET(1.0 / vocab_e_size) {
- assert(m1mixture >= 0.0 && m1mixture <= 1.0);
- assert(vocab_e_size > 0);
- }
-
- // return p0 of rule.e_ , rule.f_
- prob_t operator()(const TRule& rule) const {
- return p0(rule.f_, rule.e_, 0, 0);
- }
-
- prob_t p0(const std::vector<WordID>& vsrc, const std::vector<WordID>& vtrg, int start_src, int start_trg) const;
-
- const Model1& model1;
- const Model1& invmodel1;
- const prob_t kM1MIXTURE; // Model 1 mixture component
- const prob_t kUNIFORM_MIXTURE; // uniform mixture component
- const prob_t kUNIFORM_SOURCE;
- const prob_t kUNIFORM_TARGET;
-};
-
-// base distribution for jump size multinomials
-// basically p(0) = 0 and then, p(1) is max, and then
-// you drop as you move to the max jump distance
-struct JumpBase {
- JumpBase();
-
- const prob_t& operator()(int jump, unsigned src_len) const {
- assert(jump != 0);
- const std::map<int, prob_t>::const_iterator it = p[src_len].find(jump);
- assert(it != p[src_len].end());
- return it->second;
- }
- std::vector<std::map<int, prob_t> > p;
-};
-
-
-#endif
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