From 7fd9fe26f00cf31a7b407364399d37b4eaf04eba Mon Sep 17 00:00:00 2001 From: Chris Dyer Date: Wed, 7 Mar 2012 20:25:53 -0500 Subject: lattice builder --- gi/pf/align-tl.cc | 334 ++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 334 insertions(+) create mode 100644 gi/pf/align-tl.cc (limited to 'gi/pf/align-tl.cc') diff --git a/gi/pf/align-tl.cc b/gi/pf/align-tl.cc new file mode 100644 index 00000000..0e0454e5 --- /dev/null +++ b/gi/pf/align-tl.cc @@ -0,0 +1,334 @@ +#include +#include +#include + +#include +#include +#include + +#include "array2d.h" +#include "base_distributions.h" +#include "monotonic_pseg.h" +#include "conditional_pseg.h" +#include "trule.h" +#include "tdict.h" +#include "stringlib.h" +#include "filelib.h" +#include "dict.h" +#include "sampler.h" +#include "mfcr.h" +#include "corpus.h" +#include "ngram_base.h" +#include "transliterations.h" + +using namespace std; +using namespace tr1; +namespace po = boost::program_options; + +void InitCommandLine(int argc, char** argv, po::variables_map* conf) { + po::options_description opts("Configuration options"); + opts.add_options() + ("samples,s",po::value()->default_value(1000),"Number of samples") + ("input,i",po::value(),"Read parallel data from") + ("random_seed,S",po::value(), "Random seed"); + po::options_description clo("Command line options"); + clo.add_options() + ("config", po::value(), "Configuration file") + ("help,h", "Print this help message and exit"); + po::options_description dconfig_options, dcmdline_options; + dconfig_options.add(opts); + dcmdline_options.add(opts).add(clo); + + po::store(parse_command_line(argc, argv, dcmdline_options), *conf); + if (conf->count("config")) { + ifstream config((*conf)["config"].as().c_str()); + po::store(po::parse_config_file(config, dconfig_options), *conf); + } + po::notify(*conf); + + if (conf->count("help") || (conf->count("input") == 0)) { + cerr << dcmdline_options << endl; + exit(1); + } +} + +shared_ptr prng; + +struct LexicalAlignment { + unsigned char src_index; + bool is_transliteration; + vector > derivation; +}; + +struct AlignedSentencePair { + vector src; + vector trg; + vector a; + Array2D posterior; +}; + +struct HierarchicalWordBase { + explicit HierarchicalWordBase(const unsigned vocab_e_size) : + base(prob_t::One()), r(1,1,1,1,0.66,50.0), u0(-log(vocab_e_size)), l(1,prob_t::One()), v(1, prob_t::Zero()) {} + + void ResampleHyperparameters(MT19937* rng) { + r.resample_hyperparameters(rng); + } + + inline double logp0(const vector& s) const { + return Md::log_poisson(s.size(), 7.5) + s.size() * u0; + } + + // return p0 of rule.e_ + prob_t operator()(const TRule& rule) const { + v[0].logeq(logp0(rule.e_)); + return r.prob(rule.e_, v.begin(), l.begin()); + } + + void Increment(const TRule& rule) { + v[0].logeq(logp0(rule.e_)); + if (r.increment(rule.e_, v.begin(), l.begin(), &*prng).count) { + base *= v[0] * l[0]; + } + } + + void Decrement(const TRule& rule) { + if (r.decrement(rule.e_, &*prng).count) { + base /= prob_t(exp(logp0(rule.e_))); + } + } + + prob_t Likelihood() const { + prob_t p; p.logeq(r.log_crp_prob()); + p *= base; + return p; + } + + void Summary() const { + cerr << "NUMBER OF CUSTOMERS: " << r.num_customers() << " (d=" << r.discount() << ",s=" << r.strength() << ')' << endl; + for (MFCR<1,vector >::const_iterator it = r.begin(); it != r.end(); ++it) + cerr << " " << it->second.total_dish_count_ << " (on " << it->second.table_counts_.size() << " tables) " << TD::GetString(it->first) << endl; + } + + prob_t base; + MFCR<1,vector > r; + const double u0; + const vector l; + mutable vector v; +}; + +struct BasicLexicalAlignment { + explicit BasicLexicalAlignment(const vector >& lets, + const unsigned words_e, + const unsigned letters_e, + vector* corp) : + letters(lets), + corpus(*corp), + //up0(words_e), + //up0("en.chars.1gram", letters_e), + //up0("en.words.1gram"), + up0(letters_e), + //up0("en.chars.2gram"), + tmodel(up0) { + } + + void InstantiateRule(const WordID src, + const WordID trg, + TRule* rule) const { + static const WordID kX = TD::Convert("X") * -1; + rule->lhs_ = kX; + rule->e_ = letters[trg]; + rule->f_ = letters[src]; + } + + void InitializeRandom() { + const WordID kNULL = TD::Convert("NULL"); + cerr << "Initializing with random alignments ...\n"; + for (unsigned i = 0; i < corpus.size(); ++i) { + AlignedSentencePair& asp = corpus[i]; + asp.a.resize(asp.trg.size()); + for (unsigned j = 0; j < asp.trg.size(); ++j) { + const unsigned char a_j = prng->next() * (1 + asp.src.size()); + const WordID f_a_j = (a_j ? asp.src[a_j - 1] : kNULL); + TRule r; + InstantiateRule(f_a_j, asp.trg[j], &r); + asp.a[j].is_transliteration = false; + asp.a[j].src_index = a_j; + if (tmodel.IncrementRule(r, &*prng)) + up0.Increment(r); + } + } + cerr << " LLH = " << Likelihood() << endl; + } + + prob_t Likelihood() const { + prob_t p = tmodel.Likelihood(); + p *= up0.Likelihood(); + return p; + } + + void ResampleHyperparemeters() { + tmodel.ResampleHyperparameters(&*prng); + up0.ResampleHyperparameters(&*prng); + cerr << " (base d=" << up0.r.discount() << ",s=" << up0.r.strength() << ")\n"; + } + + void ResampleCorpus(); + + const vector >& letters; // spelling dictionary + vector& corpus; + //PhraseConditionalUninformativeBase up0; + //PhraseConditionalUninformativeUnigramBase up0; + //UnigramWordBase up0; + //HierarchicalUnigramBase up0; + HierarchicalWordBase up0; + //CompletelyUniformBase up0; + //FixedNgramBase up0; + //ConditionalTranslationModel tmodel; + //ConditionalTranslationModel tmodel; + //ConditionalTranslationModel tmodel; + //ConditionalTranslationModel tmodel; + MConditionalTranslationModel tmodel; + //ConditionalTranslationModel tmodel; + //ConditionalTranslationModel tmodel; +}; + +void BasicLexicalAlignment::ResampleCorpus() { + static const WordID kNULL = TD::Convert("NULL"); + for (unsigned i = 0; i < corpus.size(); ++i) { + AlignedSentencePair& asp = corpus[i]; + SampleSet ss; ss.resize(asp.src.size() + 1); + for (unsigned j = 0; j < asp.trg.size(); ++j) { + TRule r; + unsigned char& a_j = asp.a[j].src_index; + WordID f_a_j = (a_j ? asp.src[a_j - 1] : kNULL); + InstantiateRule(f_a_j, asp.trg[j], &r); + if (tmodel.DecrementRule(r, &*prng)) + up0.Decrement(r); + + for (unsigned prop_a_j = 0; prop_a_j <= asp.src.size(); ++prop_a_j) { + const WordID prop_f = (prop_a_j ? asp.src[prop_a_j - 1] : kNULL); + InstantiateRule(prop_f, asp.trg[j], &r); + ss[prop_a_j] = tmodel.RuleProbability(r); + } + a_j = prng->SelectSample(ss); + f_a_j = (a_j ? asp.src[a_j - 1] : kNULL); + InstantiateRule(f_a_j, asp.trg[j], &r); + if (tmodel.IncrementRule(r, &*prng)) + up0.Increment(r); + } + } + cerr << " LLH = " << Likelihood() << endl; +} + +void ExtractLetters(const set& v, vector >* l, set* letset = NULL) { + for (set::const_iterator it = v.begin(); it != v.end(); ++it) { + vector& letters = (*l)[*it]; + if (letters.size()) continue; // if e and f have the same word + + const string& w = TD::Convert(*it); + + size_t cur = 0; + while (cur < w.size()) { + const size_t len = UTF8Len(w[cur]); + letters.push_back(TD::Convert(w.substr(cur, len))); + if (letset) letset->insert(letters.back()); + cur += len; + } + } +} + +void Debug(const AlignedSentencePair& asp) { + cerr << TD::GetString(asp.src) << endl << TD::GetString(asp.trg) << endl; + Array2D a(asp.src.size(), asp.trg.size()); + for (unsigned j = 0; j < asp.trg.size(); ++j) + if (asp.a[j].src_index) a(asp.a[j].src_index - 1, j) = true; + cerr << a << endl; +} + +void AddSample(AlignedSentencePair* asp) { + for (unsigned j = 0; j < asp->trg.size(); ++j) + asp->posterior(asp->a[j].src_index, j)++; +} + +void WriteAlignments(const AlignedSentencePair& asp) { + bool first = true; + for (unsigned j = 0; j < asp.trg.size(); ++j) { + int src_index = -1; + int mc = -1; + for (unsigned i = 0; i <= asp.src.size(); ++i) { + if (asp.posterior(i, j) > mc) { + mc = asp.posterior(i, j); + src_index = i; + } + } + + if (src_index) { + if (first) first = false; else cout << ' '; + cout << (src_index - 1) << '-' << j; + } + } + cout << endl; +} + +int main(int argc, char** argv) { + po::variables_map conf; + InitCommandLine(argc, argv, &conf); + + if (conf.count("random_seed")) + prng.reset(new MT19937(conf["random_seed"].as())); + else + prng.reset(new MT19937); +// MT19937& rng = *prng; + + vector > corpuse, corpusf; + set vocabe, vocabf; + corpus::ReadParallelCorpus(conf["input"].as(), &corpusf, &corpuse, &vocabf, &vocabe); + cerr << "f-Corpus size: " << corpusf.size() << " sentences\n"; + cerr << "f-Vocabulary size: " << vocabf.size() << " types\n"; + cerr << "f-Corpus size: " << corpuse.size() << " sentences\n"; + cerr << "f-Vocabulary size: " << vocabe.size() << " types\n"; + assert(corpusf.size() == corpuse.size()); + + vector corpus(corpuse.size()); + for (unsigned i = 0; i < corpuse.size(); ++i) { + corpus[i].src.swap(corpusf[i]); + corpus[i].trg.swap(corpuse[i]); + corpus[i].posterior.resize(corpus[i].src.size() + 1, corpus[i].trg.size()); + } + corpusf.clear(); corpuse.clear(); + + vocabf.insert(TD::Convert("NULL")); + vector > letters(TD::NumWords()); + set letset; + ExtractLetters(vocabe, &letters, &letset); + ExtractLetters(vocabf, &letters, NULL); + letters[TD::Convert("NULL")].clear(); + + Transliterations tl; + + // TODO CONFIGURE THIS + int min_trans_src = 4; + + cerr << "Initializing transliteration DPs ...\n"; + for (int i = 0; i < corpus.size(); ++i) { + const vector& src = corpus[i].src; + const vector& trg = corpus[i].trg; + cerr << '.' << flush; + if (i % 80 == 79) cerr << endl; + for (int j = 0; j < src.size(); ++j) { + const vector& src_let = letters[src[j]]; + for (int k = 0; k < trg.size(); ++k) { + const vector& trg_let = letters[trg[k]]; + if (src_let.size() < min_trans_src) + tl.Forbid(src[j], trg[k]); + else + tl.Initialize(src[j], src_let, trg[k], trg_let); + } + } + } + cerr << endl; + tl.GraphSummary(); + + return 0; +} -- cgit v1.2.3