From f91319978f6e74e5c4e5701da8fbbacb96a3161e Mon Sep 17 00:00:00 2001 From: Chris Dyer Date: Tue, 5 Jul 2011 23:19:43 -0400 Subject: fast phrasinator that uses DPs instead of PYPs --- phrasinator/Makefile.am | 8 +- phrasinator/ccrp_nt.h | 154 +++++++++++++++ phrasinator/gibbs_train_plm.notables.cc | 335 ++++++++++++++++++++++++++++++++ phrasinator/train-phrasinator.pl | 2 +- 4 files changed, 497 insertions(+), 2 deletions(-) create mode 100644 phrasinator/ccrp_nt.h create mode 100644 phrasinator/gibbs_train_plm.notables.cc (limited to 'phrasinator') diff --git a/phrasinator/Makefile.am b/phrasinator/Makefile.am index 0b15a250..95a603df 100644 --- a/phrasinator/Makefile.am +++ b/phrasinator/Makefile.am @@ -1,6 +1,12 @@ -bin_PROGRAMS = gibbs_train_plm +bin_PROGRAMS = gibbs_train_plm head_bigram_model gibbs_train_plm_notables + +gibbs_train_plm_notables_SOURCES = gibbs_train_plm.notables.cc +gibbs_train_plm_notables_LDADD = $(top_srcdir)/utils/libutils.a -lz gibbs_train_plm_SOURCES = gibbs_train_plm.cc gibbs_train_plm_LDADD = $(top_srcdir)/utils/libutils.a -lz +head_bigram_model_SOURCES = head_bigram_model.cc +head_bigram_model_LDADD = $(top_srcdir)/utils/libutils.a -lz + AM_CPPFLAGS = -funroll-loops -W -Wall -Wno-sign-compare $(GTEST_CPPFLAGS) -I$(top_srcdir)/utils -I$(top_srcdir)/decoder -I$(top_srcdir)/mteval diff --git a/phrasinator/ccrp_nt.h b/phrasinator/ccrp_nt.h new file mode 100644 index 00000000..163b643a --- /dev/null +++ b/phrasinator/ccrp_nt.h @@ -0,0 +1,154 @@ +#ifndef _CCRP_NT_H_ +#define _CCRP_NT_H_ + +#include +#include +#include +#include +#include +#include +#include +#include +#include "sampler.h" +#include "slice_sampler.h" + +// Chinese restaurant process (Pitman-Yor parameters) with table tracking. + +template > +class CCRP_NoTable { + public: + explicit CCRP_NoTable(double conc) : + num_customers_(), + concentration_(conc), + concentration_prior_shape_(std::numeric_limits::quiet_NaN()), + concentration_prior_rate_(std::numeric_limits::quiet_NaN()) {} + + CCRP_NoTable(double c_shape, double c_rate, double c = 10.0) : + num_customers_(), + concentration_(c), + concentration_prior_shape_(c_shape), + concentration_prior_rate_(c_rate) {} + + double concentration() const { return concentration_; } + + bool has_concentration_prior() const { + return !std::isnan(concentration_prior_shape_); + } + + void clear() { + num_customers_ = 0; + custs_.clear(); + } + + unsigned num_customers() const { + return num_customers_; + } + + unsigned num_customers(const Dish& dish) const { + const typename std::tr1::unordered_map::const_iterator it = custs_.find(dish); + if (it == custs_.end()) return 0; + return it->second; + } + + void increment(const Dish& dish) { + ++custs_[dish]; + ++num_customers_; + } + + void decrement(const Dish& dish) { + if ((--custs_[dish]) == 0) + custs_.erase(dish); + --num_customers_; + } + + double prob(const Dish& dish, const double& p0) const { + const unsigned at_table = num_customers(dish); + return (at_table + p0 * concentration_) / (num_customers_ + concentration_); + } + + double log_crp_prob() const { + return log_crp_prob(concentration_); + } + + static double log_gamma_density(const double& x, const double& shape, const double& rate) { + assert(x >= 0.0); + assert(shape > 0.0); + assert(rate > 0.0); + const double lp = (shape-1)*log(x) - shape*log(rate) - x/rate - lgamma(shape); + return lp; + } + + // taken from http://en.wikipedia.org/wiki/Chinese_restaurant_process + // does not include P_0's + double log_crp_prob(const double& concentration) const { + double lp = 0.0; + if (has_concentration_prior()) + lp += log_gamma_density(concentration, concentration_prior_shape_, concentration_prior_rate_); + assert(lp <= 0.0); + if (num_customers_) { + lp += lgamma(concentration) - lgamma(concentration + num_customers_) + + custs_.size() * log(concentration); + assert(std::isfinite(lp)); + for (typename std::tr1::unordered_map::const_iterator it = custs_.begin(); + it != custs_.end(); ++it) { + lp += lgamma(it->second); + } + } + assert(std::isfinite(lp)); + return lp; + } + + void resample_hyperparameters(MT19937* rng, const unsigned nloop = 5, const unsigned niterations = 10) { + assert(has_concentration_prior()); + ConcentrationResampler cr(*this); + for (int iter = 0; iter < nloop; ++iter) { + concentration_ = slice_sampler1d(cr, concentration_, *rng, 0.0, + std::numeric_limits::infinity(), 0.0, niterations, 100*niterations); + } + } + + struct ConcentrationResampler { + ConcentrationResampler(const CCRP_NoTable& crp) : crp_(crp) {} + const CCRP_NoTable& crp_; + double operator()(const double& proposed_concentration) const { + return crp_.log_crp_prob(proposed_concentration); + } + }; + + void Print(std::ostream* out) const { + (*out) << "DP(alpha=" << concentration_ << ") customers=" << num_customers_ << std::endl; + int cc = 0; + for (typename std::tr1::unordered_map::const_iterator it = custs_.begin(); + it != custs_.end(); ++it) { + (*out) << " " << it->first << "(" << it->second << " eating)"; + ++cc; + if (cc > 10) { (*out) << " ..."; break; } + } + (*out) << std::endl; + } + + unsigned num_customers_; + std::tr1::unordered_map custs_; + + typedef typename std::tr1::unordered_map::const_iterator const_iterator; + const_iterator begin() const { + return custs_.begin(); + } + const_iterator end() const { + return custs_.end(); + } + + double concentration_; + + // optional gamma prior on concentration_ (NaN if no prior) + double concentration_prior_shape_; + double concentration_prior_rate_; +}; + +template +std::ostream& operator<<(std::ostream& o, const CCRP_NoTable& c) { + c.Print(&o); + return o; +} + +#endif diff --git a/phrasinator/gibbs_train_plm.notables.cc b/phrasinator/gibbs_train_plm.notables.cc new file mode 100644 index 00000000..4b431b90 --- /dev/null +++ b/phrasinator/gibbs_train_plm.notables.cc @@ -0,0 +1,335 @@ +#include +#include + +#include +#include + +#include "filelib.h" +#include "dict.h" +#include "sampler.h" +#include "ccrp.h" +#include "ccrp_nt.h" + +using namespace std; +using namespace std::tr1; +namespace po = boost::program_options; + +Dict d; // global dictionary + +string Join(char joiner, const vector& phrase) { + ostringstream os; + for (int i = 0; i < phrase.size(); ++i) { + if (i > 0) os << joiner; + os << d.Convert(phrase[i]); + } + return os.str(); +} + +template +void WriteSeg(const vector& line, const vector& label, const Dict& d) { + assert(line.size() == label.size()); + assert(label.back()); + int prev = 0; + int cur = 0; + while (cur < line.size()) { + if (label[cur]) { + if (prev) cout << ' '; + cout << "{{"; + for (int i = prev; i <= cur; ++i) + cout << (i == prev ? "" : " ") << d.Convert(line[i]); + cout << "}}:" << label[cur]; + prev = cur + 1; + } + ++cur; + } + cout << endl; +} + +ostream& operator<<(ostream& os, const vector& phrase) { + for (int i = 0; i < phrase.size(); ++i) + os << (i == 0 ? "" : " ") << d.Convert(phrase[i]); + return os; +} + +struct UnigramLM { + explicit UnigramLM(const string& fname) { + ifstream in(fname.c_str()); + assert(in); + } + + double logprob(int word) const { + assert(word < freqs_.size()); + return freqs_[word]; + } + + vector freqs_; +}; + +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 file from") + ("random_seed,S",po::value(), "Random seed") + ("write_cdec_grammar,g", po::value(), "Write cdec grammar to this file") + ("write_cdec_weights,w", po::value(), "Write cdec weights to this file") + ("poisson_length,p", "Use a Poisson distribution as the length of a phrase in the base distribuion") + ("no_hyperparameter_inference,N", "Disable hyperparameter inference"); + 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); + } +} + +void ReadCorpus(const string& filename, vector >* c, set* vocab) { + c->clear(); + istream* in; + if (filename == "-") + in = &cin; + else + in = new ifstream(filename.c_str()); + assert(*in); + string line; + while(*in) { + getline(*in, line); + if (line.empty() && !*in) break; + c->push_back(vector()); + vector& v = c->back(); + d.ConvertWhitespaceDelimitedLine(line, &v); + for (int i = 0; i < v.size(); ++i) vocab->insert(v[i]); + } + if (in != &cin) delete in; +} + +double log_poisson(unsigned x, const double& lambda) { + assert(lambda > 0.0); + return log(lambda) * x - lgamma(x + 1) - lambda; +} + +struct UniphraseLM { + UniphraseLM(const vector >& corpus, + const set& vocab, + const po::variables_map& conf) : + phrases_(1,1), + gen_(1,1), + corpus_(corpus), + uniform_word_(1.0 / vocab.size()), + gen_p0_(0.5), + p_end_(0.5), + use_poisson_(conf.count("poisson_length") > 0) {} + + double p0(const vector& phrase) const { + static vector p0s(10000, 0.0); + assert(phrase.size() < 10000); + double& p = p0s[phrase.size()]; + if (p) return p; + p = exp(log_p0(phrase)); + if (!p) { + cerr << "0 prob phrase: " << phrase << "\nAssigning std::numeric_limits::min()\n"; + p = std::numeric_limits::min(); + } + return p; + } + + double log_p0(const vector& phrase) const { + double len_logprob; + if (use_poisson_) + len_logprob = log_poisson(phrase.size(), 1.0); + else + len_logprob = log(1 - p_end_) * (phrase.size() -1) + log(p_end_); + return log(uniform_word_) * phrase.size() + len_logprob; + } + + double llh() const { + double llh = gen_.log_crp_prob(); + llh += log(gen_p0_) + log(1 - gen_p0_); + double llhr = phrases_.log_crp_prob(); + for (CCRP_NoTable >::const_iterator it = phrases_.begin(); it != phrases_.end(); ++it) { + llhr += log_p0(it->first); + //llhr += log_p0(it->first); + if (!isfinite(llh)) { + cerr << it->first << endl; + cerr << log_p0(it->first) << endl; + abort(); + } + } + return llh + llhr; + } + + void Sample(unsigned int samples, bool hyp_inf, MT19937* rng) { + cerr << "Initializing...\n"; + z_.resize(corpus_.size()); + int tc = 0; + for (int i = 0; i < corpus_.size(); ++i) { + const vector& line = corpus_[i]; + const int ls = line.size(); + const int last_pos = ls - 1; + vector& z = z_[i]; + z.resize(ls); + int prev = 0; + for (int j = 0; j < ls; ++j) { + z[j] = rng->next() < 0.5; + if (j == last_pos) z[j] = true; // break phrase at the end of the sentence + if (z[j]) { + const vector p(line.begin() + prev, line.begin() + j + 1); + phrases_.increment(p); + //cerr << p << ": " << p0(p) << endl; + prev = j + 1; + gen_.increment(false); + ++tc; // remove + } + } + ++tc; + gen_.increment(true); // end of utterance + } + cerr << "TC: " << tc << endl; + cerr << "Initial LLH: " << llh() << endl; + cerr << "Sampling...\n"; + cerr << gen_ << endl; + for (int s = 1; s < samples; ++s) { + cerr << '.'; + if (s % 10 == 0) { + cerr << " [" << s; + if (hyp_inf) ResampleHyperparameters(rng); + cerr << " LLH=" << llh() << "]\n"; + vector z(z_[0].size(), 0); + //for (int j = 0; j < z.size(); ++j) z[j] = z_[0][j]; + //SegCorpus::Write(corpus_[0], z, d); + } + for (int i = 0; i < corpus_.size(); ++i) { + const vector& line = corpus_[i]; + const int ls = line.size(); + const int last_pos = ls - 1; + vector& z = z_[i]; + int prev = 0; + for (int j = 0; j < last_pos; ++j) { // don't resample last position + int next = j+1; while(!z[next]) { ++next; } + const vector p1p2(line.begin() + prev, line.begin() + next + 1); + const vector p1(line.begin() + prev, line.begin() + j + 1); + const vector p2(line.begin() + j + 1, line.begin() + next + 1); + + if (z[j]) { + phrases_.decrement(p1); + phrases_.decrement(p2); + gen_.decrement(false); + gen_.decrement(false); + } else { + phrases_.decrement(p1p2); + gen_.decrement(false); + } + + const double d1 = phrases_.prob(p1p2, p0(p1p2)) * gen_.prob(false, gen_p0_); + double d2 = phrases_.prob(p1, p0(p1)) * gen_.prob(false, gen_p0_); + phrases_.increment(p1); + gen_.increment(false); + d2 *= phrases_.prob(p2, p0(p2)) * gen_.prob(false, gen_p0_); + phrases_.decrement(p1); + gen_.decrement(false); + z[j] = rng->SelectSample(d1, d2); + + if (z[j]) { + phrases_.increment(p1); + phrases_.increment(p2); + gen_.increment(false); + gen_.increment(false); + prev = j + 1; + } else { + phrases_.increment(p1p2); + gen_.increment(false); + } + } + } + } +// cerr << endl << endl << gen_ << endl << phrases_ << endl; + cerr << gen_.prob(false, gen_p0_) << " " << gen_.prob(true, 1 - gen_p0_) << endl; + } + + void WriteCdecGrammarForCurrentSample(ostream* os) const { + CCRP_NoTable >::const_iterator it = phrases_.begin(); + for (; it != phrases_.end(); ++it) { + (*os) << "[X] ||| " << Join(' ', it->first) << " ||| " + << Join('_', it->first) << " ||| C=1 P=" + << log(phrases_.prob(it->first, p0(it->first))) << endl; + } + } + + double OOVUnigramLogProb() const { + vector x(1,99999999); + return log(phrases_.prob(x, p0(x))); + } + + void ResampleHyperparameters(MT19937* rng) { + phrases_.resample_hyperparameters(rng); + gen_.resample_hyperparameters(rng); + cerr << " " << phrases_.concentration(); + } + + CCRP_NoTable > phrases_; + CCRP_NoTable gen_; + vector > z_; // z_[i] is there a phrase boundary after the ith word + const vector >& corpus_; + const double uniform_word_; + const double gen_p0_; + const double p_end_; // in base length distribution, p of the end of a phrase + const bool use_poisson_; +}; + + +int main(int argc, char** argv) { + po::variables_map conf; + InitCommandLine(argc, argv, &conf); + shared_ptr prng; + if (conf.count("random_seed")) + prng.reset(new MT19937(conf["random_seed"].as())); + else + prng.reset(new MT19937); + MT19937& rng = *prng; + + vector > corpus; + set vocab; + ReadCorpus(conf["input"].as(), &corpus, &vocab); + cerr << "Corpus size: " << corpus.size() << " sentences\n"; + cerr << "Vocabulary size: " << vocab.size() << " types\n"; + + UniphraseLM ulm(corpus, vocab, conf); + ulm.Sample(conf["samples"].as(), conf.count("no_hyperparameter_inference") == 0, &rng); + cerr << "OOV unigram prob: " << ulm.OOVUnigramLogProb() << endl; + + for (int i = 0; i < corpus.size(); ++i) + WriteSeg(corpus[i], ulm.z_[i], d); + + if (conf.count("write_cdec_grammar")) { + string fname = conf["write_cdec_grammar"].as(); + cerr << "Writing model to " << fname << " ...\n"; + WriteFile wf(fname); + ulm.WriteCdecGrammarForCurrentSample(wf.stream()); + } + + if (conf.count("write_cdec_weights")) { + string fname = conf["write_cdec_weights"].as(); + cerr << "Writing weights to " << fname << " .\n"; + WriteFile wf(fname); + ostream& os = *wf.stream(); + os << "# make C smaller to use more phrases\nP 1\nPassThrough " << ulm.OOVUnigramLogProb() << "\nC -3\n"; + } + + + + return 0; +} + diff --git a/phrasinator/train-phrasinator.pl b/phrasinator/train-phrasinator.pl index de258caf..c50b8e68 100755 --- a/phrasinator/train-phrasinator.pl +++ b/phrasinator/train-phrasinator.pl @@ -5,7 +5,7 @@ use Getopt::Long; use File::Spec qw (rel2abs); my $DECODER = "$script_dir/../decoder/cdec"; -my $TRAINER = "$script_dir/gibbs_train_plm"; +my $TRAINER = "$script_dir/gibbs_train_plm_notables"; die "Can't find $TRAINER" unless -f $TRAINER; die "Can't execute $TRAINER" unless -x $TRAINER; -- cgit v1.2.3 From 164d32f02604ee5bff5de94ad669fb2b4d12d34a Mon Sep 17 00:00:00 2001 From: Chris Dyer Date: Tue, 5 Jul 2011 23:35:48 -0400 Subject: build bug --- phrasinator/Makefile.am | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) (limited to 'phrasinator') diff --git a/phrasinator/Makefile.am b/phrasinator/Makefile.am index 95a603df..aba98601 100644 --- a/phrasinator/Makefile.am +++ b/phrasinator/Makefile.am @@ -1,4 +1,6 @@ -bin_PROGRAMS = gibbs_train_plm head_bigram_model gibbs_train_plm_notables +bin_PROGRAMS = gibbs_train_plm gibbs_train_plm_notables + +#head_bigram_model gibbs_train_plm_notables_SOURCES = gibbs_train_plm.notables.cc gibbs_train_plm_notables_LDADD = $(top_srcdir)/utils/libutils.a -lz @@ -6,7 +8,7 @@ gibbs_train_plm_notables_LDADD = $(top_srcdir)/utils/libutils.a -lz gibbs_train_plm_SOURCES = gibbs_train_plm.cc gibbs_train_plm_LDADD = $(top_srcdir)/utils/libutils.a -lz -head_bigram_model_SOURCES = head_bigram_model.cc -head_bigram_model_LDADD = $(top_srcdir)/utils/libutils.a -lz +#head_bigram_model_SOURCES = head_bigram_model.cc +#head_bigram_model_LDADD = $(top_srcdir)/utils/libutils.a -lz AM_CPPFLAGS = -funroll-loops -W -Wall -Wno-sign-compare $(GTEST_CPPFLAGS) -I$(top_srcdir)/utils -I$(top_srcdir)/decoder -I$(top_srcdir)/mteval -- cgit v1.2.3 From 0af7d663194beddcde420349bbd91430e0b2e423 Mon Sep 17 00:00:00 2001 From: Guest_account Guest_account prguest11 Date: Tue, 11 Oct 2011 16:16:53 +0100 Subject: remove implicit conversion-to-double operator from LogVal that caused overflow errors, clean up some pf code --- decoder/aligner.cc | 2 +- decoder/cfg.cc | 2 +- decoder/cfg_format.h | 2 +- decoder/decoder.cc | 10 ++++---- decoder/hg.cc | 4 ++-- decoder/rule_lexer.l | 2 ++ decoder/trule.h | 15 +++++++++++- gi/pf/brat.cc | 11 --------- gi/pf/cbgi.cc | 10 -------- gi/pf/dpnaive.cc | 12 ---------- gi/pf/itg.cc | 11 --------- gi/pf/pfbrat.cc | 11 --------- gi/pf/pfdist.cc | 11 --------- gi/pf/pfnaive.cc | 11 --------- mteval/mbr_kbest.cc | 4 ++-- phrasinator/ccrp_nt.h | 24 +++++++++++++++---- training/mpi_batch_optimize.cc | 2 +- training/mpi_compute_cllh.cc | 51 +++++++++++++++++++---------------------- training/mpi_online_optimize.cc | 4 ++-- utils/logval.h | 10 ++++---- 20 files changed, 78 insertions(+), 131 deletions(-) (limited to 'phrasinator') diff --git a/decoder/aligner.cc b/decoder/aligner.cc index 292ee123..53e059fb 100644 --- a/decoder/aligner.cc +++ b/decoder/aligner.cc @@ -165,7 +165,7 @@ inline void WriteProbGrid(const Array2D& m, ostream* pos) { if (m(i,j) == prob_t::Zero()) { os << "\t---X---"; } else { - snprintf(b, 1024, "%0.5f", static_cast(m(i,j))); + snprintf(b, 1024, "%0.5f", m(i,j).as_float()); os << '\t' << b; } } diff --git a/decoder/cfg.cc b/decoder/cfg.cc index 651978d2..cd7e66e9 100755 --- a/decoder/cfg.cc +++ b/decoder/cfg.cc @@ -639,7 +639,7 @@ void CFG::Print(std::ostream &o,CFGFormat const& f) const { o << '['<& src, SparseVector* trg) { for (SparseVector::const_iterator it = src.begin(); it != src.end(); ++it) - trg->set_value(it->first, it->second); + trg->set_value(it->first, it->second.as_float()); } }; @@ -788,10 +788,10 @@ bool DecoderImpl::Decode(const string& input, DecoderObserver* o) { const bool show_tree_structure=conf.count("show_tree_structure"); if (!SILENT) forest_stats(forest," Init. forest",show_tree_structure,oracle.show_derivation); if (conf.count("show_expected_length")) { - const PRPair res = - Inside, - PRWeightFunction >(forest); - cerr << " Expected length (words): " << res.r / res.p << "\t" << res << endl; + const PRPair res = + Inside, + PRWeightFunction >(forest); + cerr << " Expected length (words): " << (res.r / res.p).as_float() << "\t" << res << endl; } if (conf.count("show_partition")) { diff --git a/decoder/hg.cc b/decoder/hg.cc index 3ad17f1a..180986d7 100644 --- a/decoder/hg.cc +++ b/decoder/hg.cc @@ -157,14 +157,14 @@ prob_t Hypergraph::ComputeEdgePosteriors(double scale, vector* posts) co const ScaledEdgeProb weight(scale); const ScaledTransitionEventWeightFunction w2(scale); SparseVector pv; - const double inside = InsideOutside, ScaledTransitionEventWeightFunction>(*this, &pv, weight, w2); posts->resize(edges_.size()); for (int i = 0; i < edges_.size(); ++i) (*posts)[i] = prob_t(pv.value(i)); - return prob_t(inside); + return inside; } prob_t Hypergraph::ComputeBestPathThroughEdges(vector* post) const { diff --git a/decoder/rule_lexer.l b/decoder/rule_lexer.l index 9331d8ed..083a5bb1 100644 --- a/decoder/rule_lexer.l +++ b/decoder/rule_lexer.l @@ -220,6 +220,8 @@ NT [^\t \[\],]+ std::cerr << "Line " << lex_line << ": LHS and RHS arity mismatch!\n"; abort(); } + // const bool ignore_grammar_features = false; + // if (ignore_grammar_features) scfglex_num_feats = 0; TRulePtr rp(new TRule(scfglex_lhs, scfglex_src_rhs, scfglex_src_rhs_size, scfglex_trg_rhs, scfglex_trg_rhs_size, scfglex_feat_ids, scfglex_feat_vals, scfglex_num_feats, scfglex_src_arity, scfglex_als, scfglex_num_als)); check_and_update_ctf_stack(rp); TRulePtr coarse_rp = ((ctf_level == 0) ? TRulePtr() : ctf_rule_stack.top()); diff --git a/decoder/trule.h b/decoder/trule.h index 4df4ec90..8eb2a059 100644 --- a/decoder/trule.h +++ b/decoder/trule.h @@ -5,7 +5,9 @@ #include #include #include -#include + +#include "boost/shared_ptr.hpp" +#include "boost/functional/hash.hpp" #include "sparse_vector.h" #include "wordid.h" @@ -162,4 +164,15 @@ class TRule { bool SanityCheck() const; }; +inline size_t hash_value(const TRule& r) { + size_t h = boost::hash_value(r.e_); + boost::hash_combine(h, -r.lhs_); + boost::hash_combine(h, boost::hash_value(r.f_)); + return h; +} + +inline bool operator==(const TRule& a, const TRule& b) { + return (a.lhs_ == b.lhs_ && a.e_ == b.e_ && a.f_ == b.f_); +} + #endif diff --git a/gi/pf/brat.cc b/gi/pf/brat.cc index 4c6ba3ef..7b60ef23 100644 --- a/gi/pf/brat.cc +++ b/gi/pf/brat.cc @@ -25,17 +25,6 @@ static unsigned kMAX_SRC_PHRASE; static unsigned kMAX_TRG_PHRASE; struct FSTState; -size_t hash_value(const TRule& r) { - size_t h = 2 - r.lhs_; - boost::hash_combine(h, boost::hash_value(r.e_)); - boost::hash_combine(h, boost::hash_value(r.f_)); - return h; -} - -bool operator==(const TRule& a, const TRule& b) { - return (a.lhs_ == b.lhs_ && a.e_ == b.e_ && a.f_ == b.f_); -} - double log_poisson(unsigned x, const double& lambda) { assert(lambda > 0.0); return log(lambda) * x - lgamma(x + 1) - lambda; diff --git a/gi/pf/cbgi.cc b/gi/pf/cbgi.cc index 20204e8a..97f1ba34 100644 --- a/gi/pf/cbgi.cc +++ b/gi/pf/cbgi.cc @@ -27,16 +27,6 @@ double log_decay(unsigned x, const double& b) { return log(b - 1) - x * log(b); } -size_t hash_value(const TRule& r) { - // TODO fix hash function - size_t h = boost::hash_value(r.e_) * boost::hash_value(r.f_) * r.lhs_; - return h; -} - -bool operator==(const TRule& a, const TRule& b) { - return (a.lhs_ == b.lhs_ && a.e_ == b.e_ && a.f_ == b.f_); -} - struct SimpleBase { SimpleBase(unsigned esize, unsigned fsize, unsigned ntsize = 144) : uniform_e(-log(esize)), diff --git a/gi/pf/dpnaive.cc b/gi/pf/dpnaive.cc index 582d1be7..608f73d5 100644 --- a/gi/pf/dpnaive.cc +++ b/gi/pf/dpnaive.cc @@ -20,18 +20,6 @@ namespace po = boost::program_options; static unsigned kMAX_SRC_PHRASE; static unsigned kMAX_TRG_PHRASE; -struct FSTState; - -size_t hash_value(const TRule& r) { - size_t h = 2 - r.lhs_; - boost::hash_combine(h, boost::hash_value(r.e_)); - boost::hash_combine(h, boost::hash_value(r.f_)); - return h; -} - -bool operator==(const TRule& a, const TRule& b) { - return (a.lhs_ == b.lhs_ && a.e_ == b.e_ && a.f_ == b.f_); -} void InitCommandLine(int argc, char** argv, po::variables_map* conf) { po::options_description opts("Configuration options"); diff --git a/gi/pf/itg.cc b/gi/pf/itg.cc index 2c2a86f9..ac3c16a3 100644 --- a/gi/pf/itg.cc +++ b/gi/pf/itg.cc @@ -27,17 +27,6 @@ ostream& operator<<(ostream& os, const vector& p) { return os << ']'; } -size_t hash_value(const TRule& r) { - size_t h = boost::hash_value(r.e_); - boost::hash_combine(h, -r.lhs_); - boost::hash_combine(h, boost::hash_value(r.f_)); - return h; -} - -bool operator==(const TRule& a, const TRule& b) { - return (a.lhs_ == b.lhs_ && a.e_ == b.e_ && a.f_ == b.f_); -} - double log_poisson(unsigned x, const double& lambda) { assert(lambda > 0.0); return log(lambda) * x - lgamma(x + 1) - lambda; diff --git a/gi/pf/pfbrat.cc b/gi/pf/pfbrat.cc index 4c6ba3ef..7b60ef23 100644 --- a/gi/pf/pfbrat.cc +++ b/gi/pf/pfbrat.cc @@ -25,17 +25,6 @@ static unsigned kMAX_SRC_PHRASE; static unsigned kMAX_TRG_PHRASE; struct FSTState; -size_t hash_value(const TRule& r) { - size_t h = 2 - r.lhs_; - boost::hash_combine(h, boost::hash_value(r.e_)); - boost::hash_combine(h, boost::hash_value(r.f_)); - return h; -} - -bool operator==(const TRule& a, const TRule& b) { - return (a.lhs_ == b.lhs_ && a.e_ == b.e_ && a.f_ == b.f_); -} - double log_poisson(unsigned x, const double& lambda) { assert(lambda > 0.0); return log(lambda) * x - lgamma(x + 1) - lambda; diff --git a/gi/pf/pfdist.cc b/gi/pf/pfdist.cc index 18dfd03b..81abd61b 100644 --- a/gi/pf/pfdist.cc +++ b/gi/pf/pfdist.cc @@ -24,17 +24,6 @@ namespace po = boost::program_options; shared_ptr prng; -size_t hash_value(const TRule& r) { - size_t h = boost::hash_value(r.e_); - boost::hash_combine(h, -r.lhs_); - boost::hash_combine(h, boost::hash_value(r.f_)); - return h; -} - -bool operator==(const TRule& a, const TRule& b) { - return (a.lhs_ == b.lhs_ && a.e_ == b.e_ && a.f_ == b.f_); -} - void InitCommandLine(int argc, char** argv, po::variables_map* conf) { po::options_description opts("Configuration options"); opts.add_options() diff --git a/gi/pf/pfnaive.cc b/gi/pf/pfnaive.cc index 43c604c3..c30e7c4f 100644 --- a/gi/pf/pfnaive.cc +++ b/gi/pf/pfnaive.cc @@ -24,17 +24,6 @@ namespace po = boost::program_options; shared_ptr prng; -size_t hash_value(const TRule& r) { - size_t h = boost::hash_value(r.e_); - boost::hash_combine(h, -r.lhs_); - boost::hash_combine(h, boost::hash_value(r.f_)); - return h; -} - -bool operator==(const TRule& a, const TRule& b) { - return (a.lhs_ == b.lhs_ && a.e_ == b.e_ && a.f_ == b.f_); -} - void InitCommandLine(int argc, char** argv, po::variables_map* conf) { po::options_description opts("Configuration options"); opts.add_options() diff --git a/mteval/mbr_kbest.cc b/mteval/mbr_kbest.cc index 2867b36b..64a6a8bf 100644 --- a/mteval/mbr_kbest.cc +++ b/mteval/mbr_kbest.cc @@ -32,7 +32,7 @@ void InitCommandLine(int argc, char** argv, po::variables_map* conf) { } struct LossComparer { - bool operator()(const pair, double>& a, const pair, double>& b) const { + bool operator()(const pair, prob_t>& a, const pair, prob_t>& b) const { return a.second < b.second; } }; @@ -108,7 +108,7 @@ int main(int argc, char** argv) { ScoreP s = scorer->ScoreCandidate(list[j].first); double loss = 1.0 - s->ComputeScore(); if (type == TER || type == AER) loss = 1.0 - loss; - double weighted_loss = loss * (joints[j] / marginal); + double weighted_loss = loss * (joints[j] / marginal).as_float(); wl_acc += weighted_loss; if ((!output_list) && wl_acc > mbr_loss) break; } diff --git a/phrasinator/ccrp_nt.h b/phrasinator/ccrp_nt.h index 163b643a..811bce73 100644 --- a/phrasinator/ccrp_nt.h +++ b/phrasinator/ccrp_nt.h @@ -50,15 +50,26 @@ class CCRP_NoTable { return it->second; } - void increment(const Dish& dish) { - ++custs_[dish]; + int increment(const Dish& dish) { + int table_diff = 0; + if (++custs_[dish] == 1) + table_diff = 1; ++num_customers_; + return table_diff; } - void decrement(const Dish& dish) { - if ((--custs_[dish]) == 0) + int decrement(const Dish& dish) { + int table_diff = 0; + int nc = --custs_[dish]; + if (nc == 0) { custs_.erase(dish); + table_diff = -1; + } else if (nc < 0) { + std::cerr << "Dish counts dropped below zero for: " << dish << std::endl; + abort(); + } --num_customers_; + return table_diff; } double prob(const Dish& dish, const double& p0) const { @@ -66,6 +77,11 @@ class CCRP_NoTable { return (at_table + p0 * concentration_) / (num_customers_ + concentration_); } + double logprob(const Dish& dish, const double& logp0) const { + const unsigned at_table = num_customers(dish); + return log(at_table + exp(logp0 + log(concentration_))) - log(num_customers_ + concentration_); + } + double log_crp_prob() const { return log_crp_prob(concentration_); } diff --git a/training/mpi_batch_optimize.cc b/training/mpi_batch_optimize.cc index 0ba8c530..046e921c 100644 --- a/training/mpi_batch_optimize.cc +++ b/training/mpi_batch_optimize.cc @@ -92,7 +92,7 @@ struct TrainingObserver : public DecoderObserver { void SetLocalGradientAndObjective(vector* g, double* o) const { *o = acc_obj; for (SparseVector::const_iterator it = acc_grad.begin(); it != acc_grad.end(); ++it) - (*g)[it->first] = it->second; + (*g)[it->first] = it->second.as_float(); } virtual void NotifyDecodingStart(const SentenceMetadata& smeta) { diff --git a/training/mpi_compute_cllh.cc b/training/mpi_compute_cllh.cc index b496d196..d5caa745 100644 --- a/training/mpi_compute_cllh.cc +++ b/training/mpi_compute_cllh.cc @@ -1,6 +1,4 @@ -#include #include -#include #include #include #include @@ -12,6 +10,7 @@ #include #include +#include "sentence_metadata.h" #include "verbose.h" #include "hg.h" #include "prob.h" @@ -52,7 +51,8 @@ bool InitCommandLine(int argc, char** argv, po::variables_map* conf) { return true; } -void ReadTrainingCorpus(const string& fname, int rank, int size, vector* c, vector* ids) { +void ReadInstances(const string& fname, int rank, int size, vector* c) { + assert(fname != "-"); ReadFile rf(fname); istream& in = *rf.stream(); string line; @@ -60,20 +60,16 @@ void ReadTrainingCorpus(const string& fname, int rank, int size, vector* while(in) { getline(in, line); if (!in) break; - if (lc % size == rank) { - c->push_back(line); - ids->push_back(lc); - } + if (lc % size == rank) c->push_back(line); ++lc; } } static const double kMINUS_EPSILON = -1e-6; -struct TrainingObserver : public DecoderObserver { - void Reset() { - acc_obj = 0; - } +struct ConditionalLikelihoodObserver : public DecoderObserver { + + ConditionalLikelihoodObserver() : trg_words(), acc_obj(), cur_obj() {} virtual void NotifyDecodingStart(const SentenceMetadata&) { cur_obj = 0; @@ -120,8 +116,10 @@ struct TrainingObserver : public DecoderObserver { } assert(!isnan(log_ref_z)); acc_obj += (cur_obj - log_ref_z); + trg_words += smeta.GetReference().size(); } + unsigned trg_words; double acc_obj; double cur_obj; int state; @@ -161,35 +159,32 @@ int main(int argc, char** argv) { if (conf.count("weights")) Weights::InitFromFile(conf["weights"].as(), &weights); - // freeze feature set - //const bool freeze_feature_set = conf.count("freeze_feature_set"); - //if (freeze_feature_set) FD::Freeze(); - - vector corpus; vector ids; - ReadTrainingCorpus(conf["training_data"].as(), rank, size, &corpus, &ids); + vector corpus; + ReadInstances(conf["training_data"].as(), rank, size, &corpus); assert(corpus.size() > 0); - assert(corpus.size() == ids.size()); - - TrainingObserver observer; - double objective = 0; - observer.Reset(); if (rank == 0) - cerr << "Each processor is decoding " << corpus.size() << " training examples...\n"; + cerr << "Each processor is decoding ~" << corpus.size() << " training examples...\n"; - for (int i = 0; i < corpus.size(); ++i) { - decoder.SetId(ids[i]); + ConditionalLikelihoodObserver observer; + for (int i = 0; i < corpus.size(); ++i) decoder.Decode(corpus[i], &observer); - } + double objective = 0; + unsigned total_words = 0; #ifdef HAVE_MPI reduce(world, observer.acc_obj, objective, std::plus(), 0); + reduce(world, observer.trg_words, total_words, std::plus(), 0); #else objective = observer.acc_obj; #endif - if (rank == 0) - cout << "OBJECTIVE: " << objective << endl; + if (rank == 0) { + cout << "CONDITIONAL LOG_e LIKELIHOOD: " << objective << endl; + cout << "CONDITIONAL LOG_2 LIKELIHOOD: " << (objective/log(2)) << endl; + cout << " CONDITIONAL ENTROPY: " << (objective/log(2) / total_words) << endl; + cout << " PERPLEXITY: " << pow(2, (objective/log(2) / total_words)) << endl; + } return 0; } diff --git a/training/mpi_online_optimize.cc b/training/mpi_online_optimize.cc index 2ef4a2e7..f87b7274 100644 --- a/training/mpi_online_optimize.cc +++ b/training/mpi_online_optimize.cc @@ -94,7 +94,7 @@ struct TrainingObserver : public DecoderObserver { void SetLocalGradientAndObjective(vector* g, double* o) const { *o = acc_obj; for (SparseVector::const_iterator it = acc_grad.begin(); it != acc_grad.end(); ++it) - (*g)[it->first] = it->second; + (*g)[it->first] = it->second.as_float(); } virtual void NotifyDecodingStart(const SentenceMetadata& smeta) { @@ -158,7 +158,7 @@ struct TrainingObserver : public DecoderObserver { void GetGradient(SparseVector* g) const { g->clear(); for (SparseVector::const_iterator it = acc_grad.begin(); it != acc_grad.end(); ++it) - g->set_value(it->first, it->second); + g->set_value(it->first, it->second.as_float()); } int total_complete; diff --git a/utils/logval.h b/utils/logval.h index 6fdc2c42..8a59d0b1 100644 --- a/utils/logval.h +++ b/utils/logval.h @@ -25,12 +25,13 @@ class LogVal { typedef LogVal Self; LogVal() : s_(), v_(LOGVAL_LOG0) {} - explicit LogVal(double x) : s_(std::signbit(x)), v_(s_ ? std::log(-x) : std::log(x)) {} + LogVal(double x) : s_(std::signbit(x)), v_(s_ ? std::log(-x) : std::log(x)) {} + const Self& operator=(double x) { s_ = std::signbit(x); v_ = s_ ? std::log(-x) : std::log(x); return *this; } LogVal(init_minus_1) : s_(true),v_(0) { } LogVal(init_1) : s_(),v_(0) { } LogVal(init_0) : s_(),v_(LOGVAL_LOG0) { } - LogVal(int x) : s_(x<0), v_(s_ ? std::log(-x) : std::log(x)) {} - LogVal(unsigned x) : s_(0), v_(std::log(x)) { } + explicit LogVal(int x) : s_(x<0), v_(s_ ? std::log(-x) : std::log(x)) {} + explicit LogVal(unsigned x) : s_(0), v_(std::log(x)) { } LogVal(double lnx,bool sign) : s_(sign),v_(lnx) {} LogVal(double lnx,init_lnx) : s_(),v_(lnx) {} static Self exp(T lnx) { return Self(lnx,false); } @@ -141,9 +142,6 @@ class LogVal { return pow(1/root); } - operator T() const { - if (s_) return -std::exp(v_); else return std::exp(v_); - } T as_float() const { if (s_) return -std::exp(v_); else return std::exp(v_); } -- cgit v1.2.3