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-rw-r--r--decoder/fst_translator.cc5
-rw-r--r--gi/pf/Makefile.am4
-rw-r--r--gi/pf/pyp_lm.cc150
3 files changed, 157 insertions, 2 deletions
diff --git a/decoder/fst_translator.cc b/decoder/fst_translator.cc
index 38dbd717..074de4c9 100644
--- a/decoder/fst_translator.cc
+++ b/decoder/fst_translator.cc
@@ -30,7 +30,10 @@ struct FSTTranslatorImpl {
if (input.find("{\"rules\"") == 0) {
istringstream is(input);
Hypergraph src_cfg_hg;
- assert(HypergraphIO::ReadFromJSON(&is, &src_cfg_hg));
+ if (!HypergraphIO::ReadFromJSON(&is, &src_cfg_hg)) {
+ cerr << "Failed to read HG from JSON.\n";
+ abort();
+ }
if (add_pass_through_rules) {
SparseVector<double> feats;
feats.set_value(FD::Convert("PassThrough"), 1);
diff --git a/gi/pf/Makefile.am b/gi/pf/Makefile.am
index 0cf0bc63..7cf9c14d 100644
--- a/gi/pf/Makefile.am
+++ b/gi/pf/Makefile.am
@@ -1,4 +1,4 @@
-bin_PROGRAMS = cbgi brat dpnaive pfbrat pfdist itg pfnaive condnaive align-lexonly align-lexonly-pyp learn_cfg
+bin_PROGRAMS = cbgi brat dpnaive pfbrat pfdist itg pfnaive condnaive align-lexonly align-lexonly-pyp learn_cfg pyp_lm
noinst_LIBRARIES = libpf.a
libpf_a_SOURCES = base_distributions.cc reachability.cc cfg_wfst_composer.cc corpus.cc unigrams.cc ngram_base.cc
@@ -9,6 +9,8 @@ align_lexonly_pyp_SOURCES = align-lexonly-pyp.cc
itg_SOURCES = itg.cc
+pyp_lm_SOURCES = pyp_lm.cc
+
learn_cfg_SOURCES = learn_cfg.cc
condnaive_SOURCES = condnaive.cc
diff --git a/gi/pf/pyp_lm.cc b/gi/pf/pyp_lm.cc
new file mode 100644
index 00000000..2837e33c
--- /dev/null
+++ b/gi/pf/pyp_lm.cc
@@ -0,0 +1,150 @@
+#include <iostream>
+#include <tr1/memory>
+#include <queue>
+
+#include <boost/functional.hpp>
+#include <boost/program_options.hpp>
+#include <boost/program_options/variables_map.hpp>
+
+#include "corpus_tools.h"
+#include "m.h"
+#include "tdict.h"
+#include "sampler.h"
+#include "ccrp.h"
+#include "ccrp_onetable.h"
+
+using namespace std;
+using namespace tr1;
+namespace po = boost::program_options;
+
+shared_ptr<MT19937> prng;
+
+void InitCommandLine(int argc, char** argv, po::variables_map* conf) {
+ po::options_description opts("Configuration options");
+ opts.add_options()
+ ("samples,s",po::value<unsigned>()->default_value(1000),"Number of samples")
+ ("input,i",po::value<string>(),"Read data from")
+ ("random_seed,S",po::value<uint32_t>(), "Random seed");
+ po::options_description clo("Command line options");
+ clo.add_options()
+ ("config", po::value<string>(), "Configuration file")
+ ("help", "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<string>().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);
+ }
+}
+
+template <unsigned N> struct PYPLM;
+
+// uniform base distribution
+template<> struct PYPLM<0> {
+ PYPLM(unsigned vs) : p0(1.0 / vs) {}
+ void increment(WordID w, const vector<WordID>& context, MT19937* rng) const {}
+ void decrement(WordID w, const vector<WordID>& context, MT19937* rng) const {}
+ double prob(WordID w, const vector<WordID>& context) const { return p0; }
+ const double p0;
+};
+
+// represents an N-gram LM
+template <unsigned N> struct PYPLM {
+ PYPLM(unsigned vs) : backoff(vs) {}
+ void increment(WordID w, const vector<WordID>& context, MT19937* rng) {
+ const double bo = backoff.prob(w, context);
+ static vector<WordID> lookup(N-1);
+ for (unsigned i = 0; i < N-1; ++i)
+ lookup[i] = context[context.size() - 1 - i];
+ typename unordered_map<vector<WordID>, CCRP<WordID>, boost::hash<vector<WordID> > >::iterator it = p.find(lookup);
+ if (it == p.end())
+ it = p.insert(make_pair(lookup, CCRP<WordID>(1,1,1,1))).first;
+ if (it->second.increment(w, bo, rng))
+ backoff.increment(w, context, rng);
+ }
+ void decrement(WordID w, const vector<WordID>& context, MT19937* rng) {
+ static vector<WordID> lookup(N-1);
+ for (unsigned i = 0; i < N-1; ++i)
+ lookup[i] = context[context.size() - 1 - i];
+ typename unordered_map<vector<WordID>, CCRP<WordID>, boost::hash<vector<WordID> > >::iterator it = p.find(lookup);
+ assert(it != p.end());
+ if (it->second.decrement(w, rng))
+ backoff.decrement(w, context, rng);
+ }
+ double prob(WordID w, const vector<WordID>& context) const {
+ const double bo = backoff.prob(w, context);
+ static vector<WordID> lookup(N-1);
+ for (unsigned i = 0; i < N-1; ++i)
+ lookup[i] = context[context.size() - 1 - i];
+ typename unordered_map<vector<WordID>, CCRP<WordID>, boost::hash<vector<WordID> > >::const_iterator it = p.find(lookup);
+ if (it == p.end()) return bo;
+ return it->second.prob(w, bo);
+ }
+ PYPLM<N-1> backoff;
+ unordered_map<vector<WordID>, CCRP<WordID>, boost::hash<vector<WordID> > > p;
+};
+
+int main(int argc, char** argv) {
+ po::variables_map conf;
+
+ InitCommandLine(argc, argv, &conf);
+ const unsigned samples = conf["samples"].as<unsigned>();
+ if (conf.count("random_seed"))
+ prng.reset(new MT19937(conf["random_seed"].as<uint32_t>()));
+ else
+ prng.reset(new MT19937);
+ MT19937& rng = *prng;
+ vector<vector<WordID> > corpuse;
+ set<WordID> vocabe;
+ const WordID kEOS = TD::Convert("</s>");
+ cerr << "Reading corpus...\n";
+ CorpusTools::ReadFromFile(conf["input"].as<string>(), &corpuse, &vocabe);
+ cerr << "E-corpus size: " << corpuse.size() << " sentences\t (" << vocabe.size() << " word types)\n";
+#define kORDER 5
+ PYPLM<kORDER> lm(vocabe.size());
+ vector<WordID> ctx(kORDER - 1, TD::Convert("<s>"));
+ int mci = corpuse.size() * 99 / 100;
+ for (int SS=0; SS < samples; ++SS) {
+ for (int ci = 0; ci < mci; ++ci) {
+ ctx.resize(kORDER - 1);
+ const vector<WordID>& s = corpuse[ci];
+ for (int i = 0; i <= s.size(); ++i) {
+ WordID w = (i < s.size() ? s[i] : kEOS);
+ if (SS > 0) lm.decrement(w, ctx, &rng);
+ lm.increment(w, ctx, &rng);
+ ctx.push_back(w);
+ }
+ if (SS > 0) lm.decrement(kEOS, ctx, &rng);
+ lm.increment(kEOS, ctx, &rng);
+ }
+ }
+ double llh = 0;
+ unsigned cnt = 0;
+ for (int ci = mci; ci < corpuse.size(); ++ci) {
+ ctx.resize(kORDER - 1);
+ const vector<WordID>& s = corpuse[ci];
+ for (int i = 0; i <= s.size(); ++i) {
+ WordID w = (i < s.size() ? s[i] : kEOS);
+ double lp = log(lm.prob(w, ctx)) / log(2);
+ cerr << "p(" << TD::Convert(w) << " | " << TD::GetString(ctx) << ") = " << lp << endl;
+ ctx.push_back(w);
+ llh -= lp;
+ cnt++;
+ }
+ }
+ cerr << " Log_10 prob: " << (llh * log(2) / log(10)) << endl;
+ cerr << " Count: " << (cnt) << endl;
+ cerr << "Cross-entropy: " << (llh / cnt) << endl;
+ cerr << " Perplexity: " << pow(2, llh / cnt) << endl;
+ return 0;
+}
+
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