diff options
author | Kenneth Heafield <github@kheafield.com> | 2012-10-22 12:07:20 +0100 |
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committer | Kenneth Heafield <github@kheafield.com> | 2012-10-22 12:07:20 +0100 |
commit | 5f98fe5c4f2a2090eeb9d30c030305a70a8347d1 (patch) | |
tree | 9b6002f850e6dea1e3400c6b19bb31a9cdf3067f /gi/pf/itg.cc | |
parent | cf9994131993b40be62e90e213b1e11e6b550143 (diff) | |
parent | 21825a09d97c2e0afd20512f306fb25fed55e529 (diff) |
Merge remote branch 'upstream/master'
Conflicts:
Jamroot
bjam
decoder/Jamfile
decoder/cdec.cc
dpmert/Jamfile
jam-files/sanity.jam
klm/lm/Jamfile
klm/util/Jamfile
mira/Jamfile
Diffstat (limited to 'gi/pf/itg.cc')
-rw-r--r-- | gi/pf/itg.cc | 275 |
1 files changed, 0 insertions, 275 deletions
diff --git a/gi/pf/itg.cc b/gi/pf/itg.cc deleted file mode 100644 index 29ec3860..00000000 --- a/gi/pf/itg.cc +++ /dev/null @@ -1,275 +0,0 @@ -#include <iostream> -#include <tr1/memory> -#include <queue> - -#include <boost/functional.hpp> -#include <boost/program_options.hpp> -#include <boost/program_options/variables_map.hpp> - -#include "viterbi.h" -#include "hg.h" -#include "trule.h" -#include "tdict.h" -#include "filelib.h" -#include "dict.h" -#include "sampler.h" -#include "ccrp_nt.h" -#include "ccrp_onetable.h" - -using namespace std; -using namespace tr1; -namespace po = boost::program_options; - -ostream& operator<<(ostream& os, const vector<WordID>& p) { - os << '['; - for (int i = 0; i < p.size(); ++i) - os << (i==0 ? "" : " ") << TD::Convert(p[i]); - return os << ']'; -} - -struct UnigramModel { - explicit UnigramModel(const string& fname, unsigned vocab_size, double p0null = 0.05) : - use_uniform_(fname.size() == 0), - p0null_(p0null), - uniform_((1.0 - p0null) / vocab_size), - probs_(TD::NumWords() + 1) { - if (fname.size() > 0) LoadUnigrams(fname); - probs_[0] = p0null_; - } - -// -// \data\ -// ngram 1=9295 -// -// \1-grams: -// -3.191193 " - - void LoadUnigrams(const string& fname) { - cerr << "Loading unigram probabilities from " << fname << " ..." << endl; - ReadFile rf(fname); - string line; - istream& in = *rf.stream(); - assert(in); - getline(in, line); - assert(line.empty()); - getline(in, line); - assert(line == "\\data\\"); - getline(in, line); - size_t pos = line.find("ngram 1="); - assert(pos == 0); - assert(line.size() > 8); - const size_t num_unigrams = atoi(&line[8]); - getline(in, line); - assert(line.empty()); - getline(in, line); - assert(line == "\\1-grams:"); - for (size_t i = 0; i < num_unigrams; ++i) { - getline(in, line); - assert(line.size() > 0); - pos = line.find('\t'); - assert(pos > 0); - assert(pos + 1 < line.size()); - const WordID w = TD::Convert(line.substr(pos + 1)); - line[pos] = 0; - float p = atof(&line[0]); - const prob_t pnon_null(1.0 - p0null_.as_float()); - if (w < probs_.size()) probs_[w].logeq(p * log(10) + log(pnon_null)); else abort(); - } - } - - const prob_t& operator()(const WordID& w) const { - if (!w) return p0null_; - if (use_uniform_) return uniform_; - return probs_[w]; - } - - const bool use_uniform_; - const prob_t p0null_; - const prob_t uniform_; - vector<prob_t> probs_; -}; - -struct Model1 { - explicit Model1(const string& fname) : - kNULL(TD::Convert("<eps>")), - kZERO() { - LoadModel1(fname); - } - - void LoadModel1(const string& fname) { - cerr << "Loading Model 1 parameters from " << fname << " ..." << endl; - ReadFile rf(fname); - istream& in = *rf.stream(); - string line; - unsigned lc = 0; - while(getline(in, line)) { - ++lc; - int cur = 0; - int start = 0; - while(cur < line.size() && line[cur] != ' ') { ++cur; } - assert(cur != line.size()); - line[cur] = 0; - const WordID src = TD::Convert(&line[0]); - ++cur; - start = cur; - while(cur < line.size() && line[cur] != ' ') { ++cur; } - assert(cur != line.size()); - line[cur] = 0; - WordID trg = TD::Convert(&line[start]); - const double logprob = strtod(&line[cur + 1], NULL); - if (src >= ttable.size()) ttable.resize(src + 1); - ttable[src][trg].logeq(logprob); - } - cerr << " read " << lc << " parameters.\n"; - } - - // 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 map<WordID, prob_t>& cpd = ttable[src]; - const 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; - vector<map<WordID, prob_t> > ttable; -}; - -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") - ("particles,p",po::value<unsigned>()->default_value(25),"Number of particles") - ("input,i",po::value<string>(),"Read parallel data from") - ("model1,m",po::value<string>(),"Model 1 parameters (used in base distribution)") - ("inverse_model1,M",po::value<string>(),"Inverse Model 1 parameters (used in backward estimate)") - ("model1_interpolation_weight",po::value<double>()->default_value(0.95),"Mixing proportion of model 1 with uniform target distribution") - ("src_unigram,u",po::value<string>()->default_value(""),"Source unigram distribution; empty for uniform") - ("trg_unigram,U",po::value<string>()->default_value(""),"Target unigram distribution; empty for uniform") - ("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,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<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); - } -} - -void ReadParallelCorpus(const string& filename, - vector<vector<WordID> >* f, - vector<vector<WordID> >* e, - set<WordID>* vocab_f, - set<WordID>* vocab_e) { - f->clear(); - e->clear(); - vocab_f->clear(); - vocab_e->clear(); - istream* in; - if (filename == "-") - in = &cin; - else - in = new ifstream(filename.c_str()); - assert(*in); - string line; - const WordID kDIV = TD::Convert("|||"); - vector<WordID> tmp; - while(*in) { - getline(*in, line); - if (line.empty() && !*in) break; - e->push_back(vector<int>()); - f->push_back(vector<int>()); - vector<int>& le = e->back(); - vector<int>& lf = f->back(); - tmp.clear(); - TD::ConvertSentence(line, &tmp); - bool isf = true; - for (unsigned i = 0; i < tmp.size(); ++i) { - const int cur = tmp[i]; - if (isf) { - if (kDIV == cur) { isf = false; } else { - lf.push_back(cur); - vocab_f->insert(cur); - } - } else { - assert(cur != kDIV); - le.push_back(cur); - vocab_e->insert(cur); - } - } - assert(isf == false); - } - if (in != &cin) delete in; -} - -int main(int argc, char** argv) { - po::variables_map conf; - InitCommandLine(argc, argv, &conf); - const unsigned particles = conf["particles"].as<unsigned>(); - const unsigned samples = conf["samples"].as<unsigned>(); - TD::Convert("<s>"); - TD::Convert("</s>"); - TD::Convert("<unk>"); - if (!conf.count("model1")) { - cerr << argv[0] << "Please use --model1 to specify model 1 parameters\n"; - return 1; - } - boost::shared_ptr<MT19937> prng; - 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, corpusf; - set<WordID> vocabe, vocabf; - cerr << "Reading corpus...\n"; - ReadParallelCorpus(conf["input"].as<string>(), &corpusf, &corpuse, &vocabf, &vocabe); - cerr << "F-corpus size: " << corpusf.size() << " sentences\t (" << vocabf.size() << " word types)\n"; - cerr << "E-corpus size: " << corpuse.size() << " sentences\t (" << vocabe.size() << " word types)\n"; - assert(corpusf.size() == corpuse.size()); - UnigramModel src_unigram(conf["src_unigram"].as<string>(), vocabf.size()); - UnigramModel trg_unigram(conf["trg_unigram"].as<string>(), vocabe.size()); - const prob_t kHALF(0.5); - - const string kEMPTY = "NULL"; - const int kLHS = -TD::Convert("X"); - Model1 m1(conf["model1"].as<string>()); - Model1 invm1(conf["inverse_model1"].as<string>()); - for (int si = 0; si < conf["samples"].as<unsigned>(); ++si) { - cerr << '.' << flush; - for (int ci = 0; ci < corpusf.size(); ++ci) { - const vector<WordID>& trg = corpuse[ci]; - const vector<WordID>& src = corpusf[ci]; - for (int i = 0; i <= trg.size(); ++i) { - const WordID e_i = i > 0 ? trg[i-1] : 0; - for (int j = 0; j <= src.size(); ++j) { - const WordID f_j = j > 0 ? src[j-1] : 0; - if (e_i == 0 && f_j == 0) continue; - prob_t je = kHALF * src_unigram(f_j) * m1(f_j,e_i) + kHALF * trg_unigram(e_i) * invm1(e_i,f_j); - cerr << "p( " << (e_i ? TD::Convert(e_i) : kEMPTY) << " , " << (f_j ? TD::Convert(f_j) : kEMPTY) << " ) = " << log(je) << endl; - if (e_i && f_j) - cout << "[X] ||| " << TD::Convert(f_j) << " ||| " << TD::Convert(e_i) << " ||| LogProb=" << log(je) << endl; - } - } - } - } -} - |