diff options
Diffstat (limited to 'training')
-rw-r--r-- | training/model1.cc | 61 | ||||
-rw-r--r-- | training/mpi_flex_optimize.cc | 2 | ||||
-rw-r--r-- | training/ttables.h | 17 |
3 files changed, 43 insertions, 37 deletions
diff --git a/training/model1.cc b/training/model1.cc index 73104304..19692b9a 100644 --- a/training/model1.cc +++ b/training/model1.cc @@ -5,7 +5,7 @@ #include <boost/program_options/variables_map.hpp> #include "m.h" -#include "lattice.h" +#include "corpus_tools.h" #include "stringlib.h" #include "filelib.h" #include "ttables.h" @@ -19,6 +19,7 @@ bool InitCommandLine(int argc, char** argv, po::variables_map* conf) { opts.add_options() ("iterations,i",po::value<unsigned>()->default_value(5),"Number of iterations of EM training") ("beam_threshold,t",po::value<double>()->default_value(-4),"log_10 of beam threshold (-10000 to include everything, 0 max)") + ("bidir,b", "Run bidirectional alignment") ("no_null_word,N","Do not generate from the null token") ("write_alignments,A", "Write alignments instead of parameters") ("favor_diagonal,d", "Use a static alignment distribution that assigns higher probabilities to alignments near the diagonal") @@ -51,6 +52,15 @@ bool InitCommandLine(int argc, char** argv, po::variables_map* conf) { return true; } +// src and trg are source and target strings, respectively (not really lattices) +double PosteriorInference(const vector<WordID>& src, const vector<WordID>& trg) { + double llh = 0; + static vector<double> unnormed_a_i; + if (src.size() > unnormed_a_i.size()) + unnormed_a_i.resize(src.size()); + return llh; +} + int main(int argc, char** argv) { po::variables_map conf; if (!InitCommandLine(argc, argv, &conf)) return 1; @@ -74,8 +84,8 @@ int main(int argc, char** argv) { return 1; } - TTable tt; - TTable::Word2Word2Double was_viterbi; + TTable s2t, t2s; + TTable::Word2Word2Double s2t_viterbi; double tot_len_ratio = 0; double mean_srclen_multiplier = 0; vector<double> unnormed_a_i; @@ -96,14 +106,11 @@ int main(int argc, char** argv) { ++lc; if (lc % 1000 == 0) { cerr << '.'; flag = true; } if (lc %50000 == 0) { cerr << " [" << lc << "]\n" << flush; flag = false; } - ParseTranslatorInput(line, &ssrc, &strg); - Lattice src, trg; - LatticeTools::ConvertTextToLattice(ssrc, &src); - LatticeTools::ConvertTextToLattice(strg, &trg); + vector<WordID> src, trg; + CorpusTools::ReadLine(line, &src, &trg); if (src.size() == 0 || trg.size() == 0) { cerr << "Error: " << lc << "\n" << line << endl; - assert(src.size() > 0); - assert(trg.size() > 0); + return 1; } if (src.size() > unnormed_a_i.size()) unnormed_a_i.resize(src.size()); @@ -113,13 +120,13 @@ int main(int argc, char** argv) { vector<double> probs(src.size() + 1); bool first_al = true; // used for write_alignments for (int j = 0; j < trg.size(); ++j) { - const WordID& f_j = trg[j][0].label; + const WordID& f_j = trg[j]; double sum = 0; const double j_over_ts = double(j) / trg.size(); double prob_a_i = 1.0 / (src.size() + use_null); // uniform (model 1) if (use_null) { if (favor_diagonal) prob_a_i = prob_align_null; - probs[0] = tt.prob(kNULL, f_j) * prob_a_i; + probs[0] = s2t.prob(kNULL, f_j) * prob_a_i; sum += probs[0]; } double az = 0; @@ -133,7 +140,7 @@ int main(int argc, char** argv) { for (int i = 1; i <= src.size(); ++i) { if (favor_diagonal) prob_a_i = unnormed_a_i[i-1] / az; - probs[i] = tt.prob(src[i-1][0].label, f_j) * prob_a_i; + probs[i] = s2t.prob(src[i-1], f_j) * prob_a_i; sum += probs[i]; } if (final_iteration) { @@ -150,7 +157,7 @@ int main(int argc, char** argv) { if (probs[i] > max_p) { max_index = i; max_p = probs[i]; - max_i = src[i-1][0].label; + max_i = src[i-1]; } } if (write_alignments) { @@ -159,13 +166,13 @@ int main(int argc, char** argv) { cout << (max_index - 1) << "-" << j; } } - was_viterbi[max_i][f_j] = 1.0; + s2t_viterbi[max_i][f_j] = 1.0; } } else { if (use_null) - tt.Increment(kNULL, f_j, probs[0] / sum); + s2t.Increment(kNULL, f_j, probs[0] / sum); for (int i = 1; i <= src.size(); ++i) - tt.Increment(src[i-1][0].label, f_j, probs[i] / sum); + s2t.Increment(src[i-1], f_j, probs[i] / sum); } likelihood += log(sum); } @@ -186,9 +193,9 @@ int main(int argc, char** argv) { cerr << " perplexity: " << pow(2.0, -base2_likelihood / denom) << endl; if (!final_iteration) { if (variational_bayes) - tt.NormalizeVB(alpha); + s2t.NormalizeVB(alpha); else - tt.Normalize(); + s2t.Normalize(); } } if (testset.size()) { @@ -199,23 +206,21 @@ int main(int argc, char** argv) { string ssrc, strg, line; while (getline(in, line)) { ++lc; - ParseTranslatorInput(line, &ssrc, &strg); - Lattice src, trg; - LatticeTools::ConvertTextToLattice(ssrc, &src); - LatticeTools::ConvertTextToLattice(strg, &trg); + vector<WordID> src, trg; + CorpusTools::ReadLine(line, &src, &trg); double log_prob = Md::log_poisson(trg.size(), 0.05 + src.size() * mean_srclen_multiplier); if (src.size() > unnormed_a_i.size()) unnormed_a_i.resize(src.size()); // compute likelihood for (int j = 0; j < trg.size(); ++j) { - const WordID& f_j = trg[j][0].label; + const WordID& f_j = trg[j]; double sum = 0; const double j_over_ts = double(j) / trg.size(); double prob_a_i = 1.0 / (src.size() + use_null); // uniform (model 1) if (use_null) { if (favor_diagonal) prob_a_i = prob_align_null; - sum += tt.prob(kNULL, f_j) * prob_a_i; + sum += s2t.prob(kNULL, f_j) * prob_a_i; } double az = 0; if (favor_diagonal) { @@ -228,7 +233,7 @@ int main(int argc, char** argv) { for (int i = 1; i <= src.size(); ++i) { if (favor_diagonal) prob_a_i = unnormed_a_i[i-1] / az; - sum += tt.prob(src[i-1][0].label, f_j) * prob_a_i; + sum += s2t.prob(src[i-1], f_j) * prob_a_i; } log_prob += log(sum); } @@ -240,16 +245,16 @@ int main(int argc, char** argv) { if (write_alignments) return 0; - for (TTable::Word2Word2Double::iterator ei = tt.ttable.begin(); ei != tt.ttable.end(); ++ei) { + for (TTable::Word2Word2Double::iterator ei = s2t.ttable.begin(); ei != s2t.ttable.end(); ++ei) { const TTable::Word2Double& cpd = ei->second; - const TTable::Word2Double& vit = was_viterbi[ei->first]; + const TTable::Word2Double& vit = s2t_viterbi[ei->first]; const string& esym = TD::Convert(ei->first); double max_p = -1; for (TTable::Word2Double::const_iterator fi = cpd.begin(); fi != cpd.end(); ++fi) if (fi->second > max_p) max_p = fi->second; const double threshold = max_p * BEAM_THRESHOLD; for (TTable::Word2Double::const_iterator fi = cpd.begin(); fi != cpd.end(); ++fi) { - if (fi->second > threshold || (vit.count(fi->first) > 0)) { + if (fi->second > threshold || (vit.find(fi->first) != vit.end())) { cout << esym << ' ' << TD::Convert(fi->first) << ' ' << log(fi->second) << endl; } } diff --git a/training/mpi_flex_optimize.cc b/training/mpi_flex_optimize.cc index a9ead018..b52decdc 100644 --- a/training/mpi_flex_optimize.cc +++ b/training/mpi_flex_optimize.cc @@ -356,7 +356,7 @@ int main(int argc, char** argv) { gg.clear(); gg.resize(FD::NumFeats()); if (gg.size() != cur_weights.size()) { cur_weights.resize(gg.size()); } - for (SparseVector<double>::const_iterator it = g.begin(); it != g.end(); ++it) + for (SparseVector<double>::iterator it = g.begin(); it != g.end(); ++it) if (it->first) { gg[it->first] = it->second; } g.clear(); double r = ApplyRegularizationTerms(regularization_strength, diff --git a/training/ttables.h b/training/ttables.h index bf3351d2..9baa13ca 100644 --- a/training/ttables.h +++ b/training/ttables.h @@ -4,6 +4,7 @@ #include <iostream> #include <tr1/unordered_map> +#include "sparse_vector.h" #include "m.h" #include "wordid.h" #include "tdict.h" @@ -68,18 +69,18 @@ class TTable { } return *this; } - void ShowTTable() { - for (Word2Word2Double::iterator it = ttable.begin(); it != ttable.end(); ++it) { - Word2Double& cpd = it->second; - for (Word2Double::iterator j = cpd.begin(); j != cpd.end(); ++j) { + void ShowTTable() const { + for (Word2Word2Double::const_iterator it = ttable.begin(); it != ttable.end(); ++it) { + const Word2Double& cpd = it->second; + for (Word2Double::const_iterator j = cpd.begin(); j != cpd.end(); ++j) { std::cerr << "P(" << TD::Convert(j->first) << '|' << TD::Convert(it->first) << ") = " << j->second << std::endl; } } } - void ShowCounts() { - for (Word2Word2Double::iterator it = counts.begin(); it != counts.end(); ++it) { - Word2Double& cpd = it->second; - for (Word2Double::iterator j = cpd.begin(); j != cpd.end(); ++j) { + void ShowCounts() const { + for (Word2Word2Double::const_iterator it = counts.begin(); it != counts.end(); ++it) { + const Word2Double& cpd = it->second; + for (Word2Double::const_iterator j = cpd.begin(); j != cpd.end(); ++j) { std::cerr << "c(" << TD::Convert(j->first) << '|' << TD::Convert(it->first) << ") = " << j->second << std::endl; } } |