diff options
author | redpony <redpony@ec762483-ff6d-05da-a07a-a48fb63a330f> | 2010-12-01 00:03:35 +0000 |
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committer | redpony <redpony@ec762483-ff6d-05da-a07a-a48fb63a330f> | 2010-12-01 00:03:35 +0000 |
commit | 74615686493ad495c8e7802c96e5257da7e7f934 (patch) | |
tree | 1a24ec2b4d320dbbb9e0bead833cf921ebc2a8eb /training | |
parent | 7ebf32cd42fb1ea3db33603a7585792189b06d4a (diff) |
optional variational bayes
git-svn-id: https://ws10smt.googlecode.com/svn/trunk@734 ec762483-ff6d-05da-a07a-a48fb63a330f
Diffstat (limited to 'training')
-rw-r--r-- | training/model1.cc | 15 | ||||
-rw-r--r-- | training/ttables.h | 14 |
2 files changed, 28 insertions, 1 deletions
diff --git a/training/model1.cc b/training/model1.cc index eacf4b32..4023735c 100644 --- a/training/model1.cc +++ b/training/model1.cc @@ -20,6 +20,8 @@ bool InitCommandLine(int argc, char** argv, po::variables_map* conf) { ("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)") ("no_null_word,N","Do not generate from the null token") + ("variational_bayes,v","Add a symmetric Dirichlet prior and infer VB estimate of weights") + ("alpha,a", po::value<double>()->default_value(0.01), "Hyperparameter for optional Dirichlet prior") ("no_add_viterbi,V","Do not add Viterbi alignment points (may generate a grammar where some training sentence pairs are unreachable)"); po::options_description clo("Command line options"); clo.add_options() @@ -53,6 +55,12 @@ int main(int argc, char** argv) { const bool use_null = (conf.count("no_null_word") == 0); const WordID kNULL = TD::Convert("<eps>"); const bool add_viterbi = (conf.count("no_add_viterbi") == 0); + const bool variational_bayes = (conf.count("variational_bayes") > 0); + const double alpha = conf["alpha"].as<double>(); + if (variational_bayes && alpha <= 0.0) { + cerr << "--alpha must be > 0\n"; + return 1; + } TTable tt; TTable::Word2Word2Double was_viterbi; @@ -125,7 +133,12 @@ int main(int argc, char** argv) { cerr << " log likelihood: " << likelihood << endl; cerr << " cross entropy: " << (-likelihood / denom) << endl; cerr << " perplexity: " << pow(2.0, -likelihood / denom) << endl; - if (!final_iteration) tt.Normalize(); + if (!final_iteration) { + if (variational_bayes) + tt.NormalizeVB(alpha); + else + tt.Normalize(); + } } for (TTable::Word2Word2Double::iterator ei = tt.ttable.begin(); ei != tt.ttable.end(); ++ei) { const TTable::Word2Double& cpd = ei->second; diff --git a/training/ttables.h b/training/ttables.h index 53f5f2ab..50d85a68 100644 --- a/training/ttables.h +++ b/training/ttables.h @@ -6,6 +6,7 @@ #include "wordid.h" #include "tdict.h" +#include "em_utils.h" class TTable { public: @@ -29,6 +30,19 @@ class TTable { inline void Increment(const int& e, const int& f, double x) { counts[e][f] += x; } + void NormalizeVB(const double alpha) { + ttable.swap(counts); + for (Word2Word2Double::iterator cit = ttable.begin(); + cit != ttable.end(); ++cit) { + double tot = 0; + Word2Double& cpd = cit->second; + for (Word2Double::iterator it = cpd.begin(); it != cpd.end(); ++it) + tot += it->second + alpha; + for (Word2Double::iterator it = cpd.begin(); it != cpd.end(); ++it) + it->second = exp(digamma(it->second + alpha) - digamma(tot)); + } + counts.clear(); + } void Normalize() { ttable.swap(counts); for (Word2Word2Double::iterator cit = ttable.begin(); |