diff options
author | Patrick Simianer <simianer@cl.uni-heidelberg.de> | 2012-07-08 14:26:51 +0200 |
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committer | Patrick Simianer <simianer@cl.uni-heidelberg.de> | 2012-07-08 14:26:51 +0200 |
commit | c139ce495861bb341e1b86a85ad4559f9ad53c14 (patch) | |
tree | 1071839ee458f21f169ce06fc536fefe07e4c65d /training | |
parent | 3a94ac22e5c60aa205f2b3dadf81b0666500e0c3 (diff) | |
parent | d01e5b66d3010d61b9b56301fd7f302dd4ea5bc8 (diff) |
Merge branch 'master' of github.com:pks/cdec-dtrain
Diffstat (limited to 'training')
-rw-r--r-- | training/Makefile.am | 1 | ||||
-rw-r--r-- | training/candidate_set.cc | 9 | ||||
-rw-r--r-- | training/entropy.cc | 41 | ||||
-rw-r--r-- | training/entropy.h | 22 |
4 files changed, 69 insertions, 4 deletions
diff --git a/training/Makefile.am b/training/Makefile.am index 68ebfab4..4cef0d5b 100644 --- a/training/Makefile.am +++ b/training/Makefile.am @@ -26,6 +26,7 @@ TESTS = lbfgs_test optimize_test noinst_LIBRARIES = libtraining.a libtraining_a_SOURCES = \ candidate_set.cc \ + entropy.cc \ optimize.cc \ online_optimizer.cc \ risk.cc diff --git a/training/candidate_set.cc b/training/candidate_set.cc index 8c086ece..087efec3 100644 --- a/training/candidate_set.cc +++ b/training/candidate_set.cc @@ -4,6 +4,7 @@ #include <boost/functional/hash.hpp> +#include "verbose.h" #include "ns.h" #include "filelib.h" #include "wordid.h" @@ -118,7 +119,7 @@ void CandidateSet::WriteToFile(const string& file) const { } void CandidateSet::ReadFromFile(const string& file) { - cerr << "Reading candidates from " << file << endl; + if(!SILENT) cerr << "Reading candidates from " << file << endl; ReadFile rf(file); istream& in = *rf.stream(); string cand; @@ -133,11 +134,11 @@ void CandidateSet::ReadFromFile(const string& file) { ParseSparseVector(feats, 0, &cs.back().fmap); cs.back().eval_feats = SufficientStats(ss); } - cerr << " read " << cs.size() << " candidates\n"; + if(!SILENT) cerr << " read " << cs.size() << " candidates\n"; } void CandidateSet::Dedup() { - cerr << "Dedup in=" << cs.size(); + if(!SILENT) cerr << "Dedup in=" << cs.size(); tr1::unordered_set<Candidate, CandidateHasher, CandidateCompare> u; while(cs.size() > 0) { u.insert(cs.back()); @@ -148,7 +149,7 @@ void CandidateSet::Dedup() { cs.push_back(*it); it = u.erase(it); } - cerr << " out=" << cs.size() << endl; + if(!SILENT) cerr << " out=" << cs.size() << endl; } void CandidateSet::AddKBestCandidates(const Hypergraph& hg, size_t kbest_size, const SegmentEvaluator* scorer) { diff --git a/training/entropy.cc b/training/entropy.cc new file mode 100644 index 00000000..4fdbe2be --- /dev/null +++ b/training/entropy.cc @@ -0,0 +1,41 @@ +#include "entropy.h" + +#include "prob.h" +#include "candidate_set.h" + +using namespace std; + +namespace training { + +// see Mann and McCallum "Efficient Computation of Entropy Gradient ..." for +// a mostly clear derivation of: +// g = E[ F(x,y) * log p(y|x) ] + H(y | x) * E[ F(x,y) ] +double CandidateSetEntropy::operator()(const vector<double>& params, + SparseVector<double>* g) const { + prob_t z; + vector<double> dps(cands_.size()); + for (unsigned i = 0; i < cands_.size(); ++i) { + dps[i] = cands_[i].fmap.dot(params); + const prob_t u(dps[i], init_lnx()); + z += u; + } + const double log_z = log(z); + + SparseVector<double> exp_feats; + double entropy = 0; + for (unsigned i = 0; i < cands_.size(); ++i) { + const double log_prob = cands_[i].fmap.dot(params) - log_z; + const double prob = exp(log_prob); + const double e_logprob = prob * log_prob; + entropy -= e_logprob; + if (g) { + (*g) += cands_[i].fmap * e_logprob; + exp_feats += cands_[i].fmap * prob; + } + } + if (g) (*g) += exp_feats * entropy; + return entropy; +} + +} + diff --git a/training/entropy.h b/training/entropy.h new file mode 100644 index 00000000..796589ca --- /dev/null +++ b/training/entropy.h @@ -0,0 +1,22 @@ +#ifndef _CSENTROPY_H_ +#define _CSENTROPY_H_ + +#include <vector> +#include "sparse_vector.h" + +namespace training { + class CandidateSet; + + class CandidateSetEntropy { + public: + explicit CandidateSetEntropy(const CandidateSet& cs) : cands_(cs) {} + // compute the entropy (expected log likelihood) of a CandidateSet + // (optional) the gradient of the entropy with respect to params + double operator()(const std::vector<double>& params, + SparseVector<double>* g = NULL) const; + private: + const CandidateSet& cands_; + }; +}; + +#endif |