From 535cfe8da7c6107d8415afd1381d59f2a6b9844f Mon Sep 17 00:00:00 2001 From: Chris Dyer Date: Sun, 24 Jun 2012 15:52:30 -0400 Subject: compute risk / gradient of risk --- training/Makefile.am | 3 ++- training/risk.cc | 43 +++++++++++++++++++++++++++++++++++++++++++ training/risk.h | 25 +++++++++++++++++++++++++ 3 files changed, 70 insertions(+), 1 deletion(-) create mode 100644 training/risk.cc create mode 100644 training/risk.h diff --git a/training/Makefile.am b/training/Makefile.am index 19ee8f0d..68ebfab4 100644 --- a/training/Makefile.am +++ b/training/Makefile.am @@ -27,7 +27,8 @@ noinst_LIBRARIES = libtraining.a libtraining_a_SOURCES = \ candidate_set.cc \ optimize.cc \ - online_optimizer.cc + online_optimizer.cc \ + risk.cc mpi_online_optimize_SOURCES = mpi_online_optimize.cc mpi_online_optimize_LDADD = libtraining.a $(top_srcdir)/decoder/libcdec.a $(top_srcdir)/mteval/libmteval.a $(top_srcdir)/utils/libutils.a ../klm/lm/libklm.a ../klm/util/libklm_util.a -lz diff --git a/training/risk.cc b/training/risk.cc new file mode 100644 index 00000000..347ed3cb --- /dev/null +++ b/training/risk.cc @@ -0,0 +1,43 @@ +#include "risk.h" + +#include "prob.h" +#include "candidate_set.h" +#include "ns.h" + +using namespace std; + +namespace training { + +// g = \sum_e p(e|f) * loss(e) * (phi(e,f) - E[phi(e,f)]) +double CandidateSetRisk::operator()(const vector& params, + SparseVector* g) const { + prob_t z; + for (unsigned i = 0; i < cands_.size(); ++i) { + const prob_t u(cands_[i].fmap.dot(params), init_lnx()); + z += u; + } + const double log_z = log(z); + + SparseVector exp_feats; + if (g) { + 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); + exp_feats += cands_[i].fmap * prob; + } + } + + double risk = 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 r = prob * metric_.ComputeScore(cands_[i].eval_feats); + risk += r; + if (g) (*g) += (cands_[i].fmap - exp_feats) * r; + } + return risk; +} + +} + + diff --git a/training/risk.h b/training/risk.h new file mode 100644 index 00000000..00ff60ec --- /dev/null +++ b/training/risk.h @@ -0,0 +1,25 @@ +#ifndef _RISK_H_ +#define _RISK_H_ + +#include +#include "sparse_vector.h" +class EvaluationMetric; + +namespace training { + class CandidateSet; + + class CandidateSetRisk { + explicit CandidateSetRisk(const CandidateSet& cs, const EvaluationMetric& metric) : + cands_(cs), + metric_(metric) {} + // compute the risk (expected loss) of a CandidateSet + // (optional) the gradient of the risk with respect to params + double operator()(const std::vector& params, + SparseVector* g = NULL) const; + private: + const CandidateSet& cands_; + const EvaluationMetric& metric_; + }; +}; + +#endif -- cgit v1.2.3