diff options
| -rw-r--r-- | dtrain/Makefile.am | 2 | ||||
| -rw-r--r-- | dtrain/dtrain.cc | 12 | ||||
| -rw-r--r-- | dtrain/dtrain.h | 2 | ||||
| -rw-r--r-- | dtrain/pairsampling.h | 15 | ||||
| -rw-r--r-- | dtrain/test/example/README | 4 | ||||
| -rw-r--r-- | dtrain/test/example/dtrain.ini | 2 |
6 files changed, 30 insertions, 7 deletions
diff --git a/dtrain/Makefile.am b/dtrain/Makefile.am index f39d161e..64fef489 100644 --- a/dtrain/Makefile.am +++ b/dtrain/Makefile.am @@ -3,5 +3,5 @@ bin_PROGRAMS = dtrain dtrain_SOURCES = dtrain.cc score.cc dtrain_LDADD = $(top_srcdir)/decoder/libcdec.a $(top_srcdir)/mteval/libmteval.a $(top_srcdir)/utils/libutils.a ../klm/lm/libklm.a ../klm/util/libklm_util.a -lz -AM_CPPFLAGS = -O3 -W -Wall -Wno-sign-compare -I$(top_srcdir)/utils -I$(top_srcdir)/decoder -I$(top_srcdir)/mteval +AM_CPPFLAGS = -W -Wall -Wno-sign-compare -I$(top_srcdir)/utils -I$(top_srcdir)/decoder -I$(top_srcdir)/mteval diff --git a/dtrain/dtrain.cc b/dtrain/dtrain.cc index 8b1fc953..864eb153 100644 --- a/dtrain/dtrain.cc +++ b/dtrain/dtrain.cc @@ -424,12 +424,18 @@ main(int argc, char** argv) for (vector<pair<ScoredHyp,ScoredHyp> >::iterator it = pairs.begin(); it != pairs.end(); it++) { +#ifdef DTRAIN_FASTER_PERCEPTRON + bool rank_error = true; // pair filtering already did this for us + rank_errors++; + score_t margin = 2.; // compiler, could you get rid of the margin? +#else bool rank_error = it->first.model <= it->second.model; if (rank_error) rank_errors++; score_t margin = fabs(it->first.model - it->second.model); - if (!rank_error && margin < 1) margin_violations++; + if (!rank_error && margin < 1.) margin_violations++; +#endif if (scale_bleu_diff) eta = it->first.score - it->second.score; - if (rank_error || (gamma && margin<1)) { + if (rank_error || (gamma && margin<1.)) { SparseVector<weight_t> diff_vec = it->first.f - it->second.f; lambdas.plus_eq_v_times_s(diff_vec, eta); if (gamma) @@ -534,8 +540,10 @@ main(int argc, char** argv) cerr << _np << npairs/(float)in_sz << endl; cerr << " avg # rank err: "; cerr << rank_errors/(float)in_sz << endl; +#ifndef DTRAIN_FASTER_PERCEPTRON cerr << " avg # margin viol: "; cerr << margin_violations/(float)in_sz << endl; +#endif cerr << " non0 feature count: " << nonz << endl; cerr << " avg list sz: " << list_sz/(float)in_sz << endl; cerr << " avg f count: " << f_count/(float)list_sz << endl; diff --git a/dtrain/dtrain.h b/dtrain/dtrain.h index 94d149ce..ac0345a4 100644 --- a/dtrain/dtrain.h +++ b/dtrain/dtrain.h @@ -32,7 +32,7 @@ inline void register_and_convert(const vector<string>& strs, vector<WordID>& ids inline string gettmpf(const string path, const string infix) { - char fn[1024]; + char fn[path.size() + infix.size() + 8]; strcpy(fn, path.c_str()); strcat(fn, "/"); strcat(fn, infix.c_str()); diff --git a/dtrain/pairsampling.h b/dtrain/pairsampling.h index bac132c6..52eeedd6 100644 --- a/dtrain/pairsampling.h +++ b/dtrain/pairsampling.h @@ -1,6 +1,9 @@ #ifndef _DTRAIN_PAIRSAMPLING_H_ #define _DTRAIN_PAIRSAMPLING_H_ +#define DTRAIN_FASTER_PERCEPTRON // only look at misranked pairs + // DO NOT USE WITH SVM! + namespace dtrain { @@ -51,6 +54,9 @@ partXYX(vector<ScoredHyp>* s, vector<pair<ScoredHyp,ScoredHyp> >& training, scor unsigned sep = round(sz*hi_lo); for (unsigned i = 0; i < sep; i++) { for (unsigned j = sep; j < sz; j++) { +#ifdef DTRAIN_FASTER_PERCEPTRON + if ((*s)[i].model <= (*s)[j].model) { +#endif if (threshold > 0) { if (accept_pair((*s)[i].score, (*s)[j].score, threshold)) training.push_back(make_pair((*s)[i], (*s)[j])); @@ -58,10 +64,16 @@ partXYX(vector<ScoredHyp>* s, vector<pair<ScoredHyp,ScoredHyp> >& training, scor if ((*s)[i].score != (*s)[j].score) training.push_back(make_pair((*s)[i], (*s)[j])); } +#ifdef DTRAIN_FASTER_PERCEPTRON + } +#endif } } for (unsigned i = sep; i < sz-sep; i++) { for (unsigned j = sz-sep; j < sz; j++) { +#ifdef DTRAIN_FASTER_PERCEPTRON + if ((*s)[i].model <= (*s)[j].model) { +#endif if (threshold > 0) { if (accept_pair((*s)[i].score, (*s)[j].score, threshold)) training.push_back(make_pair((*s)[i], (*s)[j])); @@ -69,6 +81,9 @@ partXYX(vector<ScoredHyp>* s, vector<pair<ScoredHyp,ScoredHyp> >& training, scor if ((*s)[i].score != (*s)[j].score) training.push_back(make_pair((*s)[i], (*s)[j])); } +#ifdef DTRAIN_FASTER_PERCEPTRON + } +#endif } } } diff --git a/dtrain/test/example/README b/dtrain/test/example/README index b3ea5f06..6937b11b 100644 --- a/dtrain/test/example/README +++ b/dtrain/test/example/README @@ -1,8 +1,8 @@ Small example of input format for distributed training. Call dtrain from cdec/dtrain/ with ./dtrain -c test/example/dtrain.ini . -For this to work, disable '#define DTRAIN_LOCAL' from dtrain.h +For this to work, undef 'DTRAIN_LOCAL' in dtrain.h and recompile. -Data is here: http://simianer.de/dtrain +Data is here: http://simianer.de/#dtrain diff --git a/dtrain/test/example/dtrain.ini b/dtrain/test/example/dtrain.ini index f87ee9cf..e43d6b34 100644 --- a/dtrain/test/example/dtrain.ini +++ b/dtrain/test/example/dtrain.ini @@ -5,7 +5,7 @@ decoder_config=test/example/cdec.ini # config for cdec # weights for these features will be printed on each iteration print_weights=Glue WordPenalty LanguageModel LanguageModel_OOV PhraseModel_0 PhraseModel_1 PhraseModel_2 PhraseModel_3 PhraseModel_4 PhraseModel_5 PhraseModel_6 PassThrough tmp=/tmp -stop_after=10 # stop epoch after 20 inputs +stop_after=20 # stop epoch after 20 inputs # interesting stuff epochs=3 # run over input 3 times |