summaryrefslogtreecommitdiff
diff options
context:
space:
mode:
Diffstat
-rw-r--r--extools/Makefile.am10
-rw-r--r--extools/featurize_grammar.cc410
-rw-r--r--extools/filter_grammar.cc235
-rw-r--r--extools/filter_score_grammar.cc57
4 files changed, 700 insertions, 12 deletions
diff --git a/extools/Makefile.am b/extools/Makefile.am
index bce6c404..fc02f831 100644
--- a/extools/Makefile.am
+++ b/extools/Makefile.am
@@ -2,6 +2,8 @@ bin_PROGRAMS = \
extractor \
mr_stripe_rule_reduce \
build_lexical_translation \
+ filter_grammar \
+ featurize_grammar \
filter_score_grammar
noinst_PROGRAMS =
@@ -10,6 +12,14 @@ filter_score_grammar_SOURCES = filter_score_grammar.cc extract.cc sentence_pair.
filter_score_grammar_LDADD = $(top_srcdir)/decoder/libcdec.a -lz
filter_score_grammar_LDFLAGS = -all-static
+filter_grammar_SOURCES = filter_grammar.cc extract.cc sentence_pair.cc
+filter_grammar_LDADD = $(top_srcdir)/decoder/libcdec.a -lz
+filter_grammar_LDFLAGS = -all-static
+
+featurize_grammar_SOURCES = featurize_grammar.cc extract.cc sentence_pair.cc
+featurize_grammar_LDADD = $(top_srcdir)/decoder/libcdec.a -lz
+featurize_grammar_LDFLAGS = -all-static
+
build_lexical_translation_SOURCES = build_lexical_translation.cc extract.cc sentence_pair.cc
build_lexical_translation_LDADD = $(top_srcdir)/decoder/libcdec.a -lz
build_lexical_translation_LDFLAGS = -all-static
diff --git a/extools/featurize_grammar.cc b/extools/featurize_grammar.cc
new file mode 100644
index 00000000..1ca20a4b
--- /dev/null
+++ b/extools/featurize_grammar.cc
@@ -0,0 +1,410 @@
+/*
+ * Featurize a grammar in striped format
+ */
+#include <iostream>
+#include <string>
+#include <map>
+#include <vector>
+#include <utility>
+#include <cstdlib>
+#include <fstream>
+#include <tr1/unordered_map>
+
+#include "suffix_tree.h"
+#include "sparse_vector.h"
+#include "sentence_pair.h"
+#include "extract.h"
+#include "fdict.h"
+#include "tdict.h"
+#include "lex_trans_tbl.h"
+#include "filelib.h"
+
+#include <boost/shared_ptr.hpp>
+#include <boost/functional/hash.hpp>
+#include <boost/program_options.hpp>
+#include <boost/program_options/variables_map.hpp>
+
+using namespace std;
+using namespace std::tr1;
+namespace po = boost::program_options;
+
+static const size_t MAX_LINE_LENGTH = 64000000;
+
+typedef unordered_map<vector<WordID>, RuleStatistics, boost::hash<vector<WordID> > > ID2RuleStatistics;
+
+void InitCommandLine(int argc, char** argv, po::variables_map* conf) {
+ po::options_description opts("Configuration options");
+ opts.add_options()
+ ("filtered_grammar,g", po::value<string>(), "Grammar to add features to")
+ ("aligned_corpus,c", po::value<string>(), "Aligned corpus (single line format)")
+ ("help,h", "Print this help message and exit");
+ po::options_description clo("Command line options");
+ po::options_description dcmdline_options;
+ dcmdline_options.add(opts);
+
+ po::store(parse_command_line(argc, argv, dcmdline_options), *conf);
+ po::notify(*conf);
+
+ if (conf->count("help") || conf->count("aligned_corpus")==0) {
+ cerr << "\nUsage: featurize_grammar -g FILTERED-GRAMMAR.gz -c ALIGNED_CORPUS.fr-en-al [-options] < UNFILTERED-GRAMMAR\n";
+ cerr << dcmdline_options << endl;
+ exit(1);
+ }
+}
+
+namespace {
+ inline bool IsWhitespace(char c) { return c == ' ' || c == '\t'; }
+ inline bool IsBracket(char c){return c == '[' || c == ']';}
+ inline void SkipWhitespace(const char* buf, int* ptr) {
+ while (buf[*ptr] && IsWhitespace(buf[*ptr])) { ++(*ptr); }
+ }
+}
+
+int ReadPhraseUntilDividerOrEnd(const char* buf, const int sstart, const int end, vector<WordID>* p) {
+ static const WordID kDIV = TD::Convert("|||");
+ int ptr = sstart;
+ while(ptr < end) {
+ while(ptr < end && IsWhitespace(buf[ptr])) { ++ptr; }
+ int start = ptr;
+ while(ptr < end && !IsWhitespace(buf[ptr])) { ++ptr; }
+ if (ptr == start) {cerr << "Warning! empty token.\n"; return ptr; }
+ const WordID w = TD::Convert(string(buf, start, ptr - start));
+
+ if((IsBracket(buf[start]) and IsBracket(buf[ptr-1])) or( w == kDIV))
+ p->push_back(1 * w);
+ else {
+ if (w == kDIV) return ptr;
+ p->push_back(w);
+ }
+ }
+ return ptr;
+}
+
+void ParseLine(const char* buf, vector<WordID>* cur_key, ID2RuleStatistics* counts) {
+ static const WordID kDIV = TD::Convert("|||");
+ counts->clear();
+ int ptr = 0;
+ while(buf[ptr] != 0 && buf[ptr] != '\t') { ++ptr; }
+ if (buf[ptr] != '\t') {
+ cerr << "Missing tab separator between key and value!\n INPUT=" << buf << endl;
+ exit(1);
+ }
+ cur_key->clear();
+ // key is: "[X] ||| word word word"
+ int tmpp = ReadPhraseUntilDividerOrEnd(buf, 0, ptr, cur_key);
+ cur_key->push_back(kDIV);
+ ReadPhraseUntilDividerOrEnd(buf, tmpp, ptr, cur_key);
+ ++ptr;
+ int start = ptr;
+ int end = ptr;
+ int state = 0; // 0=reading label, 1=reading count
+ vector<WordID> name;
+ while(buf[ptr] != 0) {
+ while(buf[ptr] != 0 && buf[ptr] != '|') { ++ptr; }
+ if (buf[ptr] == '|') {
+ ++ptr;
+ if (buf[ptr] == '|') {
+ ++ptr;
+ if (buf[ptr] == '|') {
+ ++ptr;
+ end = ptr - 3;
+ while (end > start && IsWhitespace(buf[end-1])) { --end; }
+ if (start == end) {
+ cerr << "Got empty token!\n LINE=" << buf << endl;
+ exit(1);
+ }
+ switch (state) {
+ case 0: ++state; name.clear(); ReadPhraseUntilDividerOrEnd(buf, start, end, &name); break;
+ case 1: --state; (*counts)[name].ParseRuleStatistics(buf, start, end); break;
+ default: cerr << "Can't happen\n"; abort();
+ }
+ SkipWhitespace(buf, &ptr);
+ start = ptr;
+ }
+ }
+ }
+ }
+ end=ptr;
+ while (end > start && IsWhitespace(buf[end-1])) { --end; }
+ if (end > start) {
+ switch (state) {
+ case 0: ++state; name.clear(); ReadPhraseUntilDividerOrEnd(buf, start, end, &name); break;
+ case 1: --state; (*counts)[name].ParseRuleStatistics(buf, start, end); break;
+ default: cerr << "Can't happen\n"; abort();
+ }
+ }
+}
+
+
+void LexTranslationTable::createTTable(const char* buf){
+ AnnotatedParallelSentence sent;
+ sent.ParseInputLine(buf);
+
+ //iterate over the alignment to compute aligned words
+
+ for(int i =0;i<sent.aligned.width();i++)
+ {
+ for (int j=0;j<sent.aligned.height();j++)
+ {
+ if (DEBUG) cerr << sent.aligned(i,j) << " ";
+ if( sent.aligned(i,j))
+ {
+ if (DEBUG) cerr << TD::Convert(sent.f[i]) << " aligned to " << TD::Convert(sent.e[j]);
+ ++word_translation[pair<WordID,WordID> (sent.f[i], sent.e[j])];
+ ++total_foreign[sent.f[i]];
+ ++total_english[sent.e[j]];
+ }
+ }
+ if (DEBUG) cerr << endl;
+ }
+ if (DEBUG) cerr << endl;
+
+ const WordID NULL_ = TD::Convert("NULL");
+ //handle unaligned words - align them to null
+ for (int j =0; j < sent.e_len; j++) {
+ if (sent.e_aligned[j]) continue;
+ ++word_translation[pair<WordID,WordID> (NULL_, sent.e[j])];
+ ++total_foreign[NULL_];
+ ++total_english[sent.e[j]];
+ }
+
+ for (int i =0; i < sent.f_len; i++) {
+ if (sent.f_aligned[i]) continue;
+ ++word_translation[pair<WordID,WordID> (sent.f[i], NULL_)];
+ ++total_english[NULL_];
+ ++total_foreign[sent.f[i]];
+ }
+}
+
+inline float safenlog(float v) {
+ if (v == 1.0f) return 0.0f;
+ float res = -log(v);
+ if (res > 100.0f) res = 100.0f;
+ return res;
+}
+
+static bool IsZero(float f) { return (f > 0.999 && f < 1.001); }
+
+struct FeatureExtractor {
+ // create any keys necessary
+ virtual void ObserveFilteredRule(const WordID lhs,
+ const vector<WordID>& src,
+ const vector<WordID>& trg) {}
+
+ // compute statistics over keys, the same lhs-src-trg tuple may be seen
+ // more than once
+ virtual void ObserveUnfilteredRule(const WordID lhs,
+ const vector<WordID>& src,
+ const vector<WordID>& trg,
+ const RuleStatistics& info) {}
+
+ // compute features, a unique lhs-src-trg tuple will be seen exactly once
+ virtual void ExtractFeatures(const WordID lhs,
+ const vector<WordID>& src,
+ const vector<WordID>& trg,
+ const RuleStatistics& info,
+ SparseVector<float>* result) const = 0;
+
+ virtual ~FeatureExtractor() {}
+};
+
+struct LogRuleCount : public FeatureExtractor {
+ LogRuleCount() :
+ fid_(FD::Convert("LogRuleCount")),
+ sfid_(FD::Convert("SingletonRule")),
+ kCFE(FD::Convert("CFE")) {}
+ virtual void ExtractFeatures(const WordID lhs,
+ const vector<WordID>& src,
+ const vector<WordID>& trg,
+ const RuleStatistics& info,
+ SparseVector<float>* result) const {
+ (void) lhs; (void) src; (void) trg;
+ result->set_value(fid_, log(info.counts.value(kCFE)));
+ if (IsZero(info.counts.value(kCFE)))
+ result->set_value(sfid_, 1);
+ }
+ const int fid_;
+ const int sfid_;
+ const int kCFE;
+};
+
+// this extracts the lexical translation prob features
+// in BOTH directions.
+struct LexProbExtractor : public FeatureExtractor {
+ LexProbExtractor(const std::string& corpus) :
+ e2f_(FD::Convert("LexE2F")), f2e_(FD::Convert("LexF2E")) {
+ ReadFile rf(corpus);
+ //create lexical translation table
+ cerr << "Computing lexical translation probabilities from " << corpus << "..." << endl;
+ char* buf = new char[MAX_LINE_LENGTH];
+ istream& alignment = *rf.stream();
+ while(alignment) {
+ alignment.getline(buf, MAX_LINE_LENGTH);
+ if (buf[0] == 0) continue;
+ table.createTTable(buf);
+ }
+ delete[] buf;
+ }
+
+ virtual void ExtractFeatures(const WordID lhs,
+ const vector<WordID>& src,
+ const vector<WordID>& trg,
+ const RuleStatistics& info,
+ SparseVector<float>* result) const {
+ map <WordID, pair<int, float> > foreign_aligned;
+ map <WordID, pair<int, float> > english_aligned;
+
+ //Loop over all the alignment points to compute lexical translation probability
+ const vector< pair<short,short> >& al = info.aligns;
+ vector< pair<short,short> >::const_iterator ita;
+ for (ita = al.begin(); ita != al.end(); ++ita) {
+ if (DEBUG) {
+ cerr << "\nA:" << ita->first << "," << ita->second << "::";
+ cerr << TD::Convert(src[ita->first]) << "-" << TD::Convert(trg[ita->second]);
+ }
+
+ //Lookup this alignment probability in the table
+ int temp = table.word_translation[pair<WordID,WordID> (src[ita->first],trg[ita->second])];
+ float f2e=0, e2f=0;
+ if ( table.total_foreign[src[ita->first]] != 0)
+ f2e = (float) temp / table.total_foreign[src[ita->first]];
+ if ( table.total_english[trg[ita->second]] !=0 )
+ e2f = (float) temp / table.total_english[trg[ita->second]];
+ if (DEBUG) printf (" %d %E %E\n", temp, f2e, e2f);
+
+ //local counts to keep track of which things haven't been aligned, to later compute their null alignment
+ if (foreign_aligned.count(src[ita->first])) {
+ foreign_aligned[ src[ita->first] ].first++;
+ foreign_aligned[ src[ita->first] ].second += e2f;
+ } else {
+ foreign_aligned[ src[ita->first] ] = pair<int,float> (1,e2f);
+ }
+
+ if (english_aligned.count( trg[ ita->second] )) {
+ english_aligned[ trg[ ita->second] ].first++;
+ english_aligned[ trg[ ita->second] ].second += f2e;
+ } else {
+ english_aligned[ trg[ ita->second] ] = pair<int,float> (1,f2e);
+ }
+ }
+
+ float final_lex_f2e=1, final_lex_e2f=1;
+ static const WordID NULL_ = TD::Convert("NULL");
+
+ //compute lexical weight P(F|E) and include unaligned foreign words
+ for(int i=0;i<src.size(); i++) {
+ if (!table.total_foreign.count(src[i])) continue; //if we dont have it in the translation table, we won't know its lexical weight
+
+ if (foreign_aligned.count(src[i]))
+ {
+ pair<int, float> temp_lex_prob = foreign_aligned[src[i]];
+ final_lex_e2f *= temp_lex_prob.second / temp_lex_prob.first;
+ }
+ else //dealing with null alignment
+ {
+ int temp_count = table.word_translation[pair<WordID,WordID> (src[i],NULL_)];
+ float temp_e2f = (float) temp_count / table.total_english[NULL_];
+ final_lex_e2f *= temp_e2f;
+ }
+
+ }
+
+ //compute P(E|F) unaligned english words
+ for(int j=0; j< trg.size(); j++) {
+ if (!table.total_english.count(trg[j])) continue;
+
+ if (english_aligned.count(trg[j]))
+ {
+ pair<int, float> temp_lex_prob = english_aligned[trg[j]];
+ final_lex_f2e *= temp_lex_prob.second / temp_lex_prob.first;
+ }
+ else //dealing with null
+ {
+ int temp_count = table.word_translation[pair<WordID,WordID> (NULL_,trg[j])];
+ float temp_f2e = (float) temp_count / table.total_foreign[NULL_];
+ final_lex_f2e *= temp_f2e;
+ }
+ }
+ result->set_value(e2f_, safenlog(final_lex_e2f));
+ result->set_value(f2e_, safenlog(final_lex_f2e));
+ }
+ const int e2f_, f2e_;
+ mutable LexTranslationTable table;
+};
+
+int main(int argc, char** argv){
+ po::variables_map conf;
+ InitCommandLine(argc, argv, &conf);
+ ifstream alignment (conf["aligned_corpus"].as<string>().c_str());
+ ReadFile fg1(conf["filtered_grammar"].as<string>());
+
+ istream& fs1 = *fg1.stream();
+
+ // TODO make this list configurable
+ vector<boost::shared_ptr<FeatureExtractor> > extractors;
+ extractors.push_back(boost::shared_ptr<FeatureExtractor>(new LogRuleCount));
+ extractors.push_back(boost::shared_ptr<FeatureExtractor>(new LexProbExtractor(conf["aligned_corpus"].as<string>())));
+
+ //score unscored grammar
+ cerr << "Reading filtered grammar to detect keys..." << endl;
+ char* buf = new char[MAX_LINE_LENGTH];
+
+ ID2RuleStatistics acc, cur_counts;
+ vector<WordID> key, cur_key,temp_key;
+ WordID lhs = 0;
+ vector<WordID> src;
+
+#if 0
+ int line = 0;
+ while(fs1) {
+ fs1.getline(buf, MAX_LINE_LENGTH);
+ if (buf[0] == 0) continue;
+ ParseLine(buf, &cur_key, &cur_counts);
+ src.resize(cur_key.size() - 2);
+ for (int i = 0; i < src.size(); ++i) src[i] = cur_key[i+2];
+ lhs = cur_key[0];
+ for (ID2RuleStatistics::const_iterator it = cur_counts.begin(); it != cur_counts.end(); ++it) {
+ for (int i = 0; i < extractors.size(); ++i)
+ extractors[i]->ObserveFilteredRule(lhs, src, it->first);
+ }
+ }
+
+ cerr << "Reading unfiltered grammar..." << endl;
+ while(cin) {
+ cin.getline(buf, MAX_LINE_LENGTH);
+ if (buf[0] == 0) continue;
+ ParseLine(buf, &cur_key, &cur_counts);
+ src.resize(cur_key.size() - 2);
+ for (int i = 0; i < src.size(); ++i) src[i] = cur_key[i+2];
+ lhs = cur_key[0];
+ for (ID2RuleStatistics::const_iterator it = cur_counts.begin(); it != cur_counts.end(); ++it) {
+ // TODO set lhs, src, trg
+ for (int i = 0; i < extractors.size(); ++i)
+ extractors[i]->ObserveUnfilteredRule(lhs, src, it->first, it->second);
+ }
+ }
+#endif
+
+ ReadFile fg2(conf["filtered_grammar"].as<string>());
+ istream& fs2 = *fg2.stream();
+ cerr << "Reading filtered grammar and adding features..." << endl;
+ while(fs2) {
+ fs2.getline(buf, MAX_LINE_LENGTH);
+ if (buf[0] == 0) continue;
+ ParseLine(buf, &cur_key, &cur_counts);
+ src.resize(cur_key.size() - 2);
+ for (int i = 0; i < src.size(); ++i) src[i] = cur_key[i+2];
+ lhs = cur_key[0];
+
+ //loop over all the Target side phrases that this source aligns to
+ for (ID2RuleStatistics::const_iterator it = cur_counts.begin(); it != cur_counts.end(); ++it) {
+ SparseVector<float> feats;
+ for (int i = 0; i < extractors.size(); ++i)
+ extractors[i]->ExtractFeatures(lhs, src, it->first, it->second, &feats);
+ cout << TD::GetString(cur_key) << " ||| " << TD::GetString(it->first) << " ||| ";
+ feats.Write(false, &cout);
+ cout << endl;
+ }
+ }
+}
+
diff --git a/extools/filter_grammar.cc b/extools/filter_grammar.cc
new file mode 100644
index 00000000..a2992f7d
--- /dev/null
+++ b/extools/filter_grammar.cc
@@ -0,0 +1,235 @@
+/*
+ * Filter a grammar in striped format
+ */
+#include <iostream>
+#include <string>
+#include <map>
+#include <vector>
+#include <utility>
+#include <cstdlib>
+#include <fstream>
+#include <tr1/unordered_map>
+
+#include "suffix_tree.h"
+#include "sparse_vector.h"
+#include "sentence_pair.h"
+#include "extract.h"
+#include "fdict.h"
+#include "tdict.h"
+#include "lex_trans_tbl.h"
+#include "filelib.h"
+
+#include <boost/shared_ptr.hpp>
+#include <boost/functional/hash.hpp>
+#include <boost/program_options.hpp>
+#include <boost/program_options/variables_map.hpp>
+
+using namespace std;
+using namespace std::tr1;
+namespace po = boost::program_options;
+
+static const size_t MAX_LINE_LENGTH = 64000000;
+
+typedef unordered_map<vector<WordID>, RuleStatistics, boost::hash<vector<WordID> > > ID2RuleStatistics;
+
+void InitCommandLine(int argc, char** argv, po::variables_map* conf) {
+ po::options_description opts("Configuration options");
+ opts.add_options()
+ ("test_set,t", po::value<string>(), "Filter for this test set")
+ ("top_e_given_f,n", po::value<size_t>()->default_value(30), "Keep top N rules, according to p(e|f). 0 for all")
+ ("help,h", "Print this help message and exit");
+ po::options_description clo("Command line options");
+ po::options_description dcmdline_options;
+ dcmdline_options.add(opts);
+
+ po::store(parse_command_line(argc, argv, dcmdline_options), *conf);
+ po::notify(*conf);
+
+ if (conf->count("help") || conf->count("test_set")==0) {
+ cerr << "\nUsage: filter_grammar -t TEST-SET.fr [-options] < grammar\n";
+ cerr << dcmdline_options << endl;
+ exit(1);
+ }
+}
+namespace {
+ inline bool IsWhitespace(char c) { return c == ' ' || c == '\t'; }
+ inline bool IsBracket(char c){return c == '[' || c == ']';}
+ inline void SkipWhitespace(const char* buf, int* ptr) {
+ while (buf[*ptr] && IsWhitespace(buf[*ptr])) { ++(*ptr); }
+ }
+}
+
+int ReadPhraseUntilDividerOrEnd(const char* buf, const int sstart, const int end, vector<WordID>* p) {
+ static const WordID kDIV = TD::Convert("|||");
+ int ptr = sstart;
+ while(ptr < end) {
+ while(ptr < end && IsWhitespace(buf[ptr])) { ++ptr; }
+ int start = ptr;
+ while(ptr < end && !IsWhitespace(buf[ptr])) { ++ptr; }
+ if (ptr == start) {cerr << "Warning! empty token.\n"; return ptr; }
+ const WordID w = TD::Convert(string(buf, start, ptr - start));
+
+ if((IsBracket(buf[start]) and IsBracket(buf[ptr-1])) or( w == kDIV))
+ p->push_back(1 * w);
+ else {
+ if (w == kDIV) return ptr;
+ p->push_back(w);
+ }
+ }
+ return ptr;
+}
+
+
+void ParseLine(const char* buf, vector<WordID>* cur_key, ID2RuleStatistics* counts) {
+ static const WordID kDIV = TD::Convert("|||");
+ counts->clear();
+ int ptr = 0;
+ while(buf[ptr] != 0 && buf[ptr] != '\t') { ++ptr; }
+ if (buf[ptr] != '\t') {
+ cerr << "Missing tab separator between key and value!\n INPUT=" << buf << endl;
+ exit(1);
+ }
+ cur_key->clear();
+ // key is: "[X] ||| word word word"
+ int tmpp = ReadPhraseUntilDividerOrEnd(buf, 0, ptr, cur_key);
+ cur_key->push_back(kDIV);
+ ReadPhraseUntilDividerOrEnd(buf, tmpp, ptr, cur_key);
+ ++ptr;
+ int start = ptr;
+ int end = ptr;
+ int state = 0; // 0=reading label, 1=reading count
+ vector<WordID> name;
+ while(buf[ptr] != 0) {
+ while(buf[ptr] != 0 && buf[ptr] != '|') { ++ptr; }
+ if (buf[ptr] == '|') {
+ ++ptr;
+ if (buf[ptr] == '|') {
+ ++ptr;
+ if (buf[ptr] == '|') {
+ ++ptr;
+ end = ptr - 3;
+ while (end > start && IsWhitespace(buf[end-1])) { --end; }
+ if (start == end) {
+ cerr << "Got empty token!\n LINE=" << buf << endl;
+ exit(1);
+ }
+ switch (state) {
+ case 0: ++state; name.clear(); ReadPhraseUntilDividerOrEnd(buf, start, end, &name); break;
+ case 1: --state; (*counts)[name].ParseRuleStatistics(buf, start, end); break;
+ default: cerr << "Can't happen\n"; abort();
+ }
+ SkipWhitespace(buf, &ptr);
+ start = ptr;
+ }
+ }
+ }
+ }
+ end=ptr;
+ while (end > start && IsWhitespace(buf[end-1])) { --end; }
+ if (end > start) {
+ switch (state) {
+ case 0: ++state; name.clear(); ReadPhraseUntilDividerOrEnd(buf, start, end, &name); break;
+ case 1: --state; (*counts)[name].ParseRuleStatistics(buf, start, end); break;
+ default: cerr << "Can't happen\n"; abort();
+ }
+ }
+}
+
+
+struct SourceFilter {
+ // return true to keep the rule, otherwise false
+ virtual bool Matches(const vector<WordID>& key) const = 0;
+ virtual ~SourceFilter() {}
+};
+
+struct DumbSuffixTreeFilter : SourceFilter {
+ DumbSuffixTreeFilter(const string& corpus) :
+ kDIV(TD::Convert("|||")) {
+ cerr << "Build suffix tree from test set in " << corpus << endl;
+ assert(FileExists(corpus));
+ ReadFile rfts(corpus);
+ istream& testSet = *rfts.stream();
+ char* buf = new char[MAX_LINE_LENGTH];
+ AnnotatedParallelSentence sent;
+
+ /* process the data set to build suffix tree
+ */
+ while(!testSet.eof()) {
+ testSet.getline(buf, MAX_LINE_LENGTH);
+ if (buf[0] == 0) continue;
+
+ //hack to read in the test set using AnnotatedParallelSentence
+ strcat(buf," ||| fake ||| 0-0");
+ sent.ParseInputLine(buf);
+
+ //add each successive suffix to the tree
+ for(int i=0; i<sent.f_len; i++)
+ root.InsertPath(sent.f, i, sent.f_len - 1);
+ }
+ delete[] buf;
+ }
+ virtual bool Matches(const vector<WordID>& key) const {
+ const Node<int>* curnode = &root;
+ const int ks = key.size() - 1;
+ for(int i=0; i < ks; i++) {
+ const string& word = TD::Convert(key[i]);
+ if (key[i] == kDIV || (word[0] == '[' && word[word.size() - 1] == ']')) { // non-terminal
+ curnode = &root;
+ } else if (curnode) {
+ curnode = curnode->Extend(key[i]);
+ if (!curnode) return false;
+ }
+ }
+ return true;
+ }
+ const WordID kDIV;
+ Node<int> root;
+};
+
+int main(int argc, char** argv){
+ po::variables_map conf;
+ InitCommandLine(argc, argv, &conf);
+ const int max_options = conf["top_e_given_f"].as<size_t>();;
+ istream& unscored_grammar = cin;
+
+ cerr << "Loading test set " << conf["test_set"].as<string>() << "...\n";
+ boost::shared_ptr<SourceFilter> filter;
+ filter.reset(new DumbSuffixTreeFilter(conf["test_set"].as<string>()));
+
+ cerr << "Filtering...\n";
+ //score unscored grammar
+ char* buf = new char[MAX_LINE_LENGTH];
+
+ ID2RuleStatistics acc, cur_counts;
+ vector<WordID> key, cur_key,temp_key;
+ int line = 0;
+
+ multimap<float, ID2RuleStatistics::const_iterator> options;
+ const int kCOUNT = FD::Convert("CFE");
+ while(!unscored_grammar.eof())
+ {
+ ++line;
+ options.clear();
+ unscored_grammar.getline(buf, MAX_LINE_LENGTH);
+ if (buf[0] == 0) continue;
+ ParseLine(buf, &cur_key, &cur_counts);
+ if (!filter || filter->Matches(cur_key)) {
+ // sort by counts
+ for (ID2RuleStatistics::const_iterator it = cur_counts.begin(); it != cur_counts.end(); ++it) {
+ options.insert(make_pair(-it->second.counts.value(kCOUNT), it));
+ }
+ int ocount = 0;
+ cout << TD::GetString(cur_key) << '\t';
+
+ bool first = true;
+ for (multimap<float,ID2RuleStatistics::const_iterator>::iterator it = options.begin(); it != options.end(); ++it) {
+ if (first) { first = false; } else { cout << " ||| "; }
+ cout << TD::GetString(it->second->first) << " ||| " << it->second->second;
+ ++ocount;
+ if (ocount == max_options) break;
+ }
+ cout << endl;
+ }
+ }
+}
+
diff --git a/extools/filter_score_grammar.cc b/extools/filter_score_grammar.cc
index f34b240d..fe9a2a07 100644
--- a/extools/filter_score_grammar.cc
+++ b/extools/filter_score_grammar.cc
@@ -37,7 +37,7 @@ void InitCommandLine(int argc, char** argv, po::variables_map* conf) {
opts.add_options()
("test_set,t", po::value<string>(), "Filter for this test set (not specified = no filtering)")
("top_e_given_f,n", po::value<size_t>()->default_value(30), "Keep top N rules, according to p(e|f). 0 for all")
- ("hiero_features", "Use 'Hiero' features")
+ ("backoff_features", "Extract backoff X-features, assumes E, F, EF counts")
// ("feature,f", po::value<vector<string> >()->composing(), "List of features to compute")
("aligned_corpus,c", po::value<string>(), "Aligned corpus (single line format)")
("help,h", "Print this help message and exit");
@@ -247,36 +247,66 @@ struct FeatureExtractor {
const string extractor_name;
};
+static bool IsZero(float f) { return (f > 0.999 && f < 1.001); }
+
struct LogRuleCount : public FeatureExtractor {
LogRuleCount() :
FeatureExtractor("LogRuleCount"),
- fid_(FD::Convert("LogRuleCount")), kCFE(FD::Convert("CFE")) {}
+ fid_(FD::Convert("LogRuleCount")),
+ sfid_(FD::Convert("SingletonRule")),
+ kCFE(FD::Convert("CFE")) {}
virtual void ExtractFeatures(const vector<WordID>& lhs_src,
const vector<WordID>& trg,
const RuleStatistics& info,
SparseVector<float>* result) const {
(void) lhs_src; (void) trg;
result->set_value(fid_, log(info.counts.value(kCFE)));
+ if (IsZero(info.counts.value(kCFE)))
+ result->set_value(sfid_, 1);
}
const int fid_;
+ const int sfid_;
const int kCFE;
};
-struct SingletonRule : public FeatureExtractor {
- SingletonRule() :
- FeatureExtractor("SingletonRule"),
- fid_(FD::Convert("SingletonRule")), kCFE(FD::Convert("CFE")) {}
+struct LogECount : public FeatureExtractor {
+ LogECount() :
+ FeatureExtractor("LogECount"),
+ sfid_(FD::Convert("SingletonE")),
+ fid_(FD::Convert("LogECount")), kCE(FD::Convert("CE")) {}
virtual void ExtractFeatures(const vector<WordID>& lhs_src,
const vector<WordID>& trg,
const RuleStatistics& info,
SparseVector<float>* result) const {
(void) lhs_src; (void) trg;
- if (info.counts.value(kCFE) > 0.999 && info.counts.value(kCFE) < 1.001) {
- result->set_value(fid_, 1.0);
- }
+ assert(info.counts.value(kCE) > 0);
+ result->set_value(fid_, log(info.counts.value(kCE)));
+ if (IsZero(info.counts.value(kCE)))
+ result->set_value(sfid_, 1);
}
+ const int sfid_;
const int fid_;
- const int kCFE;
+ const int kCE;
+};
+
+struct LogFCount : public FeatureExtractor {
+ LogFCount() :
+ FeatureExtractor("LogFCount"),
+ sfid_(FD::Convert("SingletonF")),
+ fid_(FD::Convert("LogFCount")), kCF(FD::Convert("CF")) {}
+ virtual void ExtractFeatures(const vector<WordID>& lhs_src,
+ const vector<WordID>& trg,
+ const RuleStatistics& info,
+ SparseVector<float>* result) const {
+ (void) lhs_src; (void) trg;
+ assert(info.counts.value(kCF) > 0);
+ result->set_value(fid_, log(info.counts.value(kCF)));
+ if (IsZero(info.counts.value(kCF)))
+ result->set_value(sfid_, 1);
+ }
+ const int sfid_;
+ const int fid_;
+ const int kCF;
};
struct EGivenFExtractor : public FeatureExtractor {
@@ -437,13 +467,16 @@ int main(int argc, char** argv){
// TODO make this list configurable
vector<boost::shared_ptr<FeatureExtractor> > extractors;
- if (conf.count("hiero_features")) {
+ if (conf.count("backoff_features")) {
+ extractors.push_back(boost::shared_ptr<FeatureExtractor>(new LogRuleCount));
+ extractors.push_back(boost::shared_ptr<FeatureExtractor>(new LogECount));
+ extractors.push_back(boost::shared_ptr<FeatureExtractor>(new LogFCount));
extractors.push_back(boost::shared_ptr<FeatureExtractor>(new EGivenFExtractor));
extractors.push_back(boost::shared_ptr<FeatureExtractor>(new FGivenEExtractor));
extractors.push_back(boost::shared_ptr<FeatureExtractor>(new LexProbExtractor(conf["aligned_corpus"].as<string>())));
} else {
extractors.push_back(boost::shared_ptr<FeatureExtractor>(new LogRuleCount));
- extractors.push_back(boost::shared_ptr<FeatureExtractor>(new SingletonRule));
+ extractors.push_back(boost::shared_ptr<FeatureExtractor>(new LogFCount));
extractors.push_back(boost::shared_ptr<FeatureExtractor>(new LexProbExtractor(conf["aligned_corpus"].as<string>())));
}
generated by cgit v1.2.3 (git 2.39.1) at 2024-11-11 03:31:23 +0000