From 44b023d165402406fc20bb5fa240cb9a9ebf32ea Mon Sep 17 00:00:00 2001 From: Kenneth Heafield Date: Sun, 26 Jun 2011 18:40:15 -0400 Subject: Quantization --- decoder/cdec_ff.cc | 1 + 1 file changed, 1 insertion(+) (limited to 'decoder/cdec_ff.cc') diff --git a/decoder/cdec_ff.cc b/decoder/cdec_ff.cc index 37aa655b..31f88a4f 100644 --- a/decoder/cdec_ff.cc +++ b/decoder/cdec_ff.cc @@ -55,6 +55,7 @@ void register_feature_functions() { ff_registry.Register("CMR2008ReorderingFeatures", new FFFactory()); ff_registry.Register("KLanguageModel", new FFFactory >()); ff_registry.Register("KLanguageModel_Trie", new FFFactory >()); + ff_registry.Register("KLanguageModel_QuantTrie", new FFFactory >()); ff_registry.Register("KLanguageModel_Probing", new FFFactory >()); ff_registry.Register("NonLatinCount", new FFFactory); ff_registry.Register("RuleShape", new FFFactory); -- cgit v1.2.3 From f69c59716b161500011ea60892254c2701b9d63e Mon Sep 17 00:00:00 2001 From: Chris Dyer Date: Wed, 6 Jul 2011 19:54:58 -0400 Subject: ngram count features --- decoder/Makefile.am | 1 + decoder/cdec_ff.cc | 2 + decoder/ff_ngrams.cc | 319 +++++++++++++++++++++++++++++++++++++++++++++++++++ decoder/ff_ngrams.h | 29 +++++ 4 files changed, 351 insertions(+) create mode 100644 decoder/ff_ngrams.cc create mode 100644 decoder/ff_ngrams.h (limited to 'decoder/cdec_ff.cc') diff --git a/decoder/Makefile.am b/decoder/Makefile.am index 244da2de..d884c431 100644 --- a/decoder/Makefile.am +++ b/decoder/Makefile.am @@ -65,6 +65,7 @@ libcdec_a_SOURCES = \ ff_charset.cc \ ff_lm.cc \ ff_klm.cc \ + ff_ngrams.cc \ ff_spans.cc \ ff_ruleshape.cc \ ff_wordalign.cc \ diff --git a/decoder/cdec_ff.cc b/decoder/cdec_ff.cc index 31f88a4f..3451c9fb 100644 --- a/decoder/cdec_ff.cc +++ b/decoder/cdec_ff.cc @@ -4,6 +4,7 @@ #include "ff_spans.h" #include "ff_lm.h" #include "ff_klm.h" +#include "ff_ngrams.h" #include "ff_csplit.h" #include "ff_wordalign.h" #include "ff_tagger.h" @@ -51,6 +52,7 @@ void register_feature_functions() { ff_registry.Register("RandLM", new FFFactory); #endif ff_registry.Register("SpanFeatures", new FFFactory()); + ff_registry.Register("NgramFeatures", new FFFactory()); ff_registry.Register("RuleNgramFeatures", new FFFactory()); ff_registry.Register("CMR2008ReorderingFeatures", new FFFactory()); ff_registry.Register("KLanguageModel", new FFFactory >()); diff --git a/decoder/ff_ngrams.cc b/decoder/ff_ngrams.cc new file mode 100644 index 00000000..54b394ae --- /dev/null +++ b/decoder/ff_ngrams.cc @@ -0,0 +1,319 @@ +#include "ff_ngrams.h" + +#include +#include + +#include + +#include "filelib.h" +#include "stringlib.h" +#include "hg.h" +#include "tdict.h" + +using namespace std; + +static const unsigned char HAS_FULL_CONTEXT = 1; +static const unsigned char HAS_EOS_ON_RIGHT = 2; +static const unsigned char MASK = 7; + +namespace { +template +struct State { + explicit State() { + memset(state, 0, sizeof(state)); + } + explicit State(int order) { + memset(state, 0, (order - 1) * sizeof(WordID)); + } + State(char order, const WordID* mem) { + memcpy(state, mem, (order - 1) * sizeof(WordID)); + } + State(const State& other) { + memcpy(state, other.state, sizeof(state)); + } + const State& operator=(const State& other) { + memcpy(state, other.state, sizeof(state)); + } + explicit State(const State& other, unsigned order, WordID extend) { + char om1 = order - 1; + assert(om1 > 0); + for (char i = 1; i < om1; ++i) state[i - 1]= other.state[i]; + state[om1 - 1] = extend; + } + const WordID& operator[](size_t i) const { return state[i]; } + WordID& operator[](size_t i) { return state[i]; } + WordID state[MAX_ORDER]; +}; +} + +class NgramDetectorImpl { + + // returns the number of unscored words at the left edge of a span + inline int UnscoredSize(const void* state) const { + return *(static_cast(state) + unscored_size_offset_); + } + + inline void SetUnscoredSize(int size, void* state) const { + *(static_cast(state) + unscored_size_offset_) = size; + } + + inline State<5> RemnantLMState(const void* cstate) const { + return State<5>(order_, static_cast(cstate)); + } + + inline const State<5> BeginSentenceState() const { + State<5> state(order_); + state.state[0] = kSOS_; + return state; + } + + inline void SetRemnantLMState(const State<5>& lmstate, void* state) const { + // if we were clever, we could use the memory pointed to by state to do all + // the work, avoiding this copy + memcpy(state, lmstate.state, (order_-1) * sizeof(WordID)); + } + + WordID IthUnscoredWord(int i, const void* state) const { + const WordID* const mem = reinterpret_cast(static_cast(state) + unscored_words_offset_); + return mem[i]; + } + + void SetIthUnscoredWord(int i, const WordID index, void *state) const { + WordID* mem = reinterpret_cast(static_cast(state) + unscored_words_offset_); + mem[i] = index; + } + + inline bool GetFlag(const void *state, unsigned char flag) const { + return (*(static_cast(state) + is_complete_offset_) & flag); + } + + inline void SetFlag(bool on, unsigned char flag, void *state) const { + if (on) { + *(static_cast(state) + is_complete_offset_) |= flag; + } else { + *(static_cast(state) + is_complete_offset_) &= (MASK ^ flag); + } + } + + inline bool HasFullContext(const void *state) const { + return GetFlag(state, HAS_FULL_CONTEXT); + } + + inline void SetHasFullContext(bool flag, void *state) const { + SetFlag(flag, HAS_FULL_CONTEXT, state); + } + + void FireFeatures(const State<5>& state, const WordID cur, SparseVector* feats) { + assert(order_ == 2); + if (cur >= unimap_.size()) + unimap_.resize(cur + 10, 0); + int& uf = unimap_[cur]; + if (!uf) { + ostringstream os; + os << "U:" << TD::Convert(cur); + uf = FD::Convert(os.str()); + } + feats->set_value(uf, 1.0); + if (state.state[0]) { + if (state.state[0] >= bimap_.size()) + bimap_.resize(state.state[0] + 10); + int& bf = bimap_[state.state[0]][cur]; + if (!bf) { + ostringstream os; + os << "B:" << TD::Convert(state[0]) << '_' << TD::Convert(cur); + bf = FD::Convert(os.str()); + } + feats->set_value(bf, 1.0); + } + } + + public: + void LookupWords(const TRule& rule, const vector& ant_states, SparseVector* feats, SparseVector* est_feats, void* remnant) { + double sum = 0.0; + double est_sum = 0.0; + int num_scored = 0; + int num_estimated = 0; + bool saw_eos = false; + bool has_some_history = false; + State<5> state; + const vector& e = rule.e(); + bool context_complete = false; + for (int j = 0; j < e.size(); ++j) { + if (e[j] < 1) { // handle non-terminal substitution + const void* astate = (ant_states[-e[j]]); + int unscored_ant_len = UnscoredSize(astate); + for (int k = 0; k < unscored_ant_len; ++k) { + const WordID cur_word = IthUnscoredWord(k, astate); + const bool is_oov = (cur_word == 0); + SparseVector p; + if (cur_word == kSOS_) { + state = BeginSentenceState(); + if (has_some_history) { // this is immediately fully scored, and bad + p.set_value(FD::Convert("Malformed"), 1.0); + context_complete = true; + } else { // this might be a real + num_scored = max(0, order_ - 2); + } + } else { + FireFeatures(state, cur_word, &p); + const State<5> scopy = State<5>(state, order_, cur_word); + state = scopy; + if (saw_eos) { p.set_value(FD::Convert("Malformed"), 1.0); } + saw_eos = (cur_word == kEOS_); + } + has_some_history = true; + ++num_scored; + if (!context_complete) { + if (num_scored >= order_) context_complete = true; + } + if (context_complete) { + (*feats) += p; + } else { + if (remnant) + SetIthUnscoredWord(num_estimated, cur_word, remnant); + ++num_estimated; + (*est_feats) += p; + } + } + saw_eos = GetFlag(astate, HAS_EOS_ON_RIGHT); + if (HasFullContext(astate)) { // this is equivalent to the "star" in Chiang 2007 + state = RemnantLMState(astate); + context_complete = true; + } + } else { // handle terminal + const WordID cur_word = e[j]; + SparseVector p; + if (cur_word == kSOS_) { + state = BeginSentenceState(); + if (has_some_history) { // this is immediately fully scored, and bad + p.set_value(FD::Convert("Malformed"), -100); + context_complete = true; + } else { // this might be a real + num_scored = max(0, order_ - 2); + } + } else { + FireFeatures(state, cur_word, &p); + const State<5> scopy = State<5>(state, order_, cur_word); + state = scopy; + if (saw_eos) { p.set_value(FD::Convert("Malformed"), 1.0); } + saw_eos = (cur_word == kEOS_); + } + has_some_history = true; + ++num_scored; + if (!context_complete) { + if (num_scored >= order_) context_complete = true; + } + if (context_complete) { + (*feats) += p; + } else { + if (remnant) + SetIthUnscoredWord(num_estimated, cur_word, remnant); + ++num_estimated; + (*est_feats) += p; + } + } + } + if (remnant) { + SetFlag(saw_eos, HAS_EOS_ON_RIGHT, remnant); + SetRemnantLMState(state, remnant); + SetUnscoredSize(num_estimated, remnant); + SetHasFullContext(context_complete || (num_scored >= order_), remnant); + } + } + + // this assumes no target words on final unary -> goal rule. is that ok? + // for (n-1 left words) and (n-1 right words) + void FinalTraversal(const void* state, SparseVector* feats) { + if (add_sos_eos_) { // rules do not produce , so do it here + SetRemnantLMState(BeginSentenceState(), dummy_state_); + SetHasFullContext(1, dummy_state_); + SetUnscoredSize(0, dummy_state_); + dummy_ants_[1] = state; + LookupWords(*dummy_rule_, dummy_ants_, feats, NULL, NULL); + } else { // rules DO produce ... +#if 0 + double p = 0; + if (!GetFlag(state, HAS_EOS_ON_RIGHT)) { p -= 100; } + if (UnscoredSize(state) > 0) { // are there unscored words + if (kSOS_ != IthUnscoredWord(0, state)) { + p -= 100 * UnscoredSize(state); + } + } + return p; +#endif + } + } + + public: + explicit NgramDetectorImpl(bool explicit_markers) : + kCDEC_UNK(TD::Convert("")) , + add_sos_eos_(!explicit_markers) { + order_ = 2; + state_size_ = (order_ - 1) * sizeof(WordID) + 2 + (order_ - 1) * sizeof(WordID); + unscored_size_offset_ = (order_ - 1) * sizeof(WordID); + is_complete_offset_ = unscored_size_offset_ + 1; + unscored_words_offset_ = is_complete_offset_ + 1; + + // special handling of beginning / ending sentence markers + dummy_state_ = new char[state_size_]; + memset(dummy_state_, 0, state_size_); + dummy_ants_.push_back(dummy_state_); + dummy_ants_.push_back(NULL); + dummy_rule_.reset(new TRule("[DUMMY] ||| [BOS] [DUMMY] ||| [1] [2] ||| X=0")); + kSOS_ = TD::Convert(""); + kEOS_ = TD::Convert(""); + } + + ~NgramDetectorImpl() { + delete[] dummy_state_; + } + + int ReserveStateSize() const { return state_size_; } + + private: + const WordID kCDEC_UNK; + WordID kSOS_; // - requires special handling. + WordID kEOS_; // + const bool add_sos_eos_; // flag indicating whether the hypergraph produces and + // if this is true, FinalTransitionFeatures will "add" and + // if false, FinalTransitionFeatures will score anything with the + // markers in the right place (i.e., the beginning and end of + // the sentence) with 0, and anything else with -100 + + int order_; + int state_size_; + int unscored_size_offset_; + int is_complete_offset_; + int unscored_words_offset_; + char* dummy_state_; + vector dummy_ants_; + TRulePtr dummy_rule_; + mutable std::vector unimap_; // [left][right] + mutable std::vector > bimap_; // [left][right] +}; + +NgramDetector::NgramDetector(const string& param) { + string filename, mapfile, featname; + bool explicit_markers = (param == "-x"); + pimpl_ = new NgramDetectorImpl(explicit_markers); + SetStateSize(pimpl_->ReserveStateSize()); +} + +NgramDetector::~NgramDetector() { + delete pimpl_; +} + +void NgramDetector::TraversalFeaturesImpl(const SentenceMetadata& /* smeta */, + const Hypergraph::Edge& edge, + const vector& ant_states, + SparseVector* features, + SparseVector* estimated_features, + void* state) const { + pimpl_->LookupWords(*edge.rule_, ant_states, features, estimated_features, state); +} + +void NgramDetector::FinalTraversalFeatures(const void* ant_state, + SparseVector* features) const { + pimpl_->FinalTraversal(ant_state, features); +} + diff --git a/decoder/ff_ngrams.h b/decoder/ff_ngrams.h new file mode 100644 index 00000000..82f61b33 --- /dev/null +++ b/decoder/ff_ngrams.h @@ -0,0 +1,29 @@ +#ifndef _NGRAMS_FF_H_ +#define _NGRAMS_FF_H_ + +#include +#include +#include + +#include "ff.h" + +struct NgramDetectorImpl; +class NgramDetector : public FeatureFunction { + public: + // param = "filename.lm [-o n]" + NgramDetector(const std::string& param); + ~NgramDetector(); + virtual void FinalTraversalFeatures(const void* context, + SparseVector* features) const; + protected: + virtual void TraversalFeaturesImpl(const SentenceMetadata& smeta, + const Hypergraph::Edge& edge, + const std::vector& ant_contexts, + SparseVector* features, + SparseVector* estimated_features, + void* out_context) const; + private: + NgramDetectorImpl* pimpl_; +}; + +#endif -- cgit v1.2.3 From 7607b0a7873f52d6e3ea387bf88c773cbb55f8ee Mon Sep 17 00:00:00 2001 From: Kenneth Heafield Date: Thu, 18 Aug 2011 12:14:01 +0100 Subject: KenLM update: Bhiksha's trick, simple test for lms without unk, auto-detect binary files instead of requiring them to be specified at runtime. --- decoder/cdec_ff.cc | 5 +- decoder/ff_klm.cc | 38 +++++- decoder/ff_klm.h | 7 +- klm/compile.sh | 2 +- klm/lm/Makefile.am | 1 + klm/lm/bhiksha.cc | 93 +++++++++++++++ klm/lm/bhiksha.hh | 108 +++++++++++++++++ klm/lm/binary_format.cc | 13 ++- klm/lm/binary_format.hh | 9 +- klm/lm/build_binary.cc | 54 ++++++--- klm/lm/config.cc | 1 + klm/lm/config.hh | 5 +- klm/lm/model.cc | 67 ++++++----- klm/lm/model.hh | 12 +- klm/lm/model_test.cc | 73 ++++++++++-- klm/lm/ngram_query.cc | 9 ++ klm/lm/quantize.cc | 1 + klm/lm/quantize.hh | 4 +- klm/lm/read_arpa.cc | 6 +- klm/lm/search_hashed.cc | 2 +- klm/lm/search_hashed.hh | 3 +- klm/lm/search_trie.cc | 45 +++---- klm/lm/search_trie.hh | 20 ++-- klm/lm/test_nounk.arpa | 120 +++++++++++++++++++ klm/lm/trie.cc | 57 ++++----- klm/lm/trie.hh | 24 ++-- klm/lm/vocab.cc | 6 +- klm/lm/vocab.hh | 4 + klm/util/bit_packing.hh | 13 ++- klm/util/murmur_hash.cc | 258 ++++++++++++++++++++--------------------- klm/util/probing_hash_table.hh | 2 +- klm/util/sorted_uniform.hh | 23 +++- 32 files changed, 792 insertions(+), 293 deletions(-) create mode 100644 klm/lm/bhiksha.cc create mode 100644 klm/lm/bhiksha.hh create mode 100644 klm/lm/test_nounk.arpa (limited to 'decoder/cdec_ff.cc') diff --git a/decoder/cdec_ff.cc b/decoder/cdec_ff.cc index 3451c9fb..1ef76a05 100644 --- a/decoder/cdec_ff.cc +++ b/decoder/cdec_ff.cc @@ -55,10 +55,7 @@ void register_feature_functions() { ff_registry.Register("NgramFeatures", new FFFactory()); ff_registry.Register("RuleNgramFeatures", new FFFactory()); ff_registry.Register("CMR2008ReorderingFeatures", new FFFactory()); - ff_registry.Register("KLanguageModel", new FFFactory >()); - ff_registry.Register("KLanguageModel_Trie", new FFFactory >()); - ff_registry.Register("KLanguageModel_QuantTrie", new FFFactory >()); - ff_registry.Register("KLanguageModel_Probing", new FFFactory >()); + ff_registry.Register("KLanguageModel", new KLanguageModelFactory()); ff_registry.Register("NonLatinCount", new FFFactory); ff_registry.Register("RuleShape", new FFFactory); ff_registry.Register("RelativeSentencePosition", new FFFactory); diff --git a/decoder/ff_klm.cc b/decoder/ff_klm.cc index 9b7fe2d3..24dcb9c3 100644 --- a/decoder/ff_klm.cc +++ b/decoder/ff_klm.cc @@ -9,6 +9,7 @@ #include "stringlib.h" #include "hg.h" #include "tdict.h" +#include "lm/model.hh" #include "lm/enumerate_vocab.hh" using namespace std; @@ -434,8 +435,37 @@ void KLanguageModel::FinalTraversalFeatures(const void* ant_state, features->set_value(oov_fid_, oovs); } -// instantiate templates -template class KLanguageModel; -template class KLanguageModel; -template class KLanguageModel; +template boost::shared_ptr CreateModel(const std::string ¶m) { + KLanguageModel *ret = new KLanguageModel(param); + ret->Init(); + return boost::shared_ptr(ret); +} +boost::shared_ptr KLanguageModelFactory::Create(std::string param) const { + using namespace lm::ngram; + std::string filename, ignored_map; + bool ignored_markers; + std::string ignored_featname; + ParseLMArgs(param, &filename, &ignored_map, &ignored_markers, &ignored_featname); + ModelType m; + if (!RecognizeBinary(filename.c_str(), m)) m = HASH_PROBING; + + switch (m) { + case HASH_PROBING: + return CreateModel(param); + case TRIE_SORTED: + return CreateModel(param); + case ARRAY_TRIE_SORTED: + return CreateModel(param); + case QUANT_TRIE_SORTED: + return CreateModel(param); + case QUANT_ARRAY_TRIE_SORTED: + return CreateModel(param); + default: + UTIL_THROW(util::Exception, "Unrecognized kenlm binary file type " << (unsigned)m); + } +} + +std::string KLanguageModelFactory::usage(bool params,bool verbose) const { + return KLanguageModel::usage(params, verbose); +} diff --git a/decoder/ff_klm.h b/decoder/ff_klm.h index 5eafe8be..6efe50f6 100644 --- a/decoder/ff_klm.h +++ b/decoder/ff_klm.h @@ -4,8 +4,8 @@ #include #include +#include "ff_factory.h" #include "ff.h" -#include "lm/model.hh" template struct KLanguageModelImpl; @@ -34,4 +34,9 @@ class KLanguageModel : public FeatureFunction { KLanguageModelImpl* pimpl_; }; +struct KLanguageModelFactory : public FactoryBase { + FP Create(std::string param) const; + std::string usage(bool params,bool verbose) const; +}; + #endif diff --git a/klm/compile.sh b/klm/compile.sh index 6ca85e1f..abe3473a 100755 --- a/klm/compile.sh +++ b/klm/compile.sh @@ -5,7 +5,7 @@ set -e -for i in util/{bit_packing,ersatz_progress,exception,file_piece,murmur_hash,scoped,mmap} lm/{binary_format,config,lm_exception,model,quantize,read_arpa,search_hashed,search_trie,trie,virtual_interface,vocab}; do +for i in util/{bit_packing,ersatz_progress,exception,file_piece,murmur_hash,scoped,mmap} lm/{bhiksha,binary_format,config,lm_exception,model,quantize,read_arpa,search_hashed,search_trie,trie,virtual_interface,vocab}; do g++ -I. -O3 $CXXFLAGS -c $i.cc -o $i.o done g++ -I. -O3 $CXXFLAGS lm/build_binary.cc {lm,util}/*.o -lz -o build_binary diff --git a/klm/lm/Makefile.am b/klm/lm/Makefile.am index 395494bc..fae6b41a 100644 --- a/klm/lm/Makefile.am +++ b/klm/lm/Makefile.am @@ -12,6 +12,7 @@ build_binary_LDADD = libklm.a ../util/libklm_util.a -lz noinst_LIBRARIES = libklm.a libklm_a_SOURCES = \ + bhiksha.cc \ binary_format.cc \ config.cc \ lm_exception.cc \ diff --git a/klm/lm/bhiksha.cc b/klm/lm/bhiksha.cc new file mode 100644 index 00000000..bf86fd4b --- /dev/null +++ b/klm/lm/bhiksha.cc @@ -0,0 +1,93 @@ +#include "lm/bhiksha.hh" +#include "lm/config.hh" + +#include + +namespace lm { +namespace ngram { +namespace trie { + +DontBhiksha::DontBhiksha(const void * /*base*/, uint64_t /*max_offset*/, uint64_t max_next, const Config &/*config*/) : + next_(util::BitsMask::ByMax(max_next)) {} + +const uint8_t kArrayBhikshaVersion = 0; + +void ArrayBhiksha::UpdateConfigFromBinary(int fd, Config &config) { + uint8_t version; + uint8_t configured_bits; + if (read(fd, &version, 1) != 1 || read(fd, &configured_bits, 1) != 1) { + UTIL_THROW(util::ErrnoException, "Could not read from binary file"); + } + if (version != kArrayBhikshaVersion) UTIL_THROW(FormatLoadException, "This file has sorted array compression version " << (unsigned) version << " but the code expects version " << (unsigned)kArrayBhikshaVersion); + config.pointer_bhiksha_bits = configured_bits; +} + +namespace { + +// Find argmin_{chopped \in [0, RequiredBits(max_next)]} ChoppedDelta(max_offset) +uint8_t ChopBits(uint64_t max_offset, uint64_t max_next, const Config &config) { + uint8_t required = util::RequiredBits(max_next); + uint8_t best_chop = 0; + int64_t lowest_change = std::numeric_limits::max(); + // There are probably faster ways but I don't care because this is only done once per order at construction time. + for (uint8_t chop = 0; chop <= std::min(required, config.pointer_bhiksha_bits); ++chop) { + int64_t change = (max_next >> (required - chop)) * 64 /* table cost in bits */ + - max_offset * static_cast(chop); /* savings in bits*/ + if (change < lowest_change) { + lowest_change = change; + best_chop = chop; + } + } + return best_chop; +} + +std::size_t ArrayCount(uint64_t max_offset, uint64_t max_next, const Config &config) { + uint8_t required = util::RequiredBits(max_next); + uint8_t chopping = ChopBits(max_offset, max_next, config); + return (max_next >> (required - chopping)) + 1 /* we store 0 too */; +} +} // namespace + +std::size_t ArrayBhiksha::Size(uint64_t max_offset, uint64_t max_next, const Config &config) { + return sizeof(uint64_t) * (1 /* header */ + ArrayCount(max_offset, max_next, config)) + 7 /* 8-byte alignment */; +} + +uint8_t ArrayBhiksha::InlineBits(uint64_t max_offset, uint64_t max_next, const Config &config) { + return util::RequiredBits(max_next) - ChopBits(max_offset, max_next, config); +} + +namespace { + +void *AlignTo8(void *from) { + uint8_t *val = reinterpret_cast(from); + std::size_t remainder = reinterpret_cast(val) & 7; + if (!remainder) return val; + return val + 8 - remainder; +} + +} // namespace + +ArrayBhiksha::ArrayBhiksha(void *base, uint64_t max_offset, uint64_t max_next, const Config &config) + : next_inline_(util::BitsMask::ByBits(InlineBits(max_offset, max_next, config))), + offset_begin_(reinterpret_cast(AlignTo8(base)) + 1 /* 8-byte header */), + offset_end_(offset_begin_ + ArrayCount(max_offset, max_next, config)), + write_to_(reinterpret_cast(AlignTo8(base)) + 1 /* 8-byte header */ + 1 /* first entry is 0 */), + original_base_(base) {} + +void ArrayBhiksha::FinishedLoading(const Config &config) { + // *offset_begin_ = 0 but without a const_cast. + *(write_to_ - (write_to_ - offset_begin_)) = 0; + + if (write_to_ != offset_end_) UTIL_THROW(util::Exception, "Did not get all the array entries that were expected."); + + uint8_t *head_write = reinterpret_cast(original_base_); + *(head_write++) = kArrayBhikshaVersion; + *(head_write++) = config.pointer_bhiksha_bits; +} + +void ArrayBhiksha::LoadedBinary() { +} + +} // namespace trie +} // namespace ngram +} // namespace lm diff --git a/klm/lm/bhiksha.hh b/klm/lm/bhiksha.hh new file mode 100644 index 00000000..cfb2b053 --- /dev/null +++ b/klm/lm/bhiksha.hh @@ -0,0 +1,108 @@ +/* Simple implementation of + * @inproceedings{bhikshacompression, + * author={Bhiksha Raj and Ed Whittaker}, + * year={2003}, + * title={Lossless Compression of Language Model Structure and Word Identifiers}, + * booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing}, + * pages={388--391}, + * } + * + * Currently only used for next pointers. + */ + +#include + +#include "lm/binary_format.hh" +#include "lm/trie.hh" +#include "util/bit_packing.hh" +#include "util/sorted_uniform.hh" + +namespace lm { +namespace ngram { +class Config; + +namespace trie { + +class DontBhiksha { + public: + static const ModelType kModelTypeAdd = static_cast(0); + + static void UpdateConfigFromBinary(int /*fd*/, Config &/*config*/) {} + + static std::size_t Size(uint64_t /*max_offset*/, uint64_t /*max_next*/, const Config &/*config*/) { return 0; } + + static uint8_t InlineBits(uint64_t /*max_offset*/, uint64_t max_next, const Config &/*config*/) { + return util::RequiredBits(max_next); + } + + DontBhiksha(const void *base, uint64_t max_offset, uint64_t max_next, const Config &config); + + void ReadNext(const void *base, uint64_t bit_offset, uint64_t /*index*/, uint8_t total_bits, NodeRange &out) const { + out.begin = util::ReadInt57(base, bit_offset, next_.bits, next_.mask); + out.end = util::ReadInt57(base, bit_offset + total_bits, next_.bits, next_.mask); + //assert(out.end >= out.begin); + } + + void WriteNext(void *base, uint64_t bit_offset, uint64_t /*index*/, uint64_t value) { + util::WriteInt57(base, bit_offset, next_.bits, value); + } + + void FinishedLoading(const Config &/*config*/) {} + + void LoadedBinary() {} + + uint8_t InlineBits() const { return next_.bits; } + + private: + util::BitsMask next_; +}; + +class ArrayBhiksha { + public: + static const ModelType kModelTypeAdd = kArrayAdd; + + static void UpdateConfigFromBinary(int fd, Config &config); + + static std::size_t Size(uint64_t max_offset, uint64_t max_next, const Config &config); + + static uint8_t InlineBits(uint64_t max_offset, uint64_t max_next, const Config &config); + + ArrayBhiksha(void *base, uint64_t max_offset, uint64_t max_value, const Config &config); + + void ReadNext(const void *base, uint64_t bit_offset, uint64_t index, uint8_t total_bits, NodeRange &out) const { + const uint64_t *begin_it = util::BinaryBelow(util::IdentityAccessor(), offset_begin_, offset_end_, index); + const uint64_t *end_it; + for (end_it = begin_it; (end_it < offset_end_) && (*end_it <= index + 1); ++end_it) {} + --end_it; + out.begin = ((begin_it - offset_begin_) << next_inline_.bits) | + util::ReadInt57(base, bit_offset, next_inline_.bits, next_inline_.mask); + out.end = ((end_it - offset_begin_) << next_inline_.bits) | + util::ReadInt57(base, bit_offset + total_bits, next_inline_.bits, next_inline_.mask); + } + + void WriteNext(void *base, uint64_t bit_offset, uint64_t index, uint64_t value) { + uint64_t encode = value >> next_inline_.bits; + for (; write_to_ <= offset_begin_ + encode; ++write_to_) *write_to_ = index; + util::WriteInt57(base, bit_offset, next_inline_.bits, value & next_inline_.mask); + } + + void FinishedLoading(const Config &config); + + void LoadedBinary(); + + uint8_t InlineBits() const { return next_inline_.bits; } + + private: + const util::BitsMask next_inline_; + + const uint64_t *const offset_begin_; + const uint64_t *const offset_end_; + + uint64_t *write_to_; + + void *original_base_; +}; + +} // namespace trie +} // namespace ngram +} // namespace lm diff --git a/klm/lm/binary_format.cc b/klm/lm/binary_format.cc index 92b1008b..e02e621a 100644 --- a/klm/lm/binary_format.cc +++ b/klm/lm/binary_format.cc @@ -40,7 +40,7 @@ struct Sanity { } }; -const char *kModelNames[3] = {"hashed n-grams with probing", "hashed n-grams with sorted uniform find", "bit packed trie"}; +const char *kModelNames[6] = {"hashed n-grams with probing", "hashed n-grams with sorted uniform find", "trie", "trie with quantization", "trie with array-compressed pointers", "trie with quantization and array-compressed pointers"}; std::size_t Align8(std::size_t in) { std::size_t off = in % 8; @@ -100,16 +100,17 @@ uint8_t *SetupJustVocab(const Config &config, uint8_t order, std::size_t memory_ } } -uint8_t *GrowForSearch(const Config &config, std::size_t memory_size, Backing &backing) { +uint8_t *GrowForSearch(const Config &config, std::size_t vocab_pad, std::size_t memory_size, Backing &backing) { + std::size_t adjusted_vocab = backing.vocab.size() + vocab_pad; if (config.write_mmap) { // Grow the file to accomodate the search, using zeros. - if (-1 == ftruncate(backing.file.get(), backing.vocab.size() + memory_size)) - UTIL_THROW(util::ErrnoException, "ftruncate on " << config.write_mmap << " to " << (backing.vocab.size() + memory_size) << " failed"); + if (-1 == ftruncate(backing.file.get(), adjusted_vocab + memory_size)) + UTIL_THROW(util::ErrnoException, "ftruncate on " << config.write_mmap << " to " << (adjusted_vocab + memory_size) << " failed"); // We're skipping over the header and vocab for the search space mmap. mmap likes page aligned offsets, so some arithmetic to round the offset down. off_t page_size = sysconf(_SC_PAGE_SIZE); - off_t alignment_cruft = backing.vocab.size() % page_size; - backing.search.reset(util::MapOrThrow(alignment_cruft + memory_size, true, util::kFileFlags, false, backing.file.get(), backing.vocab.size() - alignment_cruft), alignment_cruft + memory_size, util::scoped_memory::MMAP_ALLOCATED); + off_t alignment_cruft = adjusted_vocab % page_size; + backing.search.reset(util::MapOrThrow(alignment_cruft + memory_size, true, util::kFileFlags, false, backing.file.get(), adjusted_vocab - alignment_cruft), alignment_cruft + memory_size, util::scoped_memory::MMAP_ALLOCATED); return reinterpret_cast(backing.search.get()) + alignment_cruft; } else { diff --git a/klm/lm/binary_format.hh b/klm/lm/binary_format.hh index 2b32b450..d28cb6c5 100644 --- a/klm/lm/binary_format.hh +++ b/klm/lm/binary_format.hh @@ -16,7 +16,12 @@ namespace lm { namespace ngram { -typedef enum {HASH_PROBING=0, HASH_SORTED=1, TRIE_SORTED=2, QUANT_TRIE_SORTED=3} ModelType; +/* Not the best numbering system, but it grew this way for historical reasons + * and I want to preserve existing binary files. */ +typedef enum {HASH_PROBING=0, HASH_SORTED=1, TRIE_SORTED=2, QUANT_TRIE_SORTED=3, ARRAY_TRIE_SORTED=4, QUANT_ARRAY_TRIE_SORTED=5} ModelType; + +const static ModelType kQuantAdd = static_cast(QUANT_TRIE_SORTED - TRIE_SORTED); +const static ModelType kArrayAdd = static_cast(ARRAY_TRIE_SORTED - TRIE_SORTED); /*Inspect a file to determine if it is a binary lm. If not, return false. * If so, return true and set recognized to the type. This is the only API in @@ -55,7 +60,7 @@ void AdvanceOrThrow(int fd, off_t off); // Create just enough of a binary file to write vocabulary to it. uint8_t *SetupJustVocab(const Config &config, uint8_t order, std::size_t memory_size, Backing &backing); // Grow the binary file for the search data structure and set backing.search, returning the memory address where the search data structure should begin. -uint8_t *GrowForSearch(const Config &config, std::size_t memory_size, Backing &backing); +uint8_t *GrowForSearch(const Config &config, std::size_t vocab_pad, std::size_t memory_size, Backing &backing); // Write header to binary file. This is done last to prevent incomplete files // from loading. diff --git a/klm/lm/build_binary.cc b/klm/lm/build_binary.cc index 4552c419..b7aee4de 100644 --- a/klm/lm/build_binary.cc +++ b/klm/lm/build_binary.cc @@ -15,12 +15,12 @@ namespace ngram { namespace { void Usage(const char *name) { - std::cerr << "Usage: " << name << " [-u log10_unknown_probability] [-s] [-n] [-p probing_multiplier] [-t trie_temporary] [-m trie_building_megabytes] [-q bits] [-b bits] [type] input.arpa output.mmap\n\n" -"-u sets the default log10 probability for if the ARPA file does not have\n" -"one.\n" + std::cerr << "Usage: " << name << " [-u log10_unknown_probability] [-s] [-i] [-p probing_multiplier] [-t trie_temporary] [-m trie_building_megabytes] [-q bits] [-b bits] [-c bits] [type] input.arpa [output.mmap]\n\n" +"-u sets the log10 probability for if the ARPA file does not have one.\n" +" Default is -100. The ARPA file will always take precedence.\n" "-s allows models to be built even if they do not have and .\n" -"-i allows buggy models from IRSTLM by mapping positive log probability to 0.\n" -"type is either probing or trie:\n\n" +"-i allows buggy models from IRSTLM by mapping positive log probability to 0.\n\n" +"type is either probing or trie. Default is probing.\n\n" "probing uses a probing hash table. It is the fastest but uses the most memory.\n" "-p sets the space multiplier and must be >1.0. The default is 1.5.\n\n" "trie is a straightforward trie with bit-level packing. It uses the least\n" @@ -29,10 +29,11 @@ void Usage(const char *name) { "-t is the temporary directory prefix. Default is the output file name.\n" "-m limits memory use for sorting. Measured in MB. Default is 1024MB.\n" "-q turns quantization on and sets the number of bits (e.g. -q 8).\n" -"-b sets backoff quantization bits. Requires -q and defaults to that value.\n\n" -"See http://kheafield.com/code/kenlm/benchmark/ for data structure benchmarks.\n" -"Passing only an input file will print memory usage of each data structure.\n" -"If the ARPA file does not have , -u sets 's probability; default 0.0.\n"; +"-b sets backoff quantization bits. Requires -q and defaults to that value.\n" +"-a compresses pointers using an array of offsets. The parameter is the\n" +" maximum number of bits encoded by the array. Memory is minimized subject\n" +" to the maximum, so pick 255 to minimize memory.\n\n" +"Get a memory estimate by passing an ARPA file without an output file name.\n"; exit(1); } @@ -63,12 +64,14 @@ void ShowSizes(const char *file, const lm::ngram::Config &config) { std::vector counts; util::FilePiece f(file); lm::ReadARPACounts(f, counts); - std::size_t sizes[3]; + std::size_t sizes[5]; sizes[0] = ProbingModel::Size(counts, config); sizes[1] = TrieModel::Size(counts, config); sizes[2] = QuantTrieModel::Size(counts, config); - std::size_t max_length = *std::max_element(sizes, sizes + 3); - std::size_t min_length = *std::max_element(sizes, sizes + 3); + sizes[3] = ArrayTrieModel::Size(counts, config); + sizes[4] = QuantArrayTrieModel::Size(counts, config); + std::size_t max_length = *std::max_element(sizes, sizes + sizeof(sizes) / sizeof(size_t)); + std::size_t min_length = *std::min_element(sizes, sizes + sizeof(sizes) / sizeof(size_t)); std::size_t divide; char prefix; if (min_length < (1 << 10) * 10) { @@ -91,7 +94,9 @@ void ShowSizes(const char *file, const lm::ngram::Config &config) { std::cout << prefix << "B\n" "probing " << std::setw(length) << (sizes[0] / divide) << " assuming -p " << config.probing_multiplier << "\n" "trie " << std::setw(length) << (sizes[1] / divide) << " without quantization\n" - "trie " << std::setw(length) << (sizes[2] / divide) << " assuming -q " << (unsigned)config.prob_bits << " -b " << (unsigned)config.backoff_bits << " quantization \n"; + "trie " << std::setw(length) << (sizes[2] / divide) << " assuming -q " << (unsigned)config.prob_bits << " -b " << (unsigned)config.backoff_bits << " quantization \n" + "trie " << std::setw(length) << (sizes[3] / divide) << " assuming -a " << (unsigned)config.pointer_bhiksha_bits << " array pointer compression\n" + "trie " << std::setw(length) << (sizes[4] / divide) << " assuming -a " << (unsigned)config.pointer_bhiksha_bits << " -q " << (unsigned)config.prob_bits << " -b " << (unsigned)config.backoff_bits<< " array pointer compression and quantization\n"; } void ProbingQuantizationUnsupported() { @@ -106,11 +111,11 @@ void ProbingQuantizationUnsupported() { int main(int argc, char *argv[]) { using namespace lm::ngram; - bool quantize = false, set_backoff_bits = false; try { + bool quantize = false, set_backoff_bits = false, bhiksha = false; lm::ngram::Config config; int opt; - while ((opt = getopt(argc, argv, "siu:p:t:m:q:b:")) != -1) { + while ((opt = getopt(argc, argv, "siu:p:t:m:q:b:a:")) != -1) { switch(opt) { case 'q': config.prob_bits = ParseBitCount(optarg); @@ -121,6 +126,9 @@ int main(int argc, char *argv[]) { config.backoff_bits = ParseBitCount(optarg); set_backoff_bits = true; break; + case 'a': + config.pointer_bhiksha_bits = ParseBitCount(optarg); + bhiksha = true; case 'u': config.unknown_missing_logprob = ParseFloat(optarg); break; @@ -162,9 +170,17 @@ int main(int argc, char *argv[]) { ProbingModel(from_file, config); } else if (!strcmp(model_type, "trie")) { if (quantize) { - QuantTrieModel(from_file, config); + if (bhiksha) { + QuantArrayTrieModel(from_file, config); + } else { + QuantTrieModel(from_file, config); + } } else { - TrieModel(from_file, config); + if (bhiksha) { + ArrayTrieModel(from_file, config); + } else { + TrieModel(from_file, config); + } } } else { Usage(argv[0]); @@ -173,9 +189,9 @@ int main(int argc, char *argv[]) { Usage(argv[0]); } } - catch (std::exception &e) { + catch (const std::exception &e) { std::cerr << e.what() << std::endl; - abort(); + return 1; } return 0; } diff --git a/klm/lm/config.cc b/klm/lm/config.cc index 08e1af5c..297589a4 100644 --- a/klm/lm/config.cc +++ b/klm/lm/config.cc @@ -20,6 +20,7 @@ Config::Config() : include_vocab(true), prob_bits(8), backoff_bits(8), + pointer_bhiksha_bits(22), load_method(util::POPULATE_OR_READ) {} } // namespace ngram diff --git a/klm/lm/config.hh b/klm/lm/config.hh index dcc7cf35..227b8512 100644 --- a/klm/lm/config.hh +++ b/klm/lm/config.hh @@ -73,9 +73,12 @@ struct Config { // Quantization options. Only effective for QuantTrieModel. One value is // reserved for each of prob and backoff, so 2^bits - 1 buckets will be used - // to quantize. + // to quantize (and one of the remaining backoffs will be 0). uint8_t prob_bits, backoff_bits; + // Bhiksha compression (simple form). Only works with trie. + uint8_t pointer_bhiksha_bits; + // ONLY EFFECTIVE WHEN READING BINARY diff --git a/klm/lm/model.cc b/klm/lm/model.cc index a1d10b3d..27e24b1c 100644 --- a/klm/lm/model.cc +++ b/klm/lm/model.cc @@ -21,6 +21,8 @@ size_t hash_value(const State &state) { namespace detail { +template const ModelType GenericModel::kModelType = Search::kModelType; + template size_t GenericModel::Size(const std::vector &counts, const Config &config) { return VocabularyT::Size(counts[0], config) + Search::Size(counts, config); } @@ -56,35 +58,40 @@ template void GenericModel void GenericModel::InitializeFromARPA(const char *file, const Config &config) { // Backing file is the ARPA. Steal it so we can make the backing file the mmap output if any. util::FilePiece f(backing_.file.release(), file, config.messages); - std::vector counts; - // File counts do not include pruned trigrams that extend to quadgrams etc. These will be fixed by search_. - ReadARPACounts(f, counts); - - if (counts.size() > kMaxOrder) UTIL_THROW(FormatLoadException, "This model has order " << counts.size() << ". Edit lm/max_order.hh, set kMaxOrder to at least this value, and recompile."); - if (counts.size() < 2) UTIL_THROW(FormatLoadException, "This ngram implementation assumes at least a bigram model."); - if (config.probing_multiplier <= 1.0) UTIL_THROW(ConfigException, "probing multiplier must be > 1.0"); - - std::size_t vocab_size = VocabularyT::Size(counts[0], config); - // Setup the binary file for writing the vocab lookup table. The search_ is responsible for growing the binary file to its needs. - vocab_.SetupMemory(SetupJustVocab(config, counts.size(), vocab_size, backing_), vocab_size, counts[0], config); - - if (config.write_mmap) { - WriteWordsWrapper wrap(config.enumerate_vocab); - vocab_.ConfigureEnumerate(&wrap, counts[0]); - search_.InitializeFromARPA(file, f, counts, config, vocab_, backing_); - wrap.Write(backing_.file.get()); - } else { - vocab_.ConfigureEnumerate(config.enumerate_vocab, counts[0]); - search_.InitializeFromARPA(file, f, counts, config, vocab_, backing_); - } + try { + std::vector counts; + // File counts do not include pruned trigrams that extend to quadgrams etc. These will be fixed by search_. + ReadARPACounts(f, counts); + + if (counts.size() > kMaxOrder) UTIL_THROW(FormatLoadException, "This model has order " << counts.size() << ". Edit lm/max_order.hh, set kMaxOrder to at least this value, and recompile."); + if (counts.size() < 2) UTIL_THROW(FormatLoadException, "This ngram implementation assumes at least a bigram model."); + if (config.probing_multiplier <= 1.0) UTIL_THROW(ConfigException, "probing multiplier must be > 1.0"); + + std::size_t vocab_size = VocabularyT::Size(counts[0], config); + // Setup the binary file for writing the vocab lookup table. The search_ is responsible for growing the binary file to its needs. + vocab_.SetupMemory(SetupJustVocab(config, counts.size(), vocab_size, backing_), vocab_size, counts[0], config); + + if (config.write_mmap) { + WriteWordsWrapper wrap(config.enumerate_vocab); + vocab_.ConfigureEnumerate(&wrap, counts[0]); + search_.InitializeFromARPA(file, f, counts, config, vocab_, backing_); + wrap.Write(backing_.file.get()); + } else { + vocab_.ConfigureEnumerate(config.enumerate_vocab, counts[0]); + search_.InitializeFromARPA(file, f, counts, config, vocab_, backing_); + } - if (!vocab_.SawUnk()) { - assert(config.unknown_missing != THROW_UP); - // Default probabilities for unknown. - search_.unigram.Unknown().backoff = 0.0; - search_.unigram.Unknown().prob = config.unknown_missing_logprob; + if (!vocab_.SawUnk()) { + assert(config.unknown_missing != THROW_UP); + // Default probabilities for unknown. + search_.unigram.Unknown().backoff = 0.0; + search_.unigram.Unknown().prob = config.unknown_missing_logprob; + } + FinishFile(config, kModelType, counts, backing_); + } catch (util::Exception &e) { + e << " Byte: " << f.Offset(); + throw; } - FinishFile(config, kModelType, counts, backing_); } template FullScoreReturn GenericModel::FullScore(const State &in_state, const WordIndex new_word, State &out_state) const { @@ -225,8 +232,10 @@ template FullScoreReturn GenericModel; // HASH_PROBING -template class GenericModel, SortedVocabulary>; // TRIE_SORTED -template class GenericModel, SortedVocabulary>; // TRIE_SORTED_QUANT +template class GenericModel, SortedVocabulary>; // TRIE_SORTED +template class GenericModel, SortedVocabulary>; +template class GenericModel, SortedVocabulary>; // TRIE_SORTED_QUANT +template class GenericModel, SortedVocabulary>; } // namespace detail } // namespace ngram diff --git a/klm/lm/model.hh b/klm/lm/model.hh index 1f49a382..21595321 100644 --- a/klm/lm/model.hh +++ b/klm/lm/model.hh @@ -1,6 +1,7 @@ #ifndef LM_MODEL__ #define LM_MODEL__ +#include "lm/bhiksha.hh" #include "lm/binary_format.hh" #include "lm/config.hh" #include "lm/facade.hh" @@ -71,6 +72,9 @@ template class GenericModel : public base::Mod private: typedef base::ModelFacade, State, VocabularyT> P; public: + // This is the model type returned by RecognizeBinary. + static const ModelType kModelType; + /* Get the size of memory that will be mapped given ngram counts. This * does not include small non-mapped control structures, such as this class * itself. @@ -131,8 +135,6 @@ template class GenericModel : public base::Mod Backing &MutableBacking() { return backing_; } - static const ModelType kModelType = Search::kModelType; - Backing backing_; VocabularyT vocab_; @@ -152,9 +154,11 @@ typedef ProbingModel Model; // Smaller implementation. typedef ::lm::ngram::SortedVocabulary SortedVocabulary; -typedef detail::GenericModel, SortedVocabulary> TrieModel; // TRIE_SORTED +typedef detail::GenericModel, SortedVocabulary> TrieModel; // TRIE_SORTED +typedef detail::GenericModel, SortedVocabulary> ArrayTrieModel; -typedef detail::GenericModel, SortedVocabulary> QuantTrieModel; // QUANT_TRIE_SORTED +typedef detail::GenericModel, SortedVocabulary> QuantTrieModel; // QUANT_TRIE_SORTED +typedef detail::GenericModel, SortedVocabulary> QuantArrayTrieModel; } // namespace ngram } // namespace lm diff --git a/klm/lm/model_test.cc b/klm/lm/model_test.cc index 8bf040ff..57c7291c 100644 --- a/klm/lm/model_test.cc +++ b/klm/lm/model_test.cc @@ -193,6 +193,14 @@ template void Stateless(const M &model) { BOOST_CHECK_EQUAL(static_cast(0), state.history_[0]); } +template void NoUnkCheck(const M &model) { + WordIndex unk_index = 0; + State state; + + FullScoreReturn ret = model.FullScoreForgotState(&unk_index, &unk_index + 1, unk_index, state); + BOOST_CHECK_CLOSE(-100.0, ret.prob, 0.001); +} + template void Everything(const M &m) { Starters(m); Continuation(m); @@ -231,25 +239,38 @@ template void LoadingTest() { Config config; config.arpa_complain = Config::NONE; config.messages = NULL; - ExpectEnumerateVocab enumerate; - config.enumerate_vocab = &enumerate; config.probing_multiplier = 2.0; - ModelT m("test.arpa", config); - enumerate.Check(m.GetVocabulary()); - Everything(m); + { + ExpectEnumerateVocab enumerate; + config.enumerate_vocab = &enumerate; + ModelT m("test.arpa", config); + enumerate.Check(m.GetVocabulary()); + Everything(m); + } + { + ExpectEnumerateVocab enumerate; + config.enumerate_vocab = &enumerate; + ModelT m("test_nounk.arpa", config); + enumerate.Check(m.GetVocabulary()); + NoUnkCheck(m); + } } BOOST_AUTO_TEST_CASE(probing) { LoadingTest(); } - BOOST_AUTO_TEST_CASE(trie) { LoadingTest(); } - -BOOST_AUTO_TEST_CASE(quant) { +BOOST_AUTO_TEST_CASE(quant_trie) { LoadingTest(); } +BOOST_AUTO_TEST_CASE(bhiksha_trie) { + LoadingTest(); +} +BOOST_AUTO_TEST_CASE(quant_bhiksha_trie) { + LoadingTest(); +} template void BinaryTest() { Config config; @@ -267,10 +288,34 @@ template void BinaryTest() { config.write_mmap = NULL; - ModelT binary("test.binary", config); - enumerate.Check(binary.GetVocabulary()); - Everything(binary); + ModelType type; + BOOST_REQUIRE(RecognizeBinary("test.binary", type)); + BOOST_CHECK_EQUAL(ModelT::kModelType, type); + + { + ModelT binary("test.binary", config); + enumerate.Check(binary.GetVocabulary()); + Everything(binary); + } unlink("test.binary"); + + // Now test without . + config.write_mmap = "test_nounk.binary"; + config.messages = NULL; + enumerate.Clear(); + { + ModelT copy_model("test_nounk.arpa", config); + enumerate.Check(copy_model.GetVocabulary()); + enumerate.Clear(); + NoUnkCheck(copy_model); + } + config.write_mmap = NULL; + { + ModelT binary("test_nounk.binary", config); + enumerate.Check(binary.GetVocabulary()); + NoUnkCheck(binary); + } + unlink("test_nounk.binary"); } BOOST_AUTO_TEST_CASE(write_and_read_probing) { @@ -282,6 +327,12 @@ BOOST_AUTO_TEST_CASE(write_and_read_trie) { BOOST_AUTO_TEST_CASE(write_and_read_quant_trie) { BinaryTest(); } +BOOST_AUTO_TEST_CASE(write_and_read_array_trie) { + BinaryTest(); +} +BOOST_AUTO_TEST_CASE(write_and_read_quant_array_trie) { + BinaryTest(); +} } // namespace } // namespace ngram diff --git a/klm/lm/ngram_query.cc b/klm/lm/ngram_query.cc index 9454a6d1..d9db4aa2 100644 --- a/klm/lm/ngram_query.cc +++ b/klm/lm/ngram_query.cc @@ -99,6 +99,15 @@ int main(int argc, char *argv[]) { case lm::ngram::TRIE_SORTED: Query(argv[1], sentence_context); break; + case lm::ngram::QUANT_TRIE_SORTED: + Query(argv[1], sentence_context); + break; + case lm::ngram::ARRAY_TRIE_SORTED: + Query(argv[1], sentence_context); + break; + case lm::ngram::QUANT_ARRAY_TRIE_SORTED: + Query(argv[1], sentence_context); + break; case lm::ngram::HASH_SORTED: default: std::cerr << "Unrecognized kenlm model type " << model_type << std::endl; diff --git a/klm/lm/quantize.cc b/klm/lm/quantize.cc index 4bb6b1b8..fd371cc8 100644 --- a/klm/lm/quantize.cc +++ b/klm/lm/quantize.cc @@ -43,6 +43,7 @@ void SeparatelyQuantize::UpdateConfigFromBinary(int fd, const std::vector(0); static void UpdateConfigFromBinary(int, const std::vector &, Config &) {} static std::size_t Size(uint8_t /*order*/, const Config &/*config*/) { return 0; } static uint8_t MiddleBits(const Config &/*config*/) { return 63; } @@ -108,7 +108,7 @@ class SeparatelyQuantize { }; public: - static const ModelType kModelType = QUANT_TRIE_SORTED; + static const ModelType kModelTypeAdd = kQuantAdd; static void UpdateConfigFromBinary(int fd, const std::vector &counts, Config &config); diff --git a/klm/lm/read_arpa.cc b/klm/lm/read_arpa.cc index 060a97ea..455bc4ba 100644 --- a/klm/lm/read_arpa.cc +++ b/klm/lm/read_arpa.cc @@ -31,15 +31,15 @@ const char kBinaryMagic[] = "mmap lm http://kheafield.com/code"; void ReadARPACounts(util::FilePiece &in, std::vector &number) { number.clear(); StringPiece line; - if (!IsEntirelyWhiteSpace(line = in.ReadLine())) { + while (IsEntirelyWhiteSpace(line = in.ReadLine())) {} + if (line != "\\data\\") { if ((line.size() >= 2) && (line.data()[0] == 0x1f) && (static_cast(line.data()[1]) == 0x8b)) { UTIL_THROW(FormatLoadException, "Looks like a gzip file. If this is an ARPA file, pipe " << in.FileName() << " through zcat. If this already in binary format, you need to decompress it because mmap doesn't work on top of gzip."); } if (static_cast(line.size()) >= strlen(kBinaryMagic) && StringPiece(line.data(), strlen(kBinaryMagic)) == kBinaryMagic) UTIL_THROW(FormatLoadException, "This looks like a binary file but got sent to the ARPA parser. Did you compress the binary file or pass a binary file where only ARPA files are accepted?"); - UTIL_THROW(FormatLoadException, "First line was \"" << line.data() << "\" not blank"); + UTIL_THROW(FormatLoadException, "first non-empty line was \"" << line << "\" not \\data\\."); } - if ((line = in.ReadLine()) != "\\data\\") UTIL_THROW(FormatLoadException, "second line was \"" << line << "\" not \\data\\."); while (!IsEntirelyWhiteSpace(line = in.ReadLine())) { if (line.size() < 6 || strncmp(line.data(), "ngram ", 6)) UTIL_THROW(FormatLoadException, "count line \"" << line << "\"doesn't begin with \"ngram \""); // So strtol doesn't go off the end of line. diff --git a/klm/lm/search_hashed.cc b/klm/lm/search_hashed.cc index c56ba7b8..82c53ec8 100644 --- a/klm/lm/search_hashed.cc +++ b/klm/lm/search_hashed.cc @@ -98,7 +98,7 @@ template uint8_t *TemplateHashedSearch template void TemplateHashedSearch::InitializeFromARPA(const char * /*file*/, util::FilePiece &f, const std::vector &counts, const Config &config, Voc &vocab, Backing &backing) { // TODO: fix sorted. - SetupMemory(GrowForSearch(config, Size(counts, config), backing), counts, config); + SetupMemory(GrowForSearch(config, 0, Size(counts, config), backing), counts, config); PositiveProbWarn warn(config.positive_log_probability); diff --git a/klm/lm/search_hashed.hh b/klm/lm/search_hashed.hh index f3acdefc..c62985e4 100644 --- a/klm/lm/search_hashed.hh +++ b/klm/lm/search_hashed.hh @@ -52,12 +52,11 @@ struct HashedSearch { Unigram unigram; - bool LookupUnigram(WordIndex word, float &prob, float &backoff, Node &next) const { + void LookupUnigram(WordIndex word, float &prob, float &backoff, Node &next) const { const ProbBackoff &entry = unigram.Lookup(word); prob = entry.prob; backoff = entry.backoff; next = static_cast(word); - return true; } }; diff --git a/klm/lm/search_trie.cc b/klm/lm/search_trie.cc index 91f87f1c..05059ffb 100644 --- a/klm/lm/search_trie.cc +++ b/klm/lm/search_trie.cc @@ -1,6 +1,7 @@ /* This is where the trie is built. It's on-disk. */ #include "lm/search_trie.hh" +#include "lm/bhiksha.hh" #include "lm/blank.hh" #include "lm/lm_exception.hh" #include "lm/max_order.hh" @@ -543,8 +544,8 @@ void ARPAToSortedFiles(const Config &config, util::FilePiece &f, std::vector appears. - size_t extra_count = counts[0] + 1; - util::scoped_mmap unigram_mmap(util::MapZeroedWrite(unigram_name.c_str(), extra_count * sizeof(ProbBackoff), unigram_file), extra_count * sizeof(ProbBackoff)); + size_t file_out = (counts[0] + 1) * sizeof(ProbBackoff); + util::scoped_mmap unigram_mmap(util::MapZeroedWrite(unigram_name.c_str(), file_out, unigram_file), file_out); Read1Grams(f, counts[0], vocab, reinterpret_cast(unigram_mmap.get()), warn); CheckSpecials(config, vocab); if (!vocab.SawUnk()) ++counts[0]; @@ -610,9 +611,9 @@ class JustCount { }; // Phase to actually write n-grams to the trie. -template class WriteEntries { +template class WriteEntries { public: - WriteEntries(ContextReader *contexts, UnigramValue *unigrams, BitPackedMiddle *middle, BitPackedLongest &longest, const uint64_t * /*counts*/, unsigned char order) : + WriteEntries(ContextReader *contexts, UnigramValue *unigrams, BitPackedMiddle *middle, BitPackedLongest &longest, const uint64_t * /*counts*/, unsigned char order) : contexts_(contexts), unigrams_(unigrams), middle_(middle), @@ -649,7 +650,7 @@ template class WriteEntries { private: ContextReader *contexts_; UnigramValue *const unigrams_; - BitPackedMiddle *const middle_; + BitPackedMiddle *const middle_; BitPackedLongest &longest_; BitPacked &bigram_pack_; }; @@ -821,7 +822,7 @@ template void TrainProbQuantizer(uint8_t order, uint64_t count, So } // namespace -template void BuildTrie(const std::string &file_prefix, std::vector &counts, const Config &config, TrieSearch &out, Quant &quant, Backing &backing) { +template void BuildTrie(const std::string &file_prefix, std::vector &counts, const Config &config, TrieSearch &out, Quant &quant, const SortedVocabulary &vocab, Backing &backing) { std::vector inputs(counts.size() - 1); std::vector contexts(counts.size() - 1); @@ -846,7 +847,7 @@ template void BuildTrie(const std::string &file_prefix, std::vecto SanityCheckCounts(counts, fixed_counts); counts = fixed_counts; - out.SetupMemory(GrowForSearch(config, TrieSearch::Size(fixed_counts, config), backing), fixed_counts, config); + out.SetupMemory(GrowForSearch(config, vocab.UnkCountChangePadding(), TrieSearch::Size(fixed_counts, config), backing), fixed_counts, config); if (Quant::kTrain) { util::ErsatzProgress progress(config.messages, "Quantizing", std::accumulate(counts.begin() + 1, counts.end(), 0)); @@ -863,7 +864,7 @@ template void BuildTrie(const std::string &file_prefix, std::vecto UnigramValue *unigrams = out.unigram.Raw(); // Fill entries except unigram probabilities. { - RecursiveInsert > inserter(&*inputs.begin(), &*contexts.begin(), unigrams, out.middle_begin_, out.longest, &*fixed_counts.begin(), counts.size()); + RecursiveInsert > inserter(&*inputs.begin(), &*contexts.begin(), unigrams, out.middle_begin_, out.longest, &*fixed_counts.begin(), counts.size()); inserter.Apply(config.messages, "Building trie", fixed_counts[0]); } @@ -901,14 +902,14 @@ template void BuildTrie(const std::string &file_prefix, std::vecto /* Set ending offsets so the last entry will be sized properly */ // Last entry for unigrams was already set. if (out.middle_begin_ != out.middle_end_) { - for (typename TrieSearch::Middle *i = out.middle_begin_; i != out.middle_end_ - 1; ++i) { - i->FinishedLoading((i+1)->InsertIndex()); + for (typename TrieSearch::Middle *i = out.middle_begin_; i != out.middle_end_ - 1; ++i) { + i->FinishedLoading((i+1)->InsertIndex(), config); } - (out.middle_end_ - 1)->FinishedLoading(out.longest.InsertIndex()); + (out.middle_end_ - 1)->FinishedLoading(out.longest.InsertIndex(), config); } } -template uint8_t *TrieSearch::SetupMemory(uint8_t *start, const std::vector &counts, const Config &config) { +template uint8_t *TrieSearch::SetupMemory(uint8_t *start, const std::vector &counts, const Config &config) { quant_.SetupMemory(start, config); start += Quant::Size(counts.size(), config); unigram.Init(start); @@ -919,22 +920,24 @@ template uint8_t *TrieSearch::SetupMemory(uint8_t *start, c std::vector middle_starts(counts.size() - 2); for (unsigned char i = 2; i < counts.size(); ++i) { middle_starts[i-2] = start; - start += Middle::Size(Quant::MiddleBits(config), counts[i-1], counts[0], counts[i]); + start += Middle::Size(Quant::MiddleBits(config), counts[i-1], counts[0], counts[i], config); } - // Crazy backwards thing so we initialize in the correct order. + // Crazy backwards thing so we initialize using pointers to ones that have already been initialized for (unsigned char i = counts.size() - 1; i >= 2; --i) { new (middle_begin_ + i - 2) Middle( middle_starts[i-2], quant_.Mid(i), + counts[i-1], counts[0], counts[i], - (i == counts.size() - 1) ? static_cast(longest) : static_cast(middle_begin_[i-1])); + (i == counts.size() - 1) ? static_cast(longest) : static_cast(middle_begin_[i-1]), + config); } longest.Init(start, quant_.Long(counts.size()), counts[0]); return start + Longest::Size(Quant::LongestBits(config), counts.back(), counts[0]); } -template void TrieSearch::LoadedBinary() { +template void TrieSearch::LoadedBinary() { unigram.LoadedBinary(); for (Middle *i = middle_begin_; i != middle_end_; ++i) { i->LoadedBinary(); @@ -942,7 +945,7 @@ template void TrieSearch::LoadedBinary() { longest.LoadedBinary(); } -template void TrieSearch::InitializeFromARPA(const char *file, util::FilePiece &f, std::vector &counts, const Config &config, SortedVocabulary &vocab, Backing &backing) { +template void TrieSearch::InitializeFromARPA(const char *file, util::FilePiece &f, std::vector &counts, const Config &config, SortedVocabulary &vocab, Backing &backing) { std::string temporary_directory; if (config.temporary_directory_prefix) { temporary_directory = config.temporary_directory_prefix; @@ -966,14 +969,16 @@ template void TrieSearch::InitializeFromARPA(const char *fi // At least 1MB sorting memory. ARPAToSortedFiles(config, f, counts, std::max(config.building_memory, 1048576), temporary_directory.c_str(), vocab); - BuildTrie(temporary_directory, counts, config, *this, quant_, backing); + BuildTrie(temporary_directory, counts, config, *this, quant_, vocab, backing); if (rmdir(temporary_directory.c_str()) && config.messages) { *config.messages << "Failed to delete " << temporary_directory << std::endl; } } -template class TrieSearch; -template class TrieSearch; +template class TrieSearch; +template class TrieSearch; +template class TrieSearch; +template class TrieSearch; } // namespace trie } // namespace ngram diff --git a/klm/lm/search_trie.hh b/klm/lm/search_trie.hh index 0a52acb5..2f39c09f 100644 --- a/klm/lm/search_trie.hh +++ b/klm/lm/search_trie.hh @@ -13,31 +13,33 @@ struct Backing; class SortedVocabulary; namespace trie { -template class TrieSearch; -template void BuildTrie(const std::string &file_prefix, std::vector &counts, const Config &config, TrieSearch &out, Quant &quant, Backing &backing); +template class TrieSearch; +template void BuildTrie(const std::string &file_prefix, std::vector &counts, const Config &config, TrieSearch &out, Quant &quant, const SortedVocabulary &vocab, Backing &backing); -template class TrieSearch { +template class TrieSearch { public: typedef NodeRange Node; typedef ::lm::ngram::trie::Unigram Unigram; Unigram unigram; - typedef trie::BitPackedMiddle Middle; + typedef trie::BitPackedMiddle Middle; typedef trie::BitPackedLongest Longest; Longest longest; - static const ModelType kModelType = Quant::kModelType; + static const ModelType kModelType = static_cast(TRIE_SORTED + Quant::kModelTypeAdd + Bhiksha::kModelTypeAdd); static void UpdateConfigFromBinary(int fd, const std::vector &counts, Config &config) { Quant::UpdateConfigFromBinary(fd, counts, config); + AdvanceOrThrow(fd, Quant::Size(counts.size(), config) + Unigram::Size(counts[0])); + Bhiksha::UpdateConfigFromBinary(fd, config); } static std::size_t Size(const std::vector &counts, const Config &config) { std::size_t ret = Quant::Size(counts.size(), config) + Unigram::Size(counts[0]); for (unsigned char i = 1; i < counts.size() - 1; ++i) { - ret += Middle::Size(Quant::MiddleBits(config), counts[i], counts[0], counts[i+1]); + ret += Middle::Size(Quant::MiddleBits(config), counts[i], counts[0], counts[i+1], config); } return ret + Longest::Size(Quant::LongestBits(config), counts.back(), counts[0]); } @@ -55,8 +57,8 @@ template class TrieSearch { void InitializeFromARPA(const char *file, util::FilePiece &f, std::vector &counts, const Config &config, SortedVocabulary &vocab, Backing &backing); - bool LookupUnigram(WordIndex word, float &prob, float &backoff, Node &node) const { - return unigram.Find(word, prob, backoff, node); + void LookupUnigram(WordIndex word, float &prob, float &backoff, Node &node) const { + unigram.Find(word, prob, backoff, node); } bool LookupMiddle(const Middle &mid, WordIndex word, float &prob, float &backoff, Node &node) const { @@ -83,7 +85,7 @@ template class TrieSearch { } private: - friend void BuildTrie(const std::string &file_prefix, std::vector &counts, const Config &config, TrieSearch &out, Quant &quant, Backing &backing); + friend void BuildTrie(const std::string &file_prefix, std::vector &counts, const Config &config, TrieSearch &out, Quant &quant, const SortedVocabulary &vocab, Backing &backing); // Middles are managed manually so we can delay construction and they don't have to be copyable. void FreeMiddles() { diff --git a/klm/lm/test_nounk.arpa b/klm/lm/test_nounk.arpa new file mode 100644 index 00000000..060733d9 --- /dev/null +++ b/klm/lm/test_nounk.arpa @@ -0,0 +1,120 @@ + +\data\ +ngram 1=36 +ngram 2=45 +ngram 3=10 +ngram 4=6 +ngram 5=4 + +\1-grams: +-1.383514 , -0.30103 +-1.139057 . -0.845098 +-1.029493 +-99 -0.4149733 +-1.285941 a -0.69897 +-1.687872 also -0.30103 +-1.687872 beyond -0.30103 +-1.687872 biarritz -0.30103 +-1.687872 call -0.30103 +-1.687872 concerns -0.30103 +-1.687872 consider -0.30103 +-1.687872 considering -0.30103 +-1.687872 for -0.30103 +-1.509559 higher -0.30103 +-1.687872 however -0.30103 +-1.687872 i -0.30103 +-1.687872 immediate -0.30103 +-1.687872 in -0.30103 +-1.687872 is -0.30103 +-1.285941 little -0.69897 +-1.383514 loin -0.30103 +-1.687872 look -0.30103 +-1.285941 looking -0.4771212 +-1.206319 more -0.544068 +-1.509559 on -0.4771212 +-1.509559 screening -0.4771212 +-1.687872 small -0.30103 +-1.687872 the -0.30103 +-1.687872 to -0.30103 +-1.687872 watch -0.30103 +-1.687872 watching -0.30103 +-1.687872 what -0.30103 +-1.687872 would -0.30103 +-3.141592 foo +-2.718281 bar 3.0 +-6.535897 baz -0.0 + +\2-grams: +-0.6925742 , . +-0.7522095 , however +-0.7522095 , is +-0.0602359 . +-0.4846522 looking -0.4771214 +-1.051485 screening +-1.07153 the +-1.07153 watching +-1.07153 what +-0.09132547 a little -0.69897 +-0.2922095 also call +-0.2922095 beyond immediate +-0.2705918 biarritz . +-0.2922095 call for +-0.2922095 concerns in +-0.2922095 consider watch +-0.2922095 considering consider +-0.2834328 for , +-0.5511513 higher more +-0.5845945 higher small +-0.2834328 however , +-0.2922095 i would +-0.2922095 immediate concerns +-0.2922095 in biarritz +-0.2922095 is to +-0.09021038 little more -0.1998621 +-0.7273645 loin , +-0.6925742 loin . +-0.6708385 loin +-0.2922095 look beyond +-0.4638903 looking higher +-0.4638903 looking on -0.4771212 +-0.5136299 more . -0.4771212 +-0.3561665 more loin +-0.1649931 on a -0.4771213 +-0.1649931 screening a -0.4771213 +-0.2705918 small . +-0.287799 the screening +-0.2922095 to look +-0.2622373 watch +-0.2922095 watching considering +-0.2922095 what i +-0.2922095 would also +-2 also would -6 +-6 foo bar + +\3-grams: +-0.01916512 more . +-0.0283603 on a little -0.4771212 +-0.0283603 screening a little -0.4771212 +-0.01660496 a little more -0.09409451 +-0.3488368 looking higher +-0.3488368 looking on -0.4771212 +-0.1892331 little more loin +-0.04835128 looking on a -0.4771212 +-3 also would consider -7 +-7 to look good + +\4-grams: +-0.009249173 looking on a little -0.4771212 +-0.005464747 on a little more -0.4771212 +-0.005464747 screening a little more +-0.1453306 a little more loin +-0.01552657 looking on a -0.4771212 +-4 also would consider higher -8 + +\5-grams: +-0.003061223 looking on a little +-0.001813953 looking on a little more +-0.0432557 on a little more loin +-5 also would consider higher looking + +\end\ diff --git a/klm/lm/trie.cc b/klm/lm/trie.cc index 63c2a612..8c536e66 100644 --- a/klm/lm/trie.cc +++ b/klm/lm/trie.cc @@ -1,5 +1,6 @@ #include "lm/trie.hh" +#include "lm/bhiksha.hh" #include "lm/quantize.hh" #include "util/bit_packing.hh" #include "util/exception.hh" @@ -57,16 +58,21 @@ void BitPacked::BaseInit(void *base, uint64_t max_vocab, uint8_t remaining_bits) max_vocab_ = max_vocab; } -template std::size_t BitPackedMiddle::Size(uint8_t quant_bits, uint64_t entries, uint64_t max_vocab, uint64_t max_ptr) { - return BaseSize(entries, max_vocab, quant_bits + util::RequiredBits(max_ptr)); +template std::size_t BitPackedMiddle::Size(uint8_t quant_bits, uint64_t entries, uint64_t max_vocab, uint64_t max_ptr, const Config &config) { + return Bhiksha::Size(entries + 1, max_ptr, config) + BaseSize(entries, max_vocab, quant_bits + Bhiksha::InlineBits(entries + 1, max_ptr, config)); } -template BitPackedMiddle::BitPackedMiddle(void *base, const Quant &quant, uint64_t max_vocab, uint64_t max_next, const BitPacked &next_source) : BitPacked(), quant_(quant), next_bits_(util::RequiredBits(max_next)), next_mask_((1ULL << next_bits_) - 1), next_source_(&next_source) { - if (next_bits_ > 57) UTIL_THROW(util::Exception, "Sorry, this does not support more than " << (1ULL << 57) << " n-grams of a particular order. Edit util/bit_packing.hh and fix the bit packing functions."); - BaseInit(base, max_vocab, quant.TotalBits() + next_bits_); +template BitPackedMiddle::BitPackedMiddle(void *base, const Quant &quant, uint64_t entries, uint64_t max_vocab, uint64_t max_next, const BitPacked &next_source, const Config &config) : + BitPacked(), + quant_(quant), + // If the offset of the method changes, also change TrieSearch::UpdateConfigFromBinary. + bhiksha_(base, entries + 1, max_next, config), + next_source_(&next_source) { + if (entries + 1 >= (1ULL << 57) || (max_next >= (1ULL << 57))) UTIL_THROW(util::Exception, "Sorry, this does not support more than " << (1ULL << 57) << " n-grams of a particular order. Edit util/bit_packing.hh and fix the bit packing functions."); + BaseInit(reinterpret_cast(base) + Bhiksha::Size(entries + 1, max_next, config), max_vocab, quant.TotalBits() + bhiksha_.InlineBits()); } -template void BitPackedMiddle::Insert(WordIndex word, float prob, float backoff) { +template void BitPackedMiddle::Insert(WordIndex word, float prob, float backoff) { assert(word <= word_mask_); uint64_t at_pointer = insert_index_ * total_bits_; @@ -75,47 +81,42 @@ template void BitPackedMiddle::Insert(WordIndex word, float quant_.Write(base_, at_pointer, prob, backoff); at_pointer += quant_.TotalBits(); uint64_t next = next_source_->InsertIndex(); - assert(next <= next_mask_); - util::WriteInt57(base_, at_pointer, next_bits_, next); + bhiksha_.WriteNext(base_, at_pointer, insert_index_, next); ++insert_index_; } -template bool BitPackedMiddle::Find(WordIndex word, float &prob, float &backoff, NodeRange &range) const { +template bool BitPackedMiddle::Find(WordIndex word, float &prob, float &backoff, NodeRange &range) const { uint64_t at_pointer; if (!FindBitPacked(base_, word_mask_, word_bits_, total_bits_, range.begin, range.end, max_vocab_, word, at_pointer)) { return false; } + uint64_t index = at_pointer; at_pointer *= total_bits_; at_pointer += word_bits_; quant_.Read(base_, at_pointer, prob, backoff); at_pointer += quant_.TotalBits(); - range.begin = util::ReadInt57(base_, at_pointer, next_bits_, next_mask_); - // Read the next entry's pointer. - at_pointer += total_bits_; - range.end = util::ReadInt57(base_, at_pointer, next_bits_, next_mask_); + bhiksha_.ReadNext(base_, at_pointer, index, total_bits_, range); + return true; } -template bool BitPackedMiddle::FindNoProb(WordIndex word, float &backoff, NodeRange &range) const { - uint64_t at_pointer; - if (!FindBitPacked(base_, word_mask_, word_bits_, total_bits_, range.begin, range.end, max_vocab_, word, at_pointer)) return false; - at_pointer *= total_bits_; +template bool BitPackedMiddle::FindNoProb(WordIndex word, float &backoff, NodeRange &range) const { + uint64_t index; + if (!FindBitPacked(base_, word_mask_, word_bits_, total_bits_, range.begin, range.end, max_vocab_, word, index)) return false; + uint64_t at_pointer = index * total_bits_; at_pointer += word_bits_; quant_.ReadBackoff(base_, at_pointer, backoff); at_pointer += quant_.TotalBits(); - range.begin = util::ReadInt57(base_, at_pointer, next_bits_, next_mask_); - // Read the next entry's pointer. - at_pointer += total_bits_; - range.end = util::ReadInt57(base_, at_pointer, next_bits_, next_mask_); + bhiksha_.ReadNext(base_, at_pointer, index, total_bits_, range); return true; } -template void BitPackedMiddle::FinishedLoading(uint64_t next_end) { - assert(next_end <= next_mask_); - uint64_t last_next_write = (insert_index_ + 1) * total_bits_ - next_bits_; - util::WriteInt57(base_, last_next_write, next_bits_, next_end); +template void BitPackedMiddle::FinishedLoading(uint64_t next_end, const Config &config) { + uint64_t last_next_write = (insert_index_ + 1) * total_bits_ - bhiksha_.InlineBits(); + bhiksha_.WriteNext(base_, last_next_write, insert_index_ + 1, next_end); + bhiksha_.FinishedLoading(config); } template void BitPackedLongest::Insert(WordIndex index, float prob) { @@ -135,8 +136,10 @@ template bool BitPackedLongest::Find(WordIndex word, float return true; } -template class BitPackedMiddle; -template class BitPackedMiddle; +template class BitPackedMiddle; +template class BitPackedMiddle; +template class BitPackedMiddle; +template class BitPackedMiddle; template class BitPackedLongest; template class BitPackedLongest; diff --git a/klm/lm/trie.hh b/klm/lm/trie.hh index 8fa21aaf..53612064 100644 --- a/klm/lm/trie.hh +++ b/klm/lm/trie.hh @@ -10,6 +10,7 @@ namespace lm { namespace ngram { +class Config; namespace trie { struct NodeRange { @@ -46,13 +47,12 @@ class Unigram { void LoadedBinary() {} - bool Find(WordIndex word, float &prob, float &backoff, NodeRange &next) const { + void Find(WordIndex word, float &prob, float &backoff, NodeRange &next) const { UnigramValue *val = unigram_ + word; prob = val->weights.prob; backoff = val->weights.backoff; next.begin = val->next; next.end = (val+1)->next; - return true; } private: @@ -67,8 +67,6 @@ class BitPacked { return insert_index_; } - void LoadedBinary() {} - protected: static std::size_t BaseSize(uint64_t entries, uint64_t max_vocab, uint8_t remaining_bits); @@ -83,30 +81,30 @@ class BitPacked { uint64_t insert_index_, max_vocab_; }; -template class BitPackedMiddle : public BitPacked { +template class BitPackedMiddle : public BitPacked { public: - static std::size_t Size(uint8_t quant_bits, uint64_t entries, uint64_t max_vocab, uint64_t max_next); + static std::size_t Size(uint8_t quant_bits, uint64_t entries, uint64_t max_vocab, uint64_t max_next, const Config &config); // next_source need not be initialized. - BitPackedMiddle(void *base, const Quant &quant, uint64_t max_vocab, uint64_t max_next, const BitPacked &next_source); + BitPackedMiddle(void *base, const Quant &quant, uint64_t entries, uint64_t max_vocab, uint64_t max_next, const BitPacked &next_source, const Config &config); void Insert(WordIndex word, float prob, float backoff); + void FinishedLoading(uint64_t next_end, const Config &config); + + void LoadedBinary() { bhiksha_.LoadedBinary(); } + bool Find(WordIndex word, float &prob, float &backoff, NodeRange &range) const; bool FindNoProb(WordIndex word, float &backoff, NodeRange &range) const; - void FinishedLoading(uint64_t next_end); - private: Quant quant_; - uint8_t next_bits_; - uint64_t next_mask_; + Bhiksha bhiksha_; const BitPacked *next_source_; }; - template class BitPackedLongest : public BitPacked { public: static std::size_t Size(uint8_t quant_bits, uint64_t entries, uint64_t max_vocab) { @@ -120,6 +118,8 @@ template class BitPackedLongest : public BitPacked { BaseInit(base, max_vocab, quant_.TotalBits()); } + void LoadedBinary() {} + void Insert(WordIndex word, float prob); bool Find(WordIndex word, float &prob, const NodeRange &node) const; diff --git a/klm/lm/vocab.cc b/klm/lm/vocab.cc index 7defd5c1..04979d51 100644 --- a/klm/lm/vocab.cc +++ b/klm/lm/vocab.cc @@ -37,14 +37,14 @@ WordIndex ReadWords(int fd, EnumerateVocab *enumerate) { WordIndex index = 0; while (true) { ssize_t got = read(fd, &buf[0], kInitialRead); - if (got == -1) UTIL_THROW(util::ErrnoException, "Reading vocabulary words"); + UTIL_THROW_IF(got == -1, util::ErrnoException, "Reading vocabulary words"); if (got == 0) return index; buf.resize(got); while (buf[buf.size() - 1]) { char next_char; ssize_t ret = read(fd, &next_char, 1); - if (ret == -1) UTIL_THROW(util::ErrnoException, "Reading vocabulary words"); - if (ret == 0) UTIL_THROW(FormatLoadException, "Missing null terminator on a vocab word."); + UTIL_THROW_IF(ret == -1, util::ErrnoException, "Reading vocabulary words"); + UTIL_THROW_IF(ret == 0, FormatLoadException, "Missing null terminator on a vocab word."); buf.push_back(next_char); } // Ok now we have null terminated strings. diff --git a/klm/lm/vocab.hh b/klm/lm/vocab.hh index c92518e4..9d218fff 100644 --- a/klm/lm/vocab.hh +++ b/klm/lm/vocab.hh @@ -61,6 +61,7 @@ class SortedVocabulary : public base::Vocabulary { } } + // Size for purposes of file writing static size_t Size(std::size_t entries, const Config &config); // Vocab words are [0, Bound()) Only valid after FinishedLoading/LoadedBinary. @@ -77,6 +78,9 @@ class SortedVocabulary : public base::Vocabulary { // Reorders reorder_vocab so that the IDs are sorted. void FinishedLoading(ProbBackoff *reorder_vocab); + // Trie stores the correct counts including in the header. If this was previously sized based on a count exluding , padding with 8 bytes will make it the correct size based on a count including . + std::size_t UnkCountChangePadding() const { return SawUnk() ? 0 : sizeof(uint64_t); } + bool SawUnk() const { return saw_unk_; } void LoadedBinary(int fd, EnumerateVocab *to); diff --git a/klm/util/bit_packing.hh b/klm/util/bit_packing.hh index b35d80c8..9f47d559 100644 --- a/klm/util/bit_packing.hh +++ b/klm/util/bit_packing.hh @@ -107,9 +107,20 @@ void BitPackingSanity(); uint8_t RequiredBits(uint64_t max_value); struct BitsMask { + static BitsMask ByMax(uint64_t max_value) { + BitsMask ret; + ret.FromMax(max_value); + return ret; + } + static BitsMask ByBits(uint8_t bits) { + BitsMask ret; + ret.bits = bits; + ret.mask = (1ULL << bits) - 1; + return ret; + } void FromMax(uint64_t max_value) { bits = RequiredBits(max_value); - mask = (1 << bits) - 1; + mask = (1ULL << bits) - 1; } uint8_t bits; uint64_t mask; diff --git a/klm/util/murmur_hash.cc b/klm/util/murmur_hash.cc index d58a0727..fec47fd9 100644 --- a/klm/util/murmur_hash.cc +++ b/klm/util/murmur_hash.cc @@ -1,129 +1,129 @@ -/* Downloaded from http://sites.google.com/site/murmurhash/ which says "All - * code is released to the public domain. For business purposes, Murmurhash is - * under the MIT license." - * This is modified from the original: - * ULL tag on 0xc6a4a7935bd1e995 so this will compile on 32-bit. - * length changed to unsigned int. - * placed in namespace util - * add MurmurHashNative - * default option = 0 for seed - */ - -#include "util/murmur_hash.hh" - -namespace util { - -//----------------------------------------------------------------------------- -// MurmurHash2, 64-bit versions, by Austin Appleby - -// The same caveats as 32-bit MurmurHash2 apply here - beware of alignment -// and endian-ness issues if used across multiple platforms. - -// 64-bit hash for 64-bit platforms - -uint64_t MurmurHash64A ( const void * key, std::size_t len, unsigned int seed ) -{ - const uint64_t m = 0xc6a4a7935bd1e995ULL; - const int r = 47; - - uint64_t h = seed ^ (len * m); - - const uint64_t * data = (const uint64_t *)key; - const uint64_t * end = data + (len/8); - - while(data != end) - { - uint64_t k = *data++; - - k *= m; - k ^= k >> r; - k *= m; - - h ^= k; - h *= m; - } - - const unsigned char * data2 = (const unsigned char*)data; - - switch(len & 7) - { - case 7: h ^= uint64_t(data2[6]) << 48; - case 6: h ^= uint64_t(data2[5]) << 40; - case 5: h ^= uint64_t(data2[4]) << 32; - case 4: h ^= uint64_t(data2[3]) << 24; - case 3: h ^= uint64_t(data2[2]) << 16; - case 2: h ^= uint64_t(data2[1]) << 8; - case 1: h ^= uint64_t(data2[0]); - h *= m; - }; - - h ^= h >> r; - h *= m; - h ^= h >> r; - - return h; -} - - -// 64-bit hash for 32-bit platforms - -uint64_t MurmurHash64B ( const void * key, std::size_t len, unsigned int seed ) -{ - const unsigned int m = 0x5bd1e995; - const int r = 24; - - unsigned int h1 = seed ^ len; - unsigned int h2 = 0; - - const unsigned int * data = (const unsigned int *)key; - - while(len >= 8) - { - unsigned int k1 = *data++; - k1 *= m; k1 ^= k1 >> r; k1 *= m; - h1 *= m; h1 ^= k1; - len -= 4; - - unsigned int k2 = *data++; - k2 *= m; k2 ^= k2 >> r; k2 *= m; - h2 *= m; h2 ^= k2; - len -= 4; - } - - if(len >= 4) - { - unsigned int k1 = *data++; - k1 *= m; k1 ^= k1 >> r; k1 *= m; - h1 *= m; h1 ^= k1; - len -= 4; - } - - switch(len) - { - case 3: h2 ^= ((unsigned char*)data)[2] << 16; - case 2: h2 ^= ((unsigned char*)data)[1] << 8; - case 1: h2 ^= ((unsigned char*)data)[0]; - h2 *= m; - }; - - h1 ^= h2 >> 18; h1 *= m; - h2 ^= h1 >> 22; h2 *= m; - h1 ^= h2 >> 17; h1 *= m; - h2 ^= h1 >> 19; h2 *= m; - - uint64_t h = h1; - - h = (h << 32) | h2; - - return h; -} - -uint64_t MurmurHashNative(const void * key, std::size_t len, unsigned int seed) { - if (sizeof(int) == 4) { - return MurmurHash64B(key, len, seed); - } else { - return MurmurHash64A(key, len, seed); - } -} - -} // namespace util +/* Downloaded from http://sites.google.com/site/murmurhash/ which says "All + * code is released to the public domain. For business purposes, Murmurhash is + * under the MIT license." + * This is modified from the original: + * ULL tag on 0xc6a4a7935bd1e995 so this will compile on 32-bit. + * length changed to unsigned int. + * placed in namespace util + * add MurmurHashNative + * default option = 0 for seed + */ + +#include "util/murmur_hash.hh" + +namespace util { + +//----------------------------------------------------------------------------- +// MurmurHash2, 64-bit versions, by Austin Appleby + +// The same caveats as 32-bit MurmurHash2 apply here - beware of alignment +// and endian-ness issues if used across multiple platforms. + +// 64-bit hash for 64-bit platforms + +uint64_t MurmurHash64A ( const void * key, std::size_t len, unsigned int seed ) +{ + const uint64_t m = 0xc6a4a7935bd1e995ULL; + const int r = 47; + + uint64_t h = seed ^ (len * m); + + const uint64_t * data = (const uint64_t *)key; + const uint64_t * end = data + (len/8); + + while(data != end) + { + uint64_t k = *data++; + + k *= m; + k ^= k >> r; + k *= m; + + h ^= k; + h *= m; + } + + const unsigned char * data2 = (const unsigned char*)data; + + switch(len & 7) + { + case 7: h ^= uint64_t(data2[6]) << 48; + case 6: h ^= uint64_t(data2[5]) << 40; + case 5: h ^= uint64_t(data2[4]) << 32; + case 4: h ^= uint64_t(data2[3]) << 24; + case 3: h ^= uint64_t(data2[2]) << 16; + case 2: h ^= uint64_t(data2[1]) << 8; + case 1: h ^= uint64_t(data2[0]); + h *= m; + }; + + h ^= h >> r; + h *= m; + h ^= h >> r; + + return h; +} + + +// 64-bit hash for 32-bit platforms + +uint64_t MurmurHash64B ( const void * key, std::size_t len, unsigned int seed ) +{ + const unsigned int m = 0x5bd1e995; + const int r = 24; + + unsigned int h1 = seed ^ len; + unsigned int h2 = 0; + + const unsigned int * data = (const unsigned int *)key; + + while(len >= 8) + { + unsigned int k1 = *data++; + k1 *= m; k1 ^= k1 >> r; k1 *= m; + h1 *= m; h1 ^= k1; + len -= 4; + + unsigned int k2 = *data++; + k2 *= m; k2 ^= k2 >> r; k2 *= m; + h2 *= m; h2 ^= k2; + len -= 4; + } + + if(len >= 4) + { + unsigned int k1 = *data++; + k1 *= m; k1 ^= k1 >> r; k1 *= m; + h1 *= m; h1 ^= k1; + len -= 4; + } + + switch(len) + { + case 3: h2 ^= ((unsigned char*)data)[2] << 16; + case 2: h2 ^= ((unsigned char*)data)[1] << 8; + case 1: h2 ^= ((unsigned char*)data)[0]; + h2 *= m; + }; + + h1 ^= h2 >> 18; h1 *= m; + h2 ^= h1 >> 22; h2 *= m; + h1 ^= h2 >> 17; h1 *= m; + h2 ^= h1 >> 19; h2 *= m; + + uint64_t h = h1; + + h = (h << 32) | h2; + + return h; +} + +uint64_t MurmurHashNative(const void * key, std::size_t len, unsigned int seed) { + if (sizeof(int) == 4) { + return MurmurHash64B(key, len, seed); + } else { + return MurmurHash64A(key, len, seed); + } +} + +} // namespace util diff --git a/klm/util/probing_hash_table.hh b/klm/util/probing_hash_table.hh index 00be0ed7..2ec342a6 100644 --- a/klm/util/probing_hash_table.hh +++ b/klm/util/probing_hash_table.hh @@ -57,7 +57,7 @@ template class IdentityAccessor { public: typedef T Key; - T operator()(const uint64_t *in) const { return *in; } + T operator()(const T *in) const { return *in; } }; struct Pivot64 { @@ -101,6 +101,27 @@ template bool SortedUniformFind(co return BoundedSortedUniformFind(accessor, begin, below, end, above, key, out); } +// May return begin - 1. +template Iterator BinaryBelow( + const Accessor &accessor, + Iterator begin, + Iterator end, + const typename Accessor::Key key) { + while (end > begin) { + Iterator pivot(begin + (end - begin) / 2); + typename Accessor::Key mid(accessor(pivot)); + if (mid < key) { + begin = pivot + 1; + } else if (mid > key) { + end = pivot; + } else { + for (++pivot; (pivot < end) && accessor(pivot) == mid; ++pivot) {} + return pivot - 1; + } + } + return begin - 1; +} + // To use this template, you need to define a Pivot function to match Key. template class SortedUniformMap { public: -- cgit v1.2.3 From 4b6222733c4f9dcb3516bcc64394fa8b4716ce48 Mon Sep 17 00:00:00 2001 From: Chris Dyer Date: Fri, 9 Sep 2011 10:15:56 +0200 Subject: rule feature refactoring --- decoder/Makefile.am | 1 + decoder/cdec_ff.cc | 2 + decoder/ff_rules.cc | 107 ++++++++++++++++++++++++++++++++++++++++++++++++++++ decoder/ff_rules.h | 40 ++++++++++++++++++++ decoder/ff_spans.cc | 39 ------------------- decoder/ff_spans.h | 15 -------- 6 files changed, 150 insertions(+), 54 deletions(-) create mode 100644 decoder/ff_rules.cc create mode 100644 decoder/ff_rules.h (limited to 'decoder/cdec_ff.cc') diff --git a/decoder/Makefile.am b/decoder/Makefile.am index d884c431..e5f7505f 100644 --- a/decoder/Makefile.am +++ b/decoder/Makefile.am @@ -61,6 +61,7 @@ libcdec_a_SOURCES = \ phrasetable_fst.cc \ trule.cc \ ff.cc \ + ff_rules.cc \ ff_wordset.cc \ ff_charset.cc \ ff_lm.cc \ diff --git a/decoder/cdec_ff.cc b/decoder/cdec_ff.cc index 1ef76a05..588842f1 100644 --- a/decoder/cdec_ff.cc +++ b/decoder/cdec_ff.cc @@ -9,6 +9,7 @@ #include "ff_wordalign.h" #include "ff_tagger.h" #include "ff_factory.h" +#include "ff_rules.h" #include "ff_ruleshape.h" #include "ff_bleu.h" #include "ff_lm_fsa.h" @@ -53,6 +54,7 @@ void register_feature_functions() { #endif ff_registry.Register("SpanFeatures", new FFFactory()); ff_registry.Register("NgramFeatures", new FFFactory()); + ff_registry.Register("RuleIdentityFeatures", new FFFactory()); ff_registry.Register("RuleNgramFeatures", new FFFactory()); ff_registry.Register("CMR2008ReorderingFeatures", new FFFactory()); ff_registry.Register("KLanguageModel", new KLanguageModelFactory()); diff --git a/decoder/ff_rules.cc b/decoder/ff_rules.cc new file mode 100644 index 00000000..bd4c4cc0 --- /dev/null +++ b/decoder/ff_rules.cc @@ -0,0 +1,107 @@ +#include "ff_rules.h" + +#include +#include +#include + +#include "filelib.h" +#include "stringlib.h" +#include "sentence_metadata.h" +#include "lattice.h" +#include "fdict.h" +#include "verbose.h" + +using namespace std; + +namespace { + string Escape(const string& x) { + string y = x; + for (int i = 0; i < y.size(); ++i) { + if (y[i] == '=') y[i]='_'; + if (y[i] == ';') y[i]='_'; + } + return y; + } +} + +RuleIdentityFeatures::RuleIdentityFeatures(const std::string& param) { +} + +void RuleIdentityFeatures::PrepareForInput(const SentenceMetadata& smeta) { +// std::map > + rule2_fid_.clear(); +} + +void RuleIdentityFeatures::TraversalFeaturesImpl(const SentenceMetadata& smeta, + const Hypergraph::Edge& edge, + const vector& ant_contexts, + SparseVector* features, + SparseVector* estimated_features, + void* context) const { + map::iterator it = rule2_fid_.find(edge.rule_.get()); + if (it == rule2_fid_.end()) { + const TRule& rule = *edge.rule_; + ostringstream os; + os << "R:"; + if (rule.lhs_ < 0) os << TD::Convert(-rule.lhs_) << ':'; + for (unsigned i = 0; i < rule.f_.size(); ++i) { + if (i > 0) os << '_'; + WordID w = rule.f_[i]; + if (w < 0) { os << 'N'; w = -w; } + assert(w > 0); + os << TD::Convert(w); + } + os << ':'; + for (unsigned i = 0; i < rule.e_.size(); ++i) { + if (i > 0) os << '_'; + WordID w = rule.e_[i]; + if (w <= 0) { + os << 'N' << (1-w); + } else { + os << TD::Convert(w); + } + } + it = rule2_fid_.insert(make_pair(&rule, FD::Convert(Escape(os.str())))).first; + } + features->add_value(it->second, 1); +} + +RuleNgramFeatures::RuleNgramFeatures(const std::string& param) { +} + +void RuleNgramFeatures::PrepareForInput(const SentenceMetadata& smeta) { +// std::map > + rule2_feats_.clear(); +} + +void RuleNgramFeatures::TraversalFeaturesImpl(const SentenceMetadata& smeta, + const Hypergraph::Edge& edge, + const vector& ant_contexts, + SparseVector* features, + SparseVector* estimated_features, + void* context) const { + map >::iterator it = rule2_feats_.find(edge.rule_.get()); + if (it == rule2_feats_.end()) { + const TRule& rule = *edge.rule_; + it = rule2_feats_.insert(make_pair(&rule, SparseVector())).first; + SparseVector& f = it->second; + string prev = ""; + for (int i = 0; i < rule.f_.size(); ++i) { + WordID w = rule.f_[i]; + if (w < 0) w = -w; + assert(w > 0); + const string& cur = TD::Convert(w); + ostringstream os; + os << "RB:" << prev << '_' << cur; + const int fid = FD::Convert(Escape(os.str())); + if (fid <= 0) return; + f.add_value(fid, 1.0); + prev = cur; + } + ostringstream os; + os << "RB:" << prev << '_' << ""; + f.set_value(FD::Convert(Escape(os.str())), 1.0); + } + (*features) += it->second; +} + diff --git a/decoder/ff_rules.h b/decoder/ff_rules.h new file mode 100644 index 00000000..48d8bd05 --- /dev/null +++ b/decoder/ff_rules.h @@ -0,0 +1,40 @@ +#ifndef _FF_RULES_H_ +#define _FF_RULES_H_ + +#include +#include +#include "ff.h" +#include "array2d.h" +#include "wordid.h" + +class RuleIdentityFeatures : public FeatureFunction { + public: + RuleIdentityFeatures(const std::string& param); + protected: + virtual void TraversalFeaturesImpl(const SentenceMetadata& smeta, + const Hypergraph::Edge& edge, + const std::vector& ant_contexts, + SparseVector* features, + SparseVector* estimated_features, + void* context) const; + virtual void PrepareForInput(const SentenceMetadata& smeta); + private: + mutable std::map rule2_fid_; +}; + +class RuleNgramFeatures : public FeatureFunction { + public: + RuleNgramFeatures(const std::string& param); + protected: + virtual void TraversalFeaturesImpl(const SentenceMetadata& smeta, + const Hypergraph::Edge& edge, + const std::vector& ant_contexts, + SparseVector* features, + SparseVector* estimated_features, + void* context) const; + virtual void PrepareForInput(const SentenceMetadata& smeta); + private: + mutable std::map > rule2_feats_; +}; + +#endif diff --git a/decoder/ff_spans.cc b/decoder/ff_spans.cc index bc23974d..0483517b 100644 --- a/decoder/ff_spans.cc +++ b/decoder/ff_spans.cc @@ -193,45 +193,6 @@ void SpanFeatures::PrepareForInput(const SentenceMetadata& smeta) { } } -RuleNgramFeatures::RuleNgramFeatures(const std::string& param) { -} - -void RuleNgramFeatures::PrepareForInput(const SentenceMetadata& smeta) { -// std::map > - rule2_feats_.clear(); -} - -void RuleNgramFeatures::TraversalFeaturesImpl(const SentenceMetadata& smeta, - const Hypergraph::Edge& edge, - const vector& ant_contexts, - SparseVector* features, - SparseVector* estimated_features, - void* context) const { - map >::iterator it = rule2_feats_.find(edge.rule_.get()); - if (it == rule2_feats_.end()) { - const TRule& rule = *edge.rule_; - it = rule2_feats_.insert(make_pair(&rule, SparseVector())).first; - SparseVector& f = it->second; - string prev = ""; - for (int i = 0; i < rule.f_.size(); ++i) { - WordID w = rule.f_[i]; - if (w < 0) w = -w; - assert(w > 0); - const string& cur = TD::Convert(w); - ostringstream os; - os << "RB:" << prev << '_' << cur; - const int fid = FD::Convert(Escape(os.str())); - if (fid <= 0) return; - f.add_value(fid, 1.0); - prev = cur; - } - ostringstream os; - os << "RB:" << prev << '_' << ""; - f.set_value(FD::Convert(Escape(os.str())), 1.0); - } - (*features) += it->second; -} - inline bool IsArity2RuleReordered(const TRule& rule) { const vector& e = rule.e_; for (int i = 0; i < e.size(); ++i) { diff --git a/decoder/ff_spans.h b/decoder/ff_spans.h index b22c4d03..24e0dede 100644 --- a/decoder/ff_spans.h +++ b/decoder/ff_spans.h @@ -44,21 +44,6 @@ class SpanFeatures : public FeatureFunction { WordID oov_; }; -class RuleNgramFeatures : public FeatureFunction { - public: - RuleNgramFeatures(const std::string& param); - protected: - virtual void TraversalFeaturesImpl(const SentenceMetadata& smeta, - const Hypergraph::Edge& edge, - const std::vector& ant_contexts, - SparseVector* features, - SparseVector* estimated_features, - void* context) const; - virtual void PrepareForInput(const SentenceMetadata& smeta); - private: - mutable std::map > rule2_feats_; -}; - class CMR2008ReorderingFeatures : public FeatureFunction { public: CMR2008ReorderingFeatures(const std::string& param); -- cgit v1.2.3 From f826e90538dc15fbde4152b0e2f7d30fd6e56784 Mon Sep 17 00:00:00 2001 From: Chris Dyer Date: Mon, 12 Sep 2011 19:22:59 +0100 Subject: source syntax features ~ blunsom emnlp 2008 --- decoder/Makefile.am | 1 + decoder/cdec_ff.cc | 2 + decoder/ff_source_syntax.cc | 157 ++++++++++++++++++++++++++++++++++++++++++++ decoder/ff_source_syntax.h | 24 +++++++ utils/stringlib.cc | 7 +- 5 files changed, 190 insertions(+), 1 deletion(-) create mode 100644 decoder/ff_source_syntax.cc create mode 100644 decoder/ff_source_syntax.h (limited to 'decoder/cdec_ff.cc') diff --git a/decoder/Makefile.am b/decoder/Makefile.am index e5f7505f..ede1cff0 100644 --- a/decoder/Makefile.am +++ b/decoder/Makefile.am @@ -72,6 +72,7 @@ libcdec_a_SOURCES = \ ff_wordalign.cc \ ff_csplit.cc \ ff_tagger.cc \ + ff_source_syntax.cc \ ff_bleu.cc \ ff_factory.cc \ freqdict.cc \ diff --git a/decoder/cdec_ff.cc b/decoder/cdec_ff.cc index 588842f1..d562bc3a 100644 --- a/decoder/cdec_ff.cc +++ b/decoder/cdec_ff.cc @@ -14,6 +14,7 @@ #include "ff_bleu.h" #include "ff_lm_fsa.h" #include "ff_sample_fsa.h" +#include "ff_source_syntax.h" #include "ff_register.h" #include "ff_charset.h" #include "ff_wordset.h" @@ -55,6 +56,7 @@ void register_feature_functions() { ff_registry.Register("SpanFeatures", new FFFactory()); ff_registry.Register("NgramFeatures", new FFFactory()); ff_registry.Register("RuleIdentityFeatures", new FFFactory()); + ff_registry.Register("SourceSyntaxFeatures", new FFFactory); ff_registry.Register("RuleNgramFeatures", new FFFactory()); ff_registry.Register("CMR2008ReorderingFeatures", new FFFactory()); ff_registry.Register("KLanguageModel", new KLanguageModelFactory()); diff --git a/decoder/ff_source_syntax.cc b/decoder/ff_source_syntax.cc new file mode 100644 index 00000000..99acbd87 --- /dev/null +++ b/decoder/ff_source_syntax.cc @@ -0,0 +1,157 @@ +#include "ff_source_syntax.h" + +#include +#include + +#include "sentence_metadata.h" +#include "array2d.h" +#include "filelib.h" + +using namespace std; + +// implements the source side syntax features described in Blunsom et al. (EMNLP 2008) +// source trees must be represented in Penn Treebank format, e.g. +// (S (NP John) (VP (V left))) + +struct SourceSyntaxFeaturesImpl { + SourceSyntaxFeaturesImpl() {} + + void InitializeGrids(const string& tree, unsigned src_len) { + assert(tree.size() > 0); + fids_cat.clear(); + fids_fonly.clear(); + fids_ef.clear(); + src_tree.clear(); + fids_cat.resize(src_len, src_len + 1); + fids_fonly.resize(src_len, src_len + 1); + fids_ef.resize(src_len, src_len + 1); + src_tree.resize(src_len, src_len + 1, TD::Convert("XX")); + ParseTreeString(tree, src_len); + } + + void ParseTreeString(const string& tree, unsigned src_len) { + stack > stk; // first = i, second = category + pair cur_cat; cur_cat.first = -1; + unsigned i = 0; + unsigned p = 0; + while(p < tree.size()) { + const char cur = tree[p]; + if (cur == '(') { + stk.push(cur_cat); + ++p; + unsigned k = p + 1; + while (k < tree.size() && tree[k] != ' ') { ++k; } + cur_cat.first = i; + cur_cat.second = TD::Convert(tree.substr(p, k - p)); + // cerr << "NT: '" << tree.substr(p, k-p) << "' (i=" << i << ")\n"; + p = k + 1; + } else if (cur == ')') { + unsigned k = p; + while (k < tree.size() && tree[k] == ')') { ++k; } + const unsigned num_closes = k - p; + for (unsigned ci = 0; ci < num_closes; ++ci) { + // cur_cat.second spans from cur_cat.first to i + // cerr << TD::Convert(cur_cat.second) << " from " << cur_cat.first << " to " << i << endl; + // NOTE: unary rule chains end up being labeled with the top-most category + src_tree(cur_cat.first, i) = cur_cat.second; + cur_cat = stk.top(); + stk.pop(); + } + p = k; + while (p < tree.size() && (tree[p] == ' ' || tree[p] == '\t')) { ++p; } + } else if (cur == ' ' || cur == '\t') { + cerr << "Unexpected whitespace in: " << tree << endl; + abort(); + } else { // terminal symbol + unsigned k = p + 1; + do { + while (k < tree.size() && tree[k] != ')' && tree[k] != ' ') { ++k; } + // cerr << "TERM: '" << tree.substr(p, k-p) << "' (i=" << i << ")\n"; + ++i; + assert(i <= src_len); + while (k < tree.size() && tree[k] == ' ') { ++k; } + p = k; + } while (p < tree.size() && tree[p] != ')'); + } + } + // cerr << "i=" << i << " src_len=" << src_len << endl; + assert(i == src_len); // make sure tree specified in src_tree is + // the same length as the source sentence + } + + WordID FireFeatures(const TRule& rule, const int i, const int j, const WordID* ants, SparseVector* feats) { + //cerr << "fire features: " << rule.AsString() << " for " << i << "," << j << endl; + const WordID lhs = src_tree(i,j); + int& fid_cat = fids_cat(i,j); + int& fid_fonly = fids_fonly(i,j)[&rule]; + int& fid_ef = fids_ef(i,j)[&rule]; + if (fid_ef <= 0) { + ostringstream os; + os << "SYN:" << TD::Convert(lhs); + fid_cat = FD::Convert(os.str()); + os << ':'; + unsigned ntc = 0; + for (unsigned k = 0; k < rule.f_.size(); ++k) { + if (k > 0) os << '_'; + int fj = rule.f_[k]; + if (fj <= 0) { + os << '[' << TD::Convert(ants[ntc++]) << ']'; + } else { + os << TD::Convert(fj); + } + } + fid_fonly = FD::Convert(os.str()); + os << ':'; + for (unsigned k = 0; k < rule.e_.size(); ++k) { + const int ei = rule.e_[k]; + if (k > 0) os << '_'; + if (ei <= 0) + os << '[' << (1-ei) << ']'; + else + os << TD::Convert(ei); + } + fid_ef = FD::Convert(os.str()); + } + if (fid_cat > 0) + feats->set_value(fid_cat, 1.0); + if (fid_fonly > 0) + feats->set_value(fid_fonly, 1.0); + if (fid_ef > 0) + feats->set_value(fid_ef, 1.0); + return lhs; + } + + Array2D src_tree; // src_tree(i,j) NT = type + mutable Array2D fids_cat; // fires for an LHS match + mutable Array2D > fids_fonly; // fires for an f-string + mutable Array2D > fids_ef; // fires for fully lexicalized +}; + +SourceSyntaxFeatures::SourceSyntaxFeatures(const string& param) : + FeatureFunction(sizeof(WordID)) { + impl = new SourceSyntaxFeaturesImpl; +} + +SourceSyntaxFeatures::~SourceSyntaxFeatures() { + delete impl; + impl = NULL; +} + +void SourceSyntaxFeatures::TraversalFeaturesImpl(const SentenceMetadata& smeta, + const Hypergraph::Edge& edge, + const vector& ant_contexts, + SparseVector* features, + SparseVector* estimated_features, + void* context) const { + WordID ants[8]; + for (unsigned i = 0; i < ant_contexts.size(); ++i) + ants[i] = *static_cast(ant_contexts[i]); + + *static_cast(context) = + impl->FireFeatures(*edge.rule_, edge.i_, edge.j_, ants, features); +} + +void SourceSyntaxFeatures::PrepareForInput(const SentenceMetadata& smeta) { + impl->InitializeGrids(smeta.GetSGMLValue("src_tree"), smeta.GetSourceLength()); +} + diff --git a/decoder/ff_source_syntax.h b/decoder/ff_source_syntax.h new file mode 100644 index 00000000..1e890736 --- /dev/null +++ b/decoder/ff_source_syntax.h @@ -0,0 +1,24 @@ +#ifndef _FF_SOURCE_TOOLS_H_ +#define _FF_SOURCE_TOOLS_H_ + +#include "ff.h" + +struct SourceSyntaxFeaturesImpl; + +class SourceSyntaxFeatures : public FeatureFunction { + public: + SourceSyntaxFeatures(const std::string& param); + ~SourceSyntaxFeatures(); + protected: + virtual void TraversalFeaturesImpl(const SentenceMetadata& smeta, + const Hypergraph::Edge& edge, + const std::vector& ant_contexts, + SparseVector* features, + SparseVector* estimated_features, + void* context) const; + virtual void PrepareForInput(const SentenceMetadata& smeta); + private: + SourceSyntaxFeaturesImpl* impl; +}; + +#endif diff --git a/utils/stringlib.cc b/utils/stringlib.cc index 7aaee9f0..ade02ca9 100644 --- a/utils/stringlib.cc +++ b/utils/stringlib.cc @@ -32,7 +32,12 @@ void ParseTranslatorInput(const string& line, string* input, string* ref) { void ProcessAndStripSGML(string* pline, map* out) { map& meta = *out; string& line = *pline; - string lline = LowercaseString(line); + string lline = *pline; + if (lline.find(" must be lowercase!\n"; + cerr << " " << *pline << endl; + abort(); + } if (lline.find(""); if (close == string::npos) return; // error -- cgit v1.2.3 From 06e3c6c886cafc967688928ad62f380f0fcefe9e Mon Sep 17 00:00:00 2001 From: Chris Dyer Date: Sat, 17 Sep 2011 17:11:55 +0100 Subject: enable sss features --- decoder/cdec_ff.cc | 1 + 1 file changed, 1 insertion(+) (limited to 'decoder/cdec_ff.cc') diff --git a/decoder/cdec_ff.cc b/decoder/cdec_ff.cc index d562bc3a..69f40c93 100644 --- a/decoder/cdec_ff.cc +++ b/decoder/cdec_ff.cc @@ -57,6 +57,7 @@ void register_feature_functions() { ff_registry.Register("NgramFeatures", new FFFactory()); ff_registry.Register("RuleIdentityFeatures", new FFFactory()); ff_registry.Register("SourceSyntaxFeatures", new FFFactory); + ff_registry.Register("SourceSpanSizeFeatures", new FFFactory); ff_registry.Register("RuleNgramFeatures", new FFFactory()); ff_registry.Register("CMR2008ReorderingFeatures", new FFFactory()); ff_registry.Register("KLanguageModel", new KLanguageModelFactory()); -- cgit v1.2.3 From 708e8220d2cbc41fbbf2e8a713edf1d2cf3bc767 Mon Sep 17 00:00:00 2001 From: Chris Dyer Date: Fri, 14 Oct 2011 11:51:12 +0100 Subject: remove FSA integration code. will have to be resurrected another day --- decoder/Makefile.am | 1 - decoder/apply_fsa_models.cc | 798 ---------------------------------------- decoder/cdec_ff.cc | 13 - decoder/feature_accum.h | 129 ------- decoder/ff_factory.h | 2 - decoder/ff_from_fsa.h | 304 --------------- decoder/ff_fsa.h | 401 -------------------- decoder/ff_fsa_data.h | 131 ------- decoder/ff_fsa_dynamic.h | 208 ----------- decoder/ff_lm.cc | 48 --- decoder/ff_lm_fsa.h | 140 ------- decoder/ff_register.h | 38 -- decoder/hg_test.cc | 16 +- training/mpi_online_optimize.cc | 2 + 14 files changed, 10 insertions(+), 2221 deletions(-) delete mode 100755 decoder/apply_fsa_models.cc delete mode 100755 decoder/feature_accum.h delete mode 100755 decoder/ff_from_fsa.h delete mode 100755 decoder/ff_fsa.h delete mode 100755 decoder/ff_fsa_data.h delete mode 100755 decoder/ff_fsa_dynamic.h delete mode 100755 decoder/ff_lm_fsa.h (limited to 'decoder/cdec_ff.cc') diff --git a/decoder/Makefile.am b/decoder/Makefile.am index ede1cff0..6b9360d8 100644 --- a/decoder/Makefile.am +++ b/decoder/Makefile.am @@ -42,7 +42,6 @@ libcdec_a_SOURCES = \ cfg.cc \ dwarf.cc \ ff_dwarf.cc \ - apply_fsa_models.cc \ rule_lexer.cc \ fst_translator.cc \ csplit.cc \ diff --git a/decoder/apply_fsa_models.cc b/decoder/apply_fsa_models.cc deleted file mode 100755 index 3e93cadd..00000000 --- a/decoder/apply_fsa_models.cc +++ /dev/null @@ -1,798 +0,0 @@ -//see apply_fsa_models.README for notes on the l2r earley fsa+cfg intersection -//implementation in this file (also some comments in this file) -#define SAFE_VALGRIND 1 - -#include "apply_fsa_models.h" -#include -#include -#include -#include - -#include "writer.h" -#include "hg.h" -#include "ff_fsa_dynamic.h" -#include "ff_from_fsa.h" -#include "feature_vector.h" -#include "stringlib.h" -#include "apply_models.h" -#include "cfg.h" -#include "hg_cfg.h" -#include "utoa.h" -#include "hash.h" -#include "value_array.h" -#include "d_ary_heap.h" -#include "agenda.h" -#include "show.h" -#include "string_to.h" - - -#define DFSA(x) x -//fsa earley chart - -#define DPFSA(x) x -//prefix trie - -#define DBUILDTRIE(x) - -#define PRINT_PREFIX 1 -#if PRINT_PREFIX -# define IF_PRINT_PREFIX(x) x -#else -# define IF_PRINT_PREFIX(x) -#endif -// keep backpointers in prefix trie so you can print a meaningful node id - -static const unsigned FSA_AGENDA_RESERVE=10; // TODO: increase to 1<<24 (16M) - -using namespace std; - -//impl details (not exported). flat namespace for my ease. - -typedef CFG::RHS RHS; -typedef CFG::BinRhs BinRhs; -typedef CFG::NTs NTs; -typedef CFG::NT NT; -typedef CFG::NTHandle NTHandle; -typedef CFG::Rules Rules; -typedef CFG::Rule Rule; -typedef CFG::RuleHandle RuleHandle; - -namespace { - -/* - -1) A -> x . * (trie) - -this is somewhat nice. cost pushed for best first, of course. similar benefit as left-branching binarization without the explicit predict/complete steps? - -vs. just - -2) * -> x . y - -here you have to potentially list out all A -> . x y as items * -> . x y immediately, and shared rhs seqs won't be shared except at the usual single-NT predict/complete. of course, the prediction of items -> . x y can occur lazy best-first. - -vs. - -3) * -> x . * - -with 3, we predict all sorts of useless items - that won't give us our goal A and may not partcipate in any parse. this is not a good option at all. - -I'm using option 1. -*/ - -// if we don't greedy-binarize, we want to encode recognized prefixes p (X -> p . rest) efficiently. if we're doing this, we may as well also push costs so we can best-first select rules in a lazy fashion. this is effectively left-branching binarization, of course. - -template -struct fsa_map_type { - typedef std::map type; // change to HASH_MAP ? -}; -//template typedef - and macro to make it less painful -#define FSA_MAP(k,v) fsa_map_type >::type - -struct PrefixTrieNode; -typedef PrefixTrieNode *NodeP; -typedef PrefixTrieNode const *NodePc; - -// for debugging prints only -struct TrieBackP { - WordID w; - NodePc from; - TrieBackP(WordID w=0,NodePc from=0) : w(w),from(from) { } -}; - -FsaFeatureFunction const* print_fsa=0; -CFG const* print_cfg=0; -inline ostream& print_cfg_rhs(std::ostream &o,WordID w,CFG const*pcfg=print_cfg) { - if (pcfg) - pcfg->print_rhs_name(o,w); - else - CFG::static_print_rhs_name(o,w); - return o; -} - -inline std::string nt_name(WordID n,CFG const*pcfg=print_cfg) { - if (pcfg) return pcfg->nt_name(n); - return CFG::static_nt_name(n); -} - -template -ostream& print_by_nt(std::ostream &o,V const& v,CFG const*pcfg=print_cfg,char const* header="\nNT -> X\n") { - o< "< -ostream& print_map_by_nt(std::ostream &o,V const& v,CFG const*pcfg=print_cfg,char const* header="\nNT -> X\n") { - o<first,pcfg) << " -> "<second<<"\n"; - } - return o; -} - -struct PrefixTrieEdge { - PrefixTrieEdge() - // : dest(0),w(TD::max_wordid) - {} - PrefixTrieEdge(WordID w,NodeP dest) - : dest(dest),w(w) - {} -// explicit PrefixTrieEdge(best_t p) : p(p),dest(0) { } - - best_t p;// viterbi additional prob, i.e. product over path incl. p_final = total rule prob. note: for final edge, set this. - //DPFSA() - // we can probably just store deltas, but for debugging remember the full p - // best_t delta; // - NodeP dest; - bool is_final() const { return dest==0; } - best_t p_dest() const; - WordID w; // for root and and is_final(), this will be (negated) NTHandle. - - // for sorting most probable first in adj; actually >(p) - inline bool operator <(PrefixTrieEdge const& o) const { - return o.p"< BPs; - void back_vec(BPs &ns) const { - IF_PRINT_PREFIX(if(backp.from) { ns.push_back(backp); backp.from->back_vec(ns); }) - } - - BPs back_vec() const { - BPs ret; - back_vec(ret); - return ret; - } - - unsigned size() const { - unsigned a=adj.size(); - unsigned e=edge_for.size(); - return a>e?a:e; - } - - void print_back_str(std::ostream &o) const { - BPs back=back_vec(); - unsigned i=back.size(); - if (!i) { - o<<"PrefixTrieNode@"<<(uintptr_t)this; - return; - } - bool first=true; - while (i--<=0) { - if (!first) o<<','; - first=false; - WordID w=back[i].w; - print_cfg_rhs(o,w); - } - } - std::string back_str() const { - std::ostringstream o; - print_back_str(o); - return o.str(); - } - -// best_t p_final; // additional prob beyond what we already paid. while building, this is the total prob -// instead of storing final, we'll say that an edge with a NULL dest is a final edge. this way it gets sorted into the list of adj. - - // instead of completed map, we have trie start w/ lhs. - NTHandle lhs; // nonneg. - instead of storing this in Item. - IF_PRINT_PREFIX(BP backp;) - - enum { ROOT=-1 }; - explicit PrefixTrieNode(NTHandle lhs=ROOT,best_t p=1) : p(p),lhs(lhs),IF_PRINT_PREFIX(backp()) { - //final=false; - } - bool is_root() const { return lhs==ROOT; } // means adj are the nonneg lhs indices, and we have the index edge_for still available - - // outgoing edges will be ordered highest p to worst p - - typedef FSA_MAP(WordID,PrefixTrieEdge) PrefixTrieEdgeFor; -public: - PrefixTrieEdgeFor edge_for; //TODO: move builder elsewhere? then need 2nd hash or edge include pointer to builder. just clear this later - bool have_adj() const { - return adj.size()>=edge_for.size(); - } - bool no_adj() const { - return adj.empty(); - } - - void index_adj() { - index_adj(edge_for); - } - template - void index_adj(M &m) { - assert(have_adj()); - m.clear(); - for (int i=0;i - void index_lhs(PV &v) { - for (int i=0,e=adj.size();i!=e;++i) { - PrefixTrieEdge const& edge=adj[i]; - // assert(edge.p.is_1()); // actually, after done_building, e will have telescoped dest->p/p. - NTHandle n=-edge.w; - assert(n>=0); -// SHOWM3(DPFSA,"index_lhs",i,edge,n); - v[n]=edge.dest; - } - } - - template - void done_root(PV &v) { - assert(is_root()); - SHOWM1(DBUILDTRIE,"done_root",OSTRF1(print_map_by_nt,edge_for)); - done_building_r(); //sets adj - SHOWM1(DBUILDTRIE,"done_root",OSTRF1(print_by_nt,adj)); -// SHOWM1(DBUILDTRIE,done_root,adj); -// index_adj(); // we want an index for the root node?. don't think so - index_lhs handles it. also we stopped clearing edge_for. - index_lhs(v); // uses adj - } - - // call only once. - void done_building_r() { - done_building(); - for (int i=0;idone_building_r(); - } - - // for done_building; compute incremental (telescoped) edge p - PrefixTrieEdge /*const&*/ operator()(PrefixTrieEdgeFor::value_type & pair) const { - PrefixTrieEdge &e=pair.second;//const_cast(pair.second); - e.p=e.p_dest()/p; - return e; - } - - // call only once. - void done_building() { - SHOWM3(DBUILDTRIE,"done_building",edge_for.size(),adj.size(),1); -#if 1 - adj.reinit_map(edge_for,*this); -#else - adj.reinit(edge_for.size()); - SHOWM3(DBUILDTRIE,"done_building_reinit",edge_for.size(),adj.size(),2); - Adj::iterator o=adj.begin(); - for (PrefixTrieEdgeFor::iterator i=edge_for.begin(),e=edge_for.end();i!=e;++i) { - SHOWM3(DBUILDTRIE,"edge_for",o-adj.begin(),i->first,i->second); - PrefixTrieEdge &edge=i->second; - edge.p=(edge.dest->p)/p; - *o++=edge; -// (*this)(*i); - } -#endif - SHOWM1(DBUILDTRIE,"done building adj",prange(adj.begin(),adj.end(),true)); - assert(adj.size()==edge_for.size()); -// if (final) p_final/=p; - std::sort(adj.begin(),adj.end()); - //TODO: store adjacent differences on edges (compared to - } - - typedef ValueArray Adj; -// typedef vector Adj; - Adj adj; - - typedef WordID W; - - // let's compute p_min so that every rule reachable from the created node has p at least this low. - NodeP improve_edge(PrefixTrieEdge const& e,best_t rulep) { - NodeP d=e.dest; - maybe_improve(d->p,rulep); - return d; - } - - inline NodeP build(W w,best_t rulep) { - return build(lhs,w,rulep); - } - inline NodeP build_lhs(NTHandle n,best_t rulep) { - return build(n,-n,rulep); - } - - NodeP build(NTHandle lhs_,W w,best_t rulep) { - PrefixTrieEdgeFor::iterator i=edge_for.find(w); - if (i!=edge_for.end()) - return improve_edge(i->second,rulep); - NodeP r=new PrefixTrieNode(lhs_,rulep); - IF_PRINT_PREFIX(r->backp=BP(w,this)); -// edge_for.insert(i,PrefixTrieEdgeFor::value_type(w,PrefixTrieEdge(w,r))); - add(edge_for,w,PrefixTrieEdge(w,r)); - SHOWM4(DBUILDTRIE,"built node",this,w,*r,r); - return r; - } - - void set_final(NTHandle lhs_,best_t pf) { - assert(no_adj()); -// final=true; - PrefixTrieEdge &e=edge_for[null_wordid]; - e.p=pf; - e.dest=0; - e.w=lhs_; - maybe_improve(p,pf); - } - -private: - void destroy_children() { - assert(adj.size()>=edge_for.size()); - for (int i=0,e=adj.size();i" << p; - o << ',' << size() << ','; - print_back_str(o); - } - PRINT_SELF(PrefixTrieNode) -}; - -inline best_t PrefixTrieEdge::p_dest() const { - return dest ? dest->p : p; // for final edge, p was set (no sentinel node) -} - - -//Trie starts with lhs (nonneg index), then continues w/ rhs (mixed >0 word, else NT) -// trie ends with final edge, which points to a per-lhs prefix node -struct PrefixTrie { - void print(std::ostream &o) const { - o << cfgp << ' ' << root; - } - PRINT_SELF(PrefixTrie); - CFG *cfgp; - Rules const* rulesp; - Rules const& rules() const { return *rulesp; } - CFG const& cfg() const { return *cfgp; } - PrefixTrieNode root; - typedef std::vector LhsToTrie; // will have to check lhs2[lhs].p for best cost of some rule with that lhs, then use edge deltas after? they're just caching a very cheap computation, really - LhsToTrie lhs2; // no reason to use a map or hash table; every NT in the CFG will have some rule rhses. lhs_to_trie[i]=root.edge_for[i], i.e. we still have a root trie node conceptually, we just access through this since it's faster. - typedef LhsToTrie LhsToComplete; - LhsToComplete lhs2complete; // the sentinel "we're completing" node (dot at end) for that lhs. special case of suffix-set=same trie minimization (aka right branching binarization) // these will be used to track kbest completions, along with a l state (r state will be in the list) - PrefixTrie(CFG &cfg) : cfgp(&cfg),rulesp(&cfg.rules),lhs2(cfg.nts.size(),0),lhs2complete(cfg.nts.size()) { -// cfg.SortLocalBestFirst(); // instead we'll sort in done_building_r - print_cfg=cfgp; - SHOWM2(DBUILDTRIE,"PrefixTrie()",rulesp->size(),lhs2.size()); - cfg.VisitRuleIds(*this); - root.done_root(lhs2); - SHOWM3(DBUILDTRIE,"done w/ PrefixTrie: ",root,root.adj.size(),lhs2.size()); - DBUILDTRIE(print_by_nt(cerr,lhs2,cfgp)); - SHOWM1(DBUILDTRIE,"lhs2",OSTRF2(print_by_nt,lhs2,cfgp)); - } - - void operator()(int ri) { - Rule const& r=rules()[ri]; - NTHandle lhs=r.lhs; - best_t p=r.p; -// NodeP n=const_cast(root).build_lhs(lhs,p); - NodeP n=root.build_lhs(lhs,p); - SHOWM4(DBUILDTRIE,"Prefixtrie rule id, root",ri,root,p,*n); - for (RHS::const_iterator i=r.rhs.begin(),e=r.rhs.end();;++i) { - SHOWM2(DBUILDTRIE,"PrefixTrie build or final",i-r.rhs.begin(),*n); - if (i==e) { - n->set_final(lhs,p); - break; - } - n=n->build(*i,p); - SHOWM2(DBUILDTRIE,"PrefixTrie built",*i,*n); - } -// root.build(lhs,r.p)->build(r.rhs,r.p); - } - inline NodeP lhs2_ex(NTHandle n) const { - NodeP r=lhs2[n]; - if (!r) throw std::runtime_error("PrefixTrie: no CFG rule w/ lhs "+cfgp->nt_name(n)); - return r; - } -private: - PrefixTrie(PrefixTrie const& o); -}; - - - -typedef std::size_t ItemHash; - - -struct ItemKey { - explicit ItemKey(NodeP start,Bytes const& start_state) : dot(start),q(start_state),r(start_state) { } - explicit ItemKey(NodeP dot) : dot(dot) { } - NodeP dot; // dot is a function of the stuff already recognized, and gives a set of suffixes y to complete to finish a rhs for lhs() -> dot y. for a lhs A -> . *, this will point to lh2[A] - Bytes q,r; // (q->r are the fsa states; if r is empty it means - bool operator==(ItemKey const& o) const { - return dot==o.dot && q==o.q && r==o.r; - } - inline ItemHash hash() const { - ItemHash h=GOLDEN_MEAN_FRACTION*(ItemHash)(dot-NULL); // i.e. lower order bits of ptr are nonrandom - using namespace boost; - hash_combine(h,q); - hash_combine(h,r); - return h; - } - template - void print(O &o) const { - o<<"lhs="<print_back_str(o); - if (print_fsa) { - o<<'/'; - print_fsa->print_state(o,&q[0]); - o<<"->"; - print_fsa->print_state(o,&r[0]); - } - } - NTHandle lhs() const { return dot->lhs; } - PRINT_SELF(ItemKey) -}; -inline ItemHash hash_value(ItemKey const& x) { - return x.hash(); -} -ItemKey null_item((PrefixTrieNode*)0); - -struct Item; -typedef Item *ItemP; - -/* we use a single type of item so it can live in a single best-first queue. we hold them by pointer so they can have mutable state, e.g. priority/location, but also lists of predictions and kbest completions (i.e. completions[L,r] = L -> * (r,s), by 1best for each possible s. we may discover more s later. we could use different subtypes since we hold by pointer, but for now everything will be packed as variants of Item */ -#undef INIT_LOCATION -#if D_ARY_TRACK_OUT_OF_HEAP -# define INIT_LOCATION , location(D_ARY_HEAP_NULL_INDEX) -#elif !defined(NDEBUG) || SAFE_VALGRIND - // avoid spurious valgrind warning - FIXME: still complains??? -# define INIT_LOCATION , location() -#else -# define INIT_LOCATION -#endif - -// these should go in a global best-first queue -struct ItemPrio { - // NOTE: sum = viterbi (max) - ItemPrio() : priority(init_0()),inner(init_0()) { } - explicit ItemPrio(best_t priority) : priority(priority),inner(init_0()) { } - best_t priority; // includes inner prob. (forward) - /* The forward probability alpha_i(X[k]->x.y) is the sum of the probabilities of all - constrained paths of length i that end in state X[k]->x.y*/ - best_t inner; - /* The inner probability beta_i(X[k]->x.y) is the sum of the probabilities of all - paths of length i-k that start in state X[k,k]->.xy and end in X[k,i]->x.y, and generate the input symbols x[k,...,i-1] */ - template - void print(O &o) const { - o<=0; - } - explicit Item(FFState const& state,NodeP dot,best_t prio,int next=0) : ItemPrio(prio),ItemKey(dot,state),trienext(next),from(0) - INIT_LOCATION - { -// t=ADJ; -// if (dot->adj.size()) - dot->p_delta(next,priority); -// SHOWM1(DFSA,"Item(state,dot,prio)",prio); - } - typedef std::queue Predicted; -// Predicted predicted; // this is empty, unless this is a predicted L -> .asdf item, or a to-complete L -> asdf . - int trienext; // index of dot->adj to complete (if dest==0), or predict (if NT), or scan (if word). note: we could store pointer inside adj since it and trie are @ fixed addrs. less pointer arith, more space. - ItemP from; //backpointer - 0 for L -> . asdf for the rest; L -> a .sdf, it's the L -> .asdf item. - ItemP predicted_from() const { - ItemP p=(ItemP)this; - while(p->from) p=p->from; - return p; - } - template - void print(O &o) const { - o<< '['; - o< -struct ApplyFsa { - ApplyFsa(HgCFG &i, - const SentenceMetadata& smeta, - const FsaFeatureFunction& fsa, - DenseWeightVector const& weights, - ApplyFsaBy const& by, - Hypergraph* oh - ) - :hgcfg(i),smeta(smeta),fsa(fsa),weights(weights),by(by),oh(oh) - { - stateless=!fsa.state_bytes(); - } - void Compute() { - if (by.IsBottomUp() || stateless) - ApplyBottomUp(); - else - ApplyEarley(); - } - void ApplyBottomUp(); - void ApplyEarley(); - CFG const& GetCFG(); -private: - CFG cfg; - HgCFG &hgcfg; - SentenceMetadata const& smeta; - FsaFF const& fsa; -// WeightVector weight_vector; - DenseWeightVector weights; - ApplyFsaBy by; - Hypergraph* oh; - std::string cfg_out; - bool stateless; -}; - -template -void ApplyFsa::ApplyBottomUp() -{ - assert(by.IsBottomUp()); - FeatureFunctionFromFsa buff(&fsa); - buff.Init(); // mandatory to call this (normally factory would do it) - vector ffs(1,&buff); - ModelSet models(weights, ffs); - IntersectionConfiguration i(stateless ? BU_FULL : by.BottomUpAlgorithm(),by.pop_limit); - ApplyModelSet(hgcfg.ih,smeta,models,i,oh); -} - -template -void ApplyFsa::ApplyEarley() -{ - hgcfg.GiveCFG(cfg); - print_cfg=&cfg; - print_fsa=&fsa; - Chart chart(cfg,smeta,fsa); - // don't need to uniq - option to do that already exists in cfg_options - //TODO: - chart.best_first(); - *oh=hgcfg.ih; -} - - -void ApplyFsaModels(HgCFG &i, - const SentenceMetadata& smeta, - const FsaFeatureFunction& fsa, - DenseWeightVector const& weight_vector, - ApplyFsaBy const& by, - Hypergraph* oh) -{ - ApplyFsa a(i,smeta,fsa,weight_vector,by,oh); - a.Compute(); -} - -/* -namespace { -char const* anames[]={ - "BU_CUBE", - "BU_FULL", - "EARLEY", - 0 -}; -} -*/ - -//TODO: named enum type in boost? - -std::string ApplyFsaBy::name() const { -// return anames[algorithm]; - return GetName(algorithm); -} - -std::string ApplyFsaBy::all_names() { - return FsaByNames(" "); - /* - std::ostringstream o; - for (int i=0;i=N_ALGORITHMS) - throw std::runtime_error("Unknown ApplyFsaBy type id: "+itos(i)+" - legal types: "+all_names()); -*/ - GetName(i); // checks validity - algorithm=i; -} - -int ApplyFsaBy::BottomUpAlgorithm() const { - assert(IsBottomUp()); - return algorithm==BU_CUBE ? - IntersectionConfiguration::CUBE - :IntersectionConfiguration::FULL; -} - -void ApplyFsaModels(Hypergraph const& ih, - const SentenceMetadata& smeta, - const FsaFeatureFunction& fsa, - DenseWeightVector const& weights, // pre: in is weighted by these (except with fsa featval=0 before this) - ApplyFsaBy const& cfg, - Hypergraph* out) -{ - HgCFG i(ih); - ApplyFsaModels(i,smeta,fsa,weights,cfg,out); -} diff --git a/decoder/cdec_ff.cc b/decoder/cdec_ff.cc index 69f40c93..4ce5749e 100644 --- a/decoder/cdec_ff.cc +++ b/decoder/cdec_ff.cc @@ -12,8 +12,6 @@ #include "ff_rules.h" #include "ff_ruleshape.h" #include "ff_bleu.h" -#include "ff_lm_fsa.h" -#include "ff_sample_fsa.h" #include "ff_source_syntax.h" #include "ff_register.h" #include "ff_charset.h" @@ -31,15 +29,6 @@ void register_feature_functions() { } registered = true; - //TODO: these are worthless example target FSA ffs. remove later - RegisterFsaImpl(true); - RegisterFsaImpl(true); - RegisterFsaImpl(true); -// ff_registry.Register("LanguageModelFsaDynamic",new FFFactory > >); // to test correctness of FsaFeatureFunctionDynamic erasure - RegisterFsaDynToFF(); - RegisterFsaImpl(true); // same as LM but using fsa wrapper - RegisterFsaDynToFF(); - RegisterFF(); RegisterFF(); @@ -47,8 +36,6 @@ void register_feature_functions() { RegisterFF(); RegisterFF(); - ff_registry.Register(new FFFactory); // same as WordPenalty, but implemented using ff_fsa - //TODO: use for all features the new Register which requires static FF::usage(false,false) give name #ifdef HAVE_RANDLM ff_registry.Register("RandLM", new FFFactory); diff --git a/decoder/feature_accum.h b/decoder/feature_accum.h deleted file mode 100755 index 4b8338eb..00000000 --- a/decoder/feature_accum.h +++ /dev/null @@ -1,129 +0,0 @@ -#ifndef FEATURE_ACCUM_H -#define FEATURE_ACCUM_H - -#include "ff.h" -#include "sparse_vector.h" -#include "value_array.h" - -struct SparseFeatureAccumulator : public FeatureVector { - typedef FeatureVector State; - SparseFeatureAccumulator() { assert(!"this code is disabled"); } - template - FeatureVector const& describe(FF const& ) { return *this; } - void Store(FeatureVector *fv) const { -//NO fv->set_from(*this); - } - template - void Store(FF const& /* ff */,FeatureVector *fv) const { -//NO fv->set_from(*this); - } - template - void Add(FF const& /* ff */,FeatureVector const& fv) { - (*this)+=fv; - } - void Add(FeatureVector const& fv) { - (*this)+=fv; - } - /* - SparseFeatureAccumulator(FeatureVector const& fv) : State(fv) {} - FeatureAccumulator(Features const& fids) {} - FeatureAccumulator(Features const& fids,FeatureVector const& fv) : State(fv) {} - void Add(Features const& fids,FeatureVector const& fv) { - *this += fv; - } - */ - void Add(int i,Featval v) { -//NO (*this)[i]+=v; - } - void Add(Features const& fids,int i,Featval v) { -//NO (*this)[i]+=v; - } -}; - -struct SingleFeatureAccumulator { - typedef Featval State; - typedef SingleFeatureAccumulator Self; - State v; - /* - void operator +=(State const& o) { - v+=o; - } - */ - void operator +=(Self const& s) { - v+=s.v; - } - SingleFeatureAccumulator() : v() {} - template - State const& describe(FF const& ) const { return v; } - - template - void Store(FF const& ff,FeatureVector *fv) const { - fv->set_value(ff.fid_,v); - } - void Store(Features const& fids,FeatureVector *fv) const { - assert(fids.size()==1); - fv->set_value(fids[0],v); - } - /* - SingleFeatureAccumulator(Features const& fids) { assert(fids.size()==1); } - SingleFeatureAccumulator(Features const& fids,FeatureVector const& fv) - { - assert(fids.size()==1); - v=fv.get_singleton(); - } - */ - - template - void Add(FF const& ff,FeatureVector const& fv) { - v+=fv.get(ff.fid_); - } - void Add(FeatureVector const& fv) { - v+=fv.get_singleton(); - } - - void Add(Features const& fids,FeatureVector const& fv) { - v += fv.get(fids[0]); - } - void Add(Featval dv) { - v+=dv; - } - void Add(int,Featval dv) { - v+=dv; - } - void Add(FeatureVector const& fids,int i,Featval dv) { - assert(fids.size()==1 && i==0); - v+=dv; - } -}; - - -#if 0 -// omitting this so we can default construct an accum. might be worth resurrecting in the future -struct ArrayFeatureAccumulator : public ValueArray { - typedef ValueArray State; - template - ArrayFeatureAccumulator(Fsa const& fsa) : State(fsa.features_.size()) { } - ArrayFeatureAccumulator(Features const& fids) : State(fids.size()) { } - ArrayFeatureAccumulator(Features const& fids) : State(fids.size()) { } - ArrayFeatureAccumulator(Features const& fids,FeatureVector const& fv) : State(fids.size()) { - for (int i=0,e=iset_value(fids[i],(*this)[i]); - } - void Add(Features const& fids,FeatureVector const& fv) { - for (int i=0,e=i -#include "ff_fsa_dynamic.h" - class FeatureFunction; class FsaFeatureFunction; diff --git a/decoder/ff_from_fsa.h b/decoder/ff_from_fsa.h deleted file mode 100755 index f8d79e03..00000000 --- a/decoder/ff_from_fsa.h +++ /dev/null @@ -1,304 +0,0 @@ -#ifndef FF_FROM_FSA_H -#define FF_FROM_FSA_H - -#include "ff_fsa.h" - -#ifndef TD__none -// replacing dependency on SRILM -#define TD__none -1 -#endif - -#ifndef FSA_FF_DEBUG -# define FSA_FF_DEBUG 0 -#endif -#if FSA_FF_DEBUG -# define FSAFFDBG(e,x) FSADBGif(debug(),e,x) -# define FSAFFDBGnl(e) FSADBGif_nl(debug(),e) -#else -# define FSAFFDBG(e,x) -# define FSAFFDBGnl(e) -#endif - -/* regular bottom up scorer from Fsa feature - uses guarantee about markov order=N to score ASAP - encoding of state: if less than N-1 (ctxlen) words - - usage: - typedef FeatureFunctionFromFsa LanguageModelFromFsa; -*/ - -template -class FeatureFunctionFromFsa : public FeatureFunction { - typedef void const* SP; - typedef WordID *W; - typedef WordID const* WP; -public: - template - FeatureFunctionFromFsa(I const& param) : ff(param) { - debug_=true; // because factory won't set until after we construct. - } - template - FeatureFunctionFromFsa(I & param) : ff(param) { - debug_=true; // because factory won't set until after we construct. - } - - static std::string usage(bool args,bool verbose) { - return Impl::usage(args,verbose); - } - void init_name_debug(std::string const& n,bool debug) { - FeatureFunction::init_name_debug(n,debug); - ff.init_name_debug(n,debug); - } - - // this should override - Features features() const { - DBGINIT("FeatureFunctionFromFsa features() name="<=1) - for (int j=0,ee=e.size();;++j) { // items in target side of rule - for(;;++j) { - if (j>=ee) goto rhs_done; // j may go 1 past ee due to k possibly getting to end - if (RHS_WORD(j)) break; - } - // word @j - int k=j; - while(k{"<") - FSAFFDBG(edge," end="<{"< -# define FSADBG(e,x) FSADBGif(d().debug(),e,x) -# define FSADBGnl(e) FSADBGif_nl(d().debug(),e,x) -#else -# define FSADBG(e,x) -# define FSADBGnl(e) -#endif - -#include "fast_lexical_cast.hpp" -#include -#include -#include "ff.h" -#include "sparse_vector.h" -#include "tdict.h" -#include "hg.h" -#include "ff_fsa_data.h" - -/* -usage: see ff_sample_fsa.h or ff_lm_fsa.h - - then, to decode, see ff_from_fsa.h (or TODO: left->right target-earley style rescoring) - - */ - - -template -struct FsaFeatureFunctionBase : public FsaFeatureFunctionData { - Impl const& d() const { return static_cast(*this); } - Impl & d() { return static_cast(*this); } - - // this will get called by factory - override if you have multiple or dynamically named features. note: may be called repeatedly - void Init() { - Init(name()); - DBGINIT("base (single feature) FsaFeatureFunctionBase::Init name="<set_value(fid,val) possibly with duplicates. state and next_state will never be the same memory. - //TODO: decide if we want to require you to support dest same as src, since that's how we use it most often in ff_from_fsa bottom-up wrapper (in l->r scoring, however, distinct copies will be the rule), and it probably wouldn't be too hard for most people to support. however, it's good to hide the complexity here, once (see overly clever FsaScan loop that swaps src/dest addresses repeatedly to scan a sequence by effectively swapping) - -protected: - // overrides have different name because of inheritance method hiding; - - // simple/common case; 1 fid. these need not be overriden if you have multiple feature ids - Featval Scan1(WordID w,void const* state,void *next_state) const { - assert(0); - return 0; - } - Featval Scan1Meta(SentenceMetadata const& /* smeta */,Hypergraph::Edge const& /* edge */, - WordID w,void const* state,void *next_state) const { - return d().Scan1(w,state,next_state); - } -public: - - // must override this or Scan1Meta or Scan1 - template - inline void ScanAccum(SentenceMetadata const& smeta,Hypergraph::Edge const& edge, - WordID w,void const* state,void *next_state,Accum *a) const { - Add(d().Scan1Meta(smeta,edge,w,state,next_state),a); - } - - // bounce back and forth between two state vars starting at cs, returning end state location. if we required src=dest addr safe state updating, this concept wouldn't need to exist. - // required that you override this if you score phrases differently than word-by-word, however, you can just use the SCAN_PHRASE_ACCUM_OVERRIDE macro to do that in terms of ScanPhraseAccum - template - void *ScanPhraseAccumBounce(SentenceMetadata const& smeta,Hypergraph::Edge const& edge,WordID const* i, WordID const* end,void *cs,void *ns,Accum *accum) const { - // extra code - IT'S FOR EFFICIENCY, MAN! IT'S OK! definitely no bugs here. - if (!ssz) { - for (;io - odd: - d().ScanAccum(smeta,edge,i[0],os,es,accum); // o->e - } - return es; - } - - - static const bool simple_phrase_score=true; // if d().simple_phrase_score_, then you should expect different Phrase scores for phrase length > M. so, set this false if you provide ScanPhraseAccum (SCAN_PHRASE_ACCUM_OVERRIDE macro does this) - - // override this (and use SCAN_PHRASE_ACCUM_OVERRIDE ) if you want e.g. maximum possible order ngram scores with markov_order < n-1. in the future SparseFeatureAccumulator will probably be the only option for type-erased FSA ffs. - // note you'll still have to override ScanAccum - template - void ScanPhraseAccum(SentenceMetadata const& smeta,Hypergraph::Edge const & edge, - WordID const* i, WordID const* end, - void const* state,void *next_state,Accum *accum) const { - if (!ssz) { - for (;i \ - void *ScanPhraseAccumBounce(SentenceMetadata const& smeta,Hypergraph::Edge const& edge,WordID const* i, WordID const* end,void *cs,void *ns,Accum *accum) const { \ - ScanPhraseAccum(smeta,edge,i,end,cs,ns,accum); \ - return ns; \ - } \ - template \ - void ScanPhraseAccumOnly(SentenceMetadata const& smeta,Hypergraph::Edge const& edge, \ - WordID const* i, WordID const* end, \ - void const* state,Accum *accum) const { \ - char s2[ssz]; ScanPhraseAccum(smeta,edge,i,end,state,(void*)s2,accum); \ - } - - // override this or bounce along with above. note: you can just call ScanPhraseAccum - // doesn't set state (for heuristic in ff_from_fsa) - template - void ScanPhraseAccumOnly(SentenceMetadata const& smeta,Hypergraph::Edge const& edge, - WordID const* i, WordID const* end, - void const* state,Accum *accum) const { - char s1[ssz]; - char s2[ssz]; - state_copy(s1,state); - d().ScanPhraseAccumBounce(smeta,edge,i,end,(void*)s1,(void*)s2,accum); - } - - // for single-feat only. but will work for different accums - template - inline void Add(Featval v,Accum *a) const { - a->Add(fid_,v); - } - inline void set_feat(FeatureVector *features,Featval v) const { - features->set_value(fid_,v); - } - - // don't set state-bytes etc. in ctor because it may depend on parsing param string - FsaFeatureFunctionBase(int statesz=0,Sentence const& end_sentence_phrase=Sentence()) - : FsaFeatureFunctionData(statesz,end_sentence_phrase) - { - name_=name(); // should allow FsaDynamic wrapper to get name copied to it with sync - } - -}; - -template -struct MultipleFeatureFsa : public FsaFeatureFunctionBase { - typedef SparseFeatureAccumulator Accum; -}; - - - - -// if State is pod. sets state size and allocs start, h_start -// usage: -// struct ShorterThanPrev : public FsaTypedBase -// i.e. Impl is a CRTP -template -struct FsaTypedBase : public FsaFeatureFunctionBase { - Impl const& d() const { return static_cast(*this); } - Impl & d() { return static_cast(*this); } -protected: - typedef FsaFeatureFunctionBase Base; - typedef St State; - static inline State & state(void *state) { - return *(State*)state; - } - static inline State const& state(void const* state) { - return *(State const*)state; - } - void set_starts(State const& s,State const& heuristic_s) { - if (0) { // already in ctor - Base::start.resize(sizeof(State)); - Base::h_start.resize(sizeof(State)); - } - assert(Base::start.size()==sizeof(State)); - assert(Base::h_start.size()==sizeof(State)); - state(Base::start.begin())=s; - state(Base::h_start.begin())=heuristic_s; - } - FsaTypedBase(St const& start_st=St() - ,St const& h_start_st=St() - ,Sentence const& end_sentence_phrase=Sentence()) - : Base(sizeof(State),end_sentence_phrase) { - set_starts(start_st,h_start_st); - } -public: - void print_state(std::ostream &o,void const*st) const { - o< - inline void ScanT(SentenceMetadata const& smeta,Hypergraph::Edge const& edge,WordID w,St const& prev_st,St &new_st,Accum *a) const { - Add(d().ScanT1(smeta,edge,w,prev_st,new_st),a); - } - - // note: you're on your own when it comes to Phrase overrides. see FsaFeatureFunctionBase. sorry. - - template - inline void ScanAccum(SentenceMetadata const& smeta,Hypergraph::Edge const& edge,WordID w,void const* st,void *next_state,Accum *a) const { - Impl const& im=d(); - FSADBG(edge,"Scan "<describe(im)<<" "<"< -struct FsaScanner { -// enum {ALIGN=8}; - static const int ALIGN=8; - FF const& ff; - SentenceMetadata const& smeta; - int ssz; - Bytes states; // first is at begin, second is at (char*)begin+stride - void *st0; // states - void *st1; // states+stride - void *cs; // initially st0, alternates between st0 and st1 - inline void *nexts() const { - return (cs==st0)?st1:st0; - } - Hypergraph::Edge const& edge; - FsaScanner(FF const& ff,SentenceMetadata const& smeta,Hypergraph::Edge const& edge) : ff(ff),smeta(smeta),edge(edge) - { - ssz=ff.state_bytes(); - int stride=((ssz+ALIGN-1)/ALIGN)*ALIGN; // round up to multiple of ALIGN - states.resize(stride+ssz); - st0=states.begin(); - st1=(char*)st0+stride; -// for (int i=0;i<2;++i) st[i]=cs+(i*stride); - } - void reset(void const* state) { - cs=st0; - std::memcpy(st0,state,ssz); - } - template - void scan(WordID w,Accum *a) { - void *ns=nexts(); - ff.ScanAccum(smeta,edge,w,cs,ns,a); - cs=ns; - } - template - void scan(WordID const* i,WordID const* end,Accum *a) { - // faster. and allows greater-order excursions - cs=ff.ScanPhraseAccumBounce(smeta,edge,i,end,cs,nexts(),a); - } -}; - - -//TODO: combine 2 FsaFeatures typelist style (can recurse for more) - - - - -#endif diff --git a/decoder/ff_fsa_data.h b/decoder/ff_fsa_data.h deleted file mode 100755 index d215e940..00000000 --- a/decoder/ff_fsa_data.h +++ /dev/null @@ -1,131 +0,0 @@ -#ifndef FF_FSA_DATA_H -#define FF_FSA_DATA_H - -#include //C99 -#include -#include "sentences.h" -#include "feature_accum.h" -#include "value_array.h" -#include "ff.h" //debug -typedef ValueArray Bytes; - -// stuff I see no reason to have virtual. but because it's impossible (w/o virtual inheritance to have dynamic fsa ff know where the impl's data starts, implemented a sync (copy) method that needs to be called. init_name_debug was already necessary to keep state in sync between ff and ff_from_fsa, so no sync should be needed after it. supposing all modifications were through setters, then no explicit sync call would ever be needed; updates could be mirrored. -struct FsaFeatureFunctionData -{ - void init_name_debug(std::string const& n,bool debug) { - name_=n; - debug_=debug; - } - //HACK for diamond inheritance (w/o costing performance) - FsaFeatureFunctionData *sync_to_; - - void sync() const { // call this if you modify any fields after your constructor is done - if (sync_to_) { - DBGINIT("sync to "<<*sync_to_); - *sync_to_=*this; - DBGINIT("synced result="<<*sync_to_<< " from this="<<*this); - } else { - DBGINIT("nobody to sync to - from FeatureFunctionData this="<<*this); - } - } - - friend std::ostream &operator<<(std::ostream &o,FsaFeatureFunctionData const& d) { - o << "[FSA "< - static inline T* state_as(void *p) { return (T*)p; } - template - static inline T const* state_as(void const* p) { return (T*)p; } - std::string describe_features(FeatureVector const& feats) { - std::ostringstream o; - o<" for lm. -protected: - int ssz; // don't forget to set this. default 0 (it may depend on params of course) - // this can be called instead or after constructor (also set bytes and end_phrase_) - void set_state_bytes(int sb=0) { - if (start.size()!=sb) start.resize(sb); - if (h_start.size()!=sb) h_start.resize(sb); - ssz=sb; - } - void set_end_phrase(WordID single) { - end_phrase_=singleton_sentence(single); - } - - inline void static to_state(void *state,char const* begin,char const* end) { - std::memcpy(state,begin,end-begin); - } - inline void static to_state(void *state,char const* begin,int n) { - std::memcpy(state,begin,n); - } - template - inline void static to_state(void *state,T const* begin,int n=1) { - to_state(state,(char const*)begin,n*sizeof(T)); - } - template - inline void static to_state(void *state,T const* begin,T const* end) { - to_state(state,(char const*)begin,(char const*)end); - } - inline static char hexdigit(int i) { - int j=i-10; - return j>=0?'a'+j:'0'+i; - } - inline static void print_hex_byte(std::ostream &o,unsigned c) { - o<>4); - o<Add(v); - } - -}; - -#endif diff --git a/decoder/ff_fsa_dynamic.h b/decoder/ff_fsa_dynamic.h deleted file mode 100755 index 6f75bbe5..00000000 --- a/decoder/ff_fsa_dynamic.h +++ /dev/null @@ -1,208 +0,0 @@ -#ifndef FF_FSA_DYNAMIC_H -#define FF_FSA_DYNAMIC_H - -struct SentenceMetadata; - -#include "ff_fsa_data.h" -#include "hg.h" // can't forward declare nested Hypergraph::Edge class -#include - -// the type-erased interface - -//FIXME: diamond inheritance problem. make a copy of the fixed data? or else make the dynamic version not wrap but rather be templated CRTP base (yuck) -struct FsaFeatureFunction : public FsaFeatureFunctionData { - static const bool simple_phrase_score=false; - virtual int markov_order() const = 0; - - // see ff_fsa.h - FsaFeatureFunctionBase gives you reasonable impls of these if you override just ScanAccum - virtual void ScanAccum(SentenceMetadata const& smeta,Hypergraph::Edge const& edge, - WordID w,void const* state,void *next_state,Accum *a) const = 0; - virtual void ScanPhraseAccum(SentenceMetadata const& smeta,Hypergraph::Edge const & edge, - WordID const* i, WordID const* end, - void const* state,void *next_state,Accum *accum) const = 0; - virtual void ScanPhraseAccumOnly(SentenceMetadata const& smeta,Hypergraph::Edge const& edge, - WordID const* i, WordID const* end, - void const* state,Accum *accum) const = 0; - virtual void *ScanPhraseAccumBounce(SentenceMetadata const& smeta,Hypergraph::Edge const& edge,WordID const* i, WordID const* end,void *cs,void *ns,Accum *accum) const = 0; - - virtual int early_score_words(SentenceMetadata const& smeta,Hypergraph::Edge const& edge,WordID const* i, WordID const* end,Accum *accum) const { return 0; } - // called after constructor, before use - virtual void Init() = 0; - virtual std::string usage_v(bool param,bool verbose) const { - return FeatureFunction::usage_helper("unnamed_dynamic_fsa_feature","","",param,verbose); - } - virtual void init_name_debug(std::string const& n,bool debug) { - FsaFeatureFunctionData::init_name_debug(n,debug); - } - - virtual void print_state(std::ostream &o,void const*state) const { - FsaFeatureFunctionData::print_state(o,state); - } - virtual std::string describe() const { return "[FSA unnamed_dynamic_fsa_feature]"; } - - //end_phrase() - virtual ~FsaFeatureFunction() {} - - // no need to override: - std::string describe_state(void const* state) const { - std::ostringstream o; - print_state(o,state); - return o.str(); - } -}; - -// conforming to above interface, type erases FsaImpl -// you might be wondering: why do this? answer: it's cool, and it means that the bottom-up ff over ff_fsa wrapper doesn't go through multiple layers of dynamic dispatch -// usage: typedef FsaFeatureFunctionDynamic MyFsaDyn; -template -struct FsaFeatureFunctionDynamic : public FsaFeatureFunction { - static const bool simple_phrase_score=Impl::simple_phrase_score; - Impl& d() { return impl;//static_cast(*this); - } - Impl const& d() const { return impl; - //static_cast(*this); - } - int markov_order() const { return d().markov_order(); } - - std::string describe() const { - return d().describe(); - } - - virtual void ScanAccum(SentenceMetadata const& smeta,Hypergraph::Edge const& edge, - WordID w,void const* state,void *next_state,Accum *a) const { - return d().ScanAccum(smeta,edge,w,state,next_state,a); - } - - virtual void ScanPhraseAccum(SentenceMetadata const& smeta,Hypergraph::Edge const & edge, - WordID const* i, WordID const* end, - void const* state,void *next_state,Accum *a) const { - return d().ScanPhraseAccum(smeta,edge,i,end,state,next_state,a); - } - - virtual void ScanPhraseAccumOnly(SentenceMetadata const& smeta,Hypergraph::Edge const& edge, - WordID const* i, WordID const* end, - void const* state,Accum *a) const { - return d().ScanPhraseAccumOnly(smeta,edge,i,end,state,a); - } - - virtual void *ScanPhraseAccumBounce(SentenceMetadata const& smeta,Hypergraph::Edge const& edge,WordID const* i, WordID const* end,void *cs,void *ns,Accum *a) const { - return d().ScanPhraseAccumBounce(smeta,edge,i,end,cs,ns,a); - } - - virtual int early_score_words(SentenceMetadata const& smeta,Hypergraph::Edge const& edge,WordID const* i, WordID const* end,Accum *accum) const { - return d().early_score_words(smeta,edge,i,end,accum); - } - - static std::string usage(bool param,bool verbose) { - return Impl::usage(param,verbose); - } - - std::string usage_v(bool param,bool verbose) const { - return Impl::usage(param,verbose); - } - - virtual void print_state(std::ostream &o,void const*state) const { - return d().print_state(o,state); - } - - void init_name_debug(std::string const& n,bool debug) { - FsaFeatureFunction::init_name_debug(n,debug); - d().init_name_debug(n,debug); - } - - virtual void Init() { - d().sync_to_=(FsaFeatureFunctionData*)this; - d().Init(); - d().sync(); - } - - template - FsaFeatureFunctionDynamic(I const& param) : impl(param) { - Init(); - } -private: - Impl impl; -}; - -// constructor takes ptr or shared_ptr to Impl, otherwise same as above - note: not virtual -template -struct FsaFeatureFunctionPimpl : public FsaFeatureFunctionData { - typedef boost::shared_ptr Pimpl; - static const bool simple_phrase_score=Impl::simple_phrase_score; - Impl const& d() const { return *p_; } - int markov_order() const { return d().markov_order(); } - - std::string describe() const { - return d().describe(); - } - - void ScanAccum(SentenceMetadata const& smeta,Hypergraph::Edge const& edge, - WordID w,void const* state,void *next_state,Accum *a) const { - return d().ScanAccum(smeta,edge,w,state,next_state,a); - } - - void ScanPhraseAccum(SentenceMetadata const& smeta,Hypergraph::Edge const & edge, - WordID const* i, WordID const* end, - void const* state,void *next_state,Accum *a) const { - return d().ScanPhraseAccum(smeta,edge,i,end,state,next_state,a); - } - - void ScanPhraseAccumOnly(SentenceMetadata const& smeta,Hypergraph::Edge const& edge, - WordID const* i, WordID const* end, - void const* state,Accum *a) const { - return d().ScanPhraseAccumOnly(smeta,edge,i,end,state,a); - } - - void *ScanPhraseAccumBounce(SentenceMetadata const& smeta,Hypergraph::Edge const& edge,WordID const* i, WordID const* end,void *cs,void *ns,Accum *a) const { - return d().ScanPhraseAccumBounce(smeta,edge,i,end,cs,ns,a); - } - - int early_score_words(SentenceMetadata const& smeta,Hypergraph::Edge const& edge,WordID const* i, WordID const* end,Accum *accum) const { - return d().early_score_words(smeta,edge,i,end,accum); - } - - static std::string usage(bool param,bool verbose) { - return Impl::usage(param,verbose); - } - - std::string usage_v(bool param,bool verbose) const { - return Impl::usage(param,verbose); - } - - void print_state(std::ostream &o,void const*state) const { - return d().print_state(o,state); - } - -#if 0 - // this and Init() don't touch p_ because we want to leave the original alone. - void init_name_debug(std::string const& n,bool debug) { - FsaFeatureFunctionData::init_name_debug(n,debug); - } -#endif - void Init() { - p_=hold_pimpl_.get(); -#if 0 - d().sync_to_=static_cast(this); - d().Init(); -#endif - *static_cast(this)=d(); - } - - FsaFeatureFunctionPimpl(Impl const* const p) : hold_pimpl_(p,null_deleter()) { - Init(); - } - FsaFeatureFunctionPimpl(Pimpl const& p) : hold_pimpl_(p) { - Init(); - } -private: - Impl const* p_; - Pimpl hold_pimpl_; -}; - -typedef FsaFeatureFunctionPimpl FsaFeatureFunctionFwd; // allow ff_from_fsa for an existing dynamic-type ff (as opposed to usual register a wrapped known-type FSA in ff_register, which is more efficient) -//typedef FsaFeatureFunctionDynamic DynamicFsaFeatureFunctionFwd; //if you really need to have a dynamic fsa facade that's also a dynamic fsa - -//TODO: combine 2 (or N) FsaFeatureFunction (type erased) - - -#endif diff --git a/decoder/ff_lm.cc b/decoder/ff_lm.cc index afa36b96..5e16d4e3 100644 --- a/decoder/ff_lm.cc +++ b/decoder/ff_lm.cc @@ -46,7 +46,6 @@ char const* usage_verbose="-n determines the name of the feature (and its weight #endif #include "ff_lm.h" -#include "ff_lm_fsa.h" #include #include @@ -69,10 +68,6 @@ char const* usage_verbose="-n determines the name of the feature (and its weight using namespace std; -string LanguageModelFsa::usage(bool param,bool verbose) { - return FeatureFunction::usage_helper("LanguageModelFsa",usage_short,usage_verbose,param,verbose); -} - string LanguageModel::usage(bool param,bool verbose) { return FeatureFunction::usage_helper(usage_name,usage_short,usage_verbose,param,verbose); } @@ -524,49 +519,6 @@ LanguageModel::LanguageModel(const string& param) { SetStateSize(LanguageModelImpl::OrderToStateSize(order)); } -//TODO: decide whether to waste a word of space so states are always none-terminated for SRILM. otherwise we have to copy -void LanguageModelFsa::set_ngram_order(int i) { - assert(i>0); - ngram_order_=i; - ctxlen_=i-1; - set_state_bytes(ctxlen_*sizeof(WordID)); - WordID *ss=(WordID*)start.begin(); - WordID *hs=(WordID*)h_start.begin(); - if (ctxlen_) { // avoid segfault in case of unigram lm (0 state) - set_end_phrase(TD::Convert("")); -// se is pretty boring in unigram case, just adds constant prob. check that this is what we want - ss[0]=TD::Convert(""); // start-sentence context (length 1) - hs[0]=0; // empty context - for (int i=1;ifloor_; - set_ngram_order(lmorder); -} - -void LanguageModelFsa::print_state(ostream &o,void const* st) const { - WordID const *wst=(WordID const*)st; - o<<'['; - bool sp=false; - for (int i=ctxlen_;i>0;sp=true) { - --i; - WordID w=wst[i]; - if (w==0) continue; - if (sp) o<<' '; - o << TD::Convert(w); - } - o<<']'; -} - Features LanguageModel::features() const { return single_feature(fid_); } diff --git a/decoder/ff_lm_fsa.h b/decoder/ff_lm_fsa.h deleted file mode 100755 index 85b7ef44..00000000 --- a/decoder/ff_lm_fsa.h +++ /dev/null @@ -1,140 +0,0 @@ -#ifndef FF_LM_FSA_H -#define FF_LM_FSA_H - -//FIXME: when FSA_LM_PHRASE 1, 3gram fsa has differences, especially with unk words, in about the 4th decimal digit (about .05%), compared to regular ff_lm. this is USUALLY a bug (there's way more actual precision in there). this was with #define LM_FSA_SHORTEN_CONTEXT 1 and 0 (so it's not that). also, LM_FSA_SHORTEN_CONTEXT gives identical scores with FSA_LM_PHRASE 0 - -// enabling for now - retest unigram+ more, solve above puzzle - -// some impls in ff_lm.cc - -#define FSA_LM_PHRASE 1 - -#define FSA_LM_DEBUG 0 -#if FSA_LM_DEBUG -# define FSALMDBG(e,x) FSADBGif(debug(),e,x) -# define FSALMDBGnl(e) FSADBGif_nl(debug(),e) -#else -# define FSALMDBG(e,x) -# define FSALMDBGnl(e) -#endif - -#include "ff_fsa.h" -#include "ff_lm.h" - -#ifndef TD__none -// replacing dependency on SRILM -#define TD__none -1 -#endif - -namespace { -WordID empty_context=TD__none; -} - -struct LanguageModelFsa : public FsaFeatureFunctionBase { - typedef WordID * W; - typedef WordID const* WP; - - // overrides; implementations in ff_lm.cc - typedef SingleFeatureAccumulator Accum; - static std::string usage(bool,bool); - LanguageModelFsa(std::string const& param); - int markov_order() const { return ctxlen_; } - void print_state(std::ostream &,void const *) const; - inline Featval floored(Featval p) const { - return pleft;--e) - if (e[-1]!=TD__none) break; - //post: [left,e] are the seen left words - return e; - } - - template - void ScanAccum(SentenceMetadata const& /* smeta */,Hypergraph::Edge const& edge,WordID w,void const* old_st,void *new_st,Accum *a) const { -#if USE_INFO_EDGE - Hypergraph::Edge &de=(Hypergraph::Edge &)edge; -#endif - if (!ctxlen_) { - Add(floored(pimpl_->WordProb(w,&empty_context)),a); - } else { - WordID ctx[ngram_order_]; //alloca if you don't have C99 - state_copy(ctx,old_st); - ctx[ctxlen_]=TD__none; - Featval p=floored(pimpl_->WordProb(w,ctx)); - FSALMDBG(de,"p("<ShortenContext(nst,ctxlen_); -#endif - Add(p,a); - } - } - -#if FSA_LM_PHRASE - //FIXME: there is a bug in here somewhere, or else the 3gram LM we use gives different scores for phrases (impossible? BOW nonzero when shortening context past what LM has?) - template - void ScanPhraseAccum(SentenceMetadata const& /* smeta */,const Hypergraph::Edge&edge,WordID const* begin,WordID const* end,void const* old_st,void *new_st,Accum *a) const { - Hypergraph::Edge &de=(Hypergraph::Edge &)edge;(void)de; - if (begin==end) return; // otherwise w/ shortening it's possible to end up with no words at all. - /* // this is forcing unigram prob always. we will instead build the phrase - if (!ctxlen_) { - Featval p=0; - for (;iWordProb(*i,e&mpty_context)); - Add(p,a); - return; - } */ - int nw=end-begin; - WP st=(WP)old_st; - WP st_end=st+ctxlen_; // may include some null already (or none if full) - int nboth=nw+ctxlen_; - WordID ctx[nboth+1]; - ctx[nboth]=TD__none; - // reverse order - state at very end of context, then [i,end) in rev order ending at ctx[0] - W ctx_score_end=wordcpy_reverse(ctx,begin,end); - wordcpy(ctx_score_end,st,st_end); // st already reversed. - assert(ctx_score_end==ctx+nw); - // we could just copy the filled state words, but it probably doesn't save much time (and might cost some to scan to find the nones. most contexts are full except for the shortest source spans. - FSALMDBG(de," scan.r->l("<ctx;--ctx_score_end) - p+=floored(pimpl_->WordProb(ctx_score_end[-1],ctx_score_end)); - //TODO: look for score discrepancy - - // i had some idea that maybe shortencontext would return a different prob if the length provided was > ctxlen_; however, since the same disagreement happens with LM_FSA_SHORTEN_CONTEXT 0 anyway, it's not that. perhaps look to SCAN_PHRASE_ACCUM_OVERRIDE - make sure they do the right thing. -#if LM_FSA_SHORTEN_CONTEXT - p+=pimpl_->ShortenContext(ctx,nboth - need to use factory rather than ctor. -#if 0 -template -inline void RegisterFsa(bool ff_also=true,bool fsa_prefix_ff=true) { - assert(!ff_also); -// global_fsa_ff_registry->RegisterFsa(); -//if (ff_also) ff_registry.RegisterFF >(prefix_fsa(DynFsa::usage(false,false)),fsa_prefix_ff); -} -#endif - -//TODO: ff from fsa that uses pointer to fsa impl? e.g. in LanguageModel we share underlying lm file by recognizing same param, but without that effort, otherwise stateful ff may duplicate state if we enable both fsa and ff_from_fsa -template -inline void RegisterFsaImpl(bool ff_also=true,bool fsa_prefix_ff=false) { - typedef FsaFeatureFunctionDynamic DynFsa; - typedef FeatureFunctionFromFsa FFFrom; - std::string name=FsaImpl::usage(false,false); - fsa_ff_registry.Register(new FsaFactory); - if (ff_also) - ff_registry.Register(prefix_fsa(name,fsa_prefix_ff),new FFFactory); -} template inline void RegisterFF() { ff_registry.Register(new FFFactory); } -template -inline void RegisterFsaDynToFF(std::string name,bool prefix=true) { - typedef FsaFeatureFunctionDynamic DynFsa; - ff_registry.Register(prefix?"DynamicFsa"+name:name,new FFFactory >); -} - -template -inline void RegisterFsaDynToFF(bool prefix=true) { - RegisterFsaDynToFF(FsaImpl::usage(false,false),prefix); -} - void register_feature_functions(); #endif diff --git a/decoder/hg_test.cc b/decoder/hg_test.cc index 3be5b82d..5d1910fb 100644 --- a/decoder/hg_test.cc +++ b/decoder/hg_test.cc @@ -57,7 +57,7 @@ TEST_F(HGTest,Union) { c3 = ViterbiESentence(hg1, &t3); int l3 = ViterbiPathLength(hg1); cerr << c3 << "\t" << TD::GetString(t3) << endl; - EXPECT_FLOAT_EQ(c2, c3); + EXPECT_FLOAT_EQ(c2.as_float(), c3.as_float()); EXPECT_EQ(TD::GetString(t2), TD::GetString(t3)); EXPECT_EQ(l2, l3); @@ -117,7 +117,7 @@ TEST_F(HGTest,InsideScore) { cerr << "cost: " << cost << "\n"; hg.PrintGraphviz(); prob_t inside = Inside(hg); - EXPECT_FLOAT_EQ(1.7934048, inside); // computed by hand + EXPECT_FLOAT_EQ(1.7934048, inside.as_float()); // computed by hand vector post; inside = hg.ComputeBestPathThroughEdges(&post); EXPECT_FLOAT_EQ(-0.3, log(inside)); // computed by hand @@ -282,13 +282,13 @@ TEST_F(HGTest, TestGenericInside) { hg.Reweight(wts); vector inside; prob_t ins = Inside(hg, &inside); - EXPECT_FLOAT_EQ(1.7934048, ins); // computed by hand + EXPECT_FLOAT_EQ(1.7934048, ins.as_float()); // computed by hand vector outside; Outside(hg, inside, &outside); EXPECT_EQ(3, outside.size()); - EXPECT_FLOAT_EQ(1.7934048, outside[0]); - EXPECT_FLOAT_EQ(1.3114071, outside[1]); - EXPECT_FLOAT_EQ(1.0, outside[2]); + EXPECT_FLOAT_EQ(1.7934048, outside[0].as_float()); + EXPECT_FLOAT_EQ(1.3114071, outside[1].as_float()); + EXPECT_FLOAT_EQ(1.0, outside[2].as_float()); } TEST_F(HGTest,TestGenericInside2) { @@ -327,8 +327,8 @@ TEST_F(HGTest,TestAddExpectations) { SparseVector feat_exps; prob_t z = InsideOutside, EdgeFeaturesAndProbWeightFunction>(hg, &feat_exps); - EXPECT_FLOAT_EQ(-2.5439765, feat_exps.value(FD::Convert("f1")) / z); - EXPECT_FLOAT_EQ(-2.6357865, feat_exps.value(FD::Convert("f2")) / z); + EXPECT_FLOAT_EQ(-2.5439765, (feat_exps.value(FD::Convert("f1")) / z).as_float()); + EXPECT_FLOAT_EQ(-2.6357865, (feat_exps.value(FD::Convert("f2")) / z).as_float()); cerr << feat_exps << endl; cerr << "Z=" << z << endl; } diff --git a/training/mpi_online_optimize.cc b/training/mpi_online_optimize.cc index f87b7274..993627f0 100644 --- a/training/mpi_online_optimize.cc +++ b/training/mpi_online_optimize.cc @@ -9,6 +9,7 @@ #include #include +#include "stringlib.h" #include "verbose.h" #include "hg.h" #include "prob.h" @@ -204,6 +205,7 @@ bool LoadAgenda(const string& file, vector >* a) { } int main(int argc, char** argv) { + cerr << "THIS SOFTWARE IS DEPRECATED YOU SHOULD USE mpi_flex_optimize\n"; #ifdef HAVE_MPI mpi::environment env(argc, argv); mpi::communicator world; -- cgit v1.2.3