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#include "lm/exception.hh"
#include "lm/sri.hh"
#include <Ngram.h>
#include <Vocab.h>
#include <errno.h>
namespace lm {
namespace sri {
Vocabulary::Vocabulary() : sri_(new Vocab) {}
Vocabulary::~Vocabulary() {}
WordIndex Vocabulary::Index(const char *str) const {
WordIndex ret = sri_->getIndex(str);
// NGram wants the index of Vocab_Unknown for unknown words, but for some reason SRI returns Vocab_None here :-(.
if (ret == Vocab_None) {
return not_found_;
} else {
return ret;
}
}
const char *Vocabulary::Word(WordIndex index) const {
return sri_->getWord(index);
}
void Vocabulary::FinishedLoading() {
SetSpecial(
sri_->ssIndex(),
sri_->seIndex(),
sri_->unkIndex(),
sri_->highIndex() + 1);
}
namespace {
Ngram *MakeSRIModel(const char *file_name, unsigned int ngram_length, Vocab &sri_vocab) {
sri_vocab.unkIsWord() = true;
std::auto_ptr<Ngram> ret(new Ngram(sri_vocab, ngram_length));
File file(file_name, "r");
errno = 0;
if (!ret->read(file)) {
UTIL_THROW(FormatLoadException, "reading file " << file_name << " with SRI failed.");
}
return ret.release();
}
} // namespace
Model::Model(const char *file_name, unsigned int ngram_length) : sri_(MakeSRIModel(file_name, ngram_length, *vocab_.sri_)) {
if (!sri_->setorder()) {
UTIL_THROW(FormatLoadException, "Can't have an SRI model with order 0.");
}
vocab_.FinishedLoading();
State begin_state = State();
begin_state.valid_length_ = 1;
if (kMaxOrder > 1) {
begin_state.history_[0] = vocab_.BeginSentence();
if (kMaxOrder > 2) begin_state.history_[1] = Vocab_None;
}
State null_state = State();
null_state.valid_length_ = 0;
if (kMaxOrder > 1) null_state.history_[0] = Vocab_None;
Init(begin_state, null_state, vocab_, sri_->setorder());
not_found_ = vocab_.NotFound();
}
Model::~Model() {}
namespace {
/* Argh SRI's wordProb knows the ngram length but doesn't return it. One more
* reason you should use my model. */
// TODO(stolcke): fix SRILM so I don't have to do this.
unsigned int MatchedLength(Ngram &model, const WordIndex new_word, const SRIVocabIndex *const_history) {
unsigned int out_length = 0;
// This gets the length of context used, which is ngram_length - 1 unless new_word is OOV in which case it is 0.
model.contextID(new_word, const_history, out_length);
return out_length + 1;
}
} // namespace
FullScoreReturn Model::FullScore(const State &in_state, const WordIndex new_word, State &out_state) const {
// If you get a compiler in this function, change SRIVocabIndex in sri.hh to match the one found in SRI's Vocab.h.
const SRIVocabIndex *const_history;
SRIVocabIndex local_history[Order()];
if (in_state.valid_length_ < kMaxOrder - 1) {
const_history = in_state.history_;
} else {
std::copy(in_state.history_, in_state.history_ + in_state.valid_length_, local_history);
local_history[in_state.valid_length_] = Vocab_None;
const_history = local_history;
}
FullScoreReturn ret;
if (new_word != not_found_) {
ret.ngram_length = MatchedLength(*sri_, new_word, const_history);
out_state.history_[0] = new_word;
out_state.valid_length_ = std::min<unsigned char>(ret.ngram_length, Order() - 1);
std::copy(const_history, const_history + out_state.valid_length_ - 1, out_state.history_ + 1);
if (out_state.valid_length_ < kMaxOrder - 1) {
out_state.history_[out_state.valid_length_] = Vocab_None;
}
} else {
ret.ngram_length = 0;
if (kMaxOrder > 1) out_state.history_[0] = Vocab_None;
out_state.valid_length_ = 0;
}
ret.prob = sri_->wordProb(new_word, const_history);
return ret;
}
} // namespace sri
} // namespace lm
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