| #ifndef LM_READ_ARPA_H |
| #define LM_READ_ARPA_H |
| |
| #include "lm/lm_exception.hh" |
| #include "lm/word_index.hh" |
| #include "lm/weights.hh" |
| #include "util/file_piece.hh" |
| |
| #include <cstddef> |
| #include <iosfwd> |
| #include <vector> |
| |
| namespace lm { |
| |
| void ReadARPACounts(util::FilePiece &in, std::vector<uint64_t> &number); |
| void ReadNGramHeader(util::FilePiece &in, unsigned int length); |
| |
| void ReadBackoff(util::FilePiece &in, Prob &weights); |
| void ReadBackoff(util::FilePiece &in, float &backoff); |
| inline void ReadBackoff(util::FilePiece &in, ProbBackoff &weights) { |
| ReadBackoff(in, weights.backoff); |
| } |
| inline void ReadBackoff(util::FilePiece &in, RestWeights &weights) { |
| ReadBackoff(in, weights.backoff); |
| } |
| |
| void ReadEnd(util::FilePiece &in); |
| |
| extern const bool kARPASpaces[256]; |
| |
| // Positive log probability warning. |
| class PositiveProbWarn { |
| public: |
| PositiveProbWarn() : action_(THROW_UP) {} |
| |
| explicit PositiveProbWarn(WarningAction action) : action_(action) {} |
| |
| void Warn(float prob); |
| |
| private: |
| WarningAction action_; |
| }; |
| |
| template <class Voc, class Weights> void Read1Gram(util::FilePiece &f, Voc &vocab, Weights *unigrams, PositiveProbWarn &warn) { |
| try { |
| float prob = f.ReadFloat(); |
| if (prob > 0.0) { |
| warn.Warn(prob); |
| prob = 0.0; |
| } |
| UTIL_THROW_IF(f.get() != '\t', FormatLoadException, "Expected tab after probability"); |
| WordIndex word = vocab.Insert(f.ReadDelimited(kARPASpaces)); |
| Weights &w = unigrams[word]; |
| w.prob = prob; |
| ReadBackoff(f, w); |
| } catch(util::Exception &e) { |
| e << " in the 1-gram at byte " << f.Offset(); |
| throw; |
| } |
| } |
| |
| template <class Voc, class Weights> void Read1Grams(util::FilePiece &f, std::size_t count, Voc &vocab, Weights *unigrams, PositiveProbWarn &warn) { |
| ReadNGramHeader(f, 1); |
| for (std::size_t i = 0; i < count; ++i) { |
| Read1Gram(f, vocab, unigrams, warn); |
| } |
| vocab.FinishedLoading(unigrams); |
| } |
| |
| // Read ngram, write vocab ids to indices_out. |
| template <class Voc, class Weights, class Iterator> void ReadNGram(util::FilePiece &f, const unsigned char n, const Voc &vocab, Iterator indices_out, Weights &weights, PositiveProbWarn &warn) { |
| try { |
| weights.prob = f.ReadFloat(); |
| if (weights.prob > 0.0) { |
| warn.Warn(weights.prob); |
| weights.prob = 0.0; |
| } |
| for (unsigned char i = 0; i < n; ++i, ++indices_out) { |
| StringPiece word(f.ReadDelimited(kARPASpaces)); |
| WordIndex index = vocab.Index(word); |
| *indices_out = index; |
| // Check for words mapped to <unk> that are not the string <unk>. |
| UTIL_THROW_IF(index == 0 /* mapped to <unk> */ && (word != StringPiece("<unk>", 5)) && (word != StringPiece("<UNK>", 5)), |
| FormatLoadException, "Word " << word << " was not seen in the unigrams (which are supposed to list the entire vocabulary) but appears"); |
| } |
| ReadBackoff(f, weights); |
| } catch(util::Exception &e) { |
| e << " in the " << static_cast<unsigned int>(n) << "-gram at byte " << f.Offset(); |
| throw; |
| } |
| } |
| |
| } // namespace lm |
| |
| #endif // LM_READ_ARPA_H |