peacock-data-public-datasets-idc-temp-code
/
cc-multilingual-main
/cc_net
/third_party
/kenlm
/lm
/read_arpa.hh
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 | |