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#ifndef LM_READ_ARPA__
#define LM_READ_ARPA__
#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;
}
if (f.get() != '\t') UTIL_THROW(FormatLoadException, "Expected tab after probability");
Weights &value = unigrams[vocab.Insert(f.ReadDelimited(kARPASpaces))];
value.prob = prob;
ReadBackoff(f, value);
} catch(util::Exception &e) {
e << " in the 1-gram at byte " << f.Offset();
throw;
}
}
// Return true if a positive log probability came out.
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);
}
// Return true if a positive log probability came out.
template <class Voc, class Weights> void ReadNGram(util::FilePiece &f, const unsigned char n, const Voc &vocab, WordIndex *const reverse_indices, Weights &weights, PositiveProbWarn &warn) {
try {
weights.prob = f.ReadFloat();
if (weights.prob > 0.0) {
warn.Warn(weights.prob);
weights.prob = 0.0;
}
for (WordIndex *vocab_out = reverse_indices + n - 1; vocab_out >= reverse_indices; --vocab_out) {
*vocab_out = vocab.Index(f.ReadDelimited(kARPASpaces));
}
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__
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