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Training in progress, epoch 0
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#include "print.hh"
#include "ngram_stream.hh"
#include "../../util/file_stream.hh"
#include "../../util/file.hh"
#include "../../util/mmap.hh"
#include "../../util/scoped.hh"
#include <sstream>
#include <cstring>
namespace lm {
VocabReconstitute::VocabReconstitute(int fd) {
uint64_t size = util::SizeOrThrow(fd);
util::MapRead(util::POPULATE_OR_READ, fd, 0, size, memory_);
const char *const start = static_cast<const char*>(memory_.get());
const char *i;
for (i = start; i != start + size; i += strlen(i) + 1) {
map_.push_back(i);
}
// Last one for LookupPiece.
map_.push_back(i);
}
namespace {
template <class Payload> void PrintLead(const VocabReconstitute &vocab, ProxyStream<Payload> &stream, util::FileStream &out) {
out << stream->Value().prob << '\t' << vocab.Lookup(*stream->begin());
for (const WordIndex *i = stream->begin() + 1; i != stream->end(); ++i) {
out << ' ' << vocab.Lookup(*i);
}
}
} // namespace
void PrintARPA::Run(const util::stream::ChainPositions &positions) {
VocabReconstitute vocab(vocab_fd_);
util::FileStream out(out_fd_);
out << "\\data\\\n";
for (size_t i = 0; i < positions.size(); ++i) {
out << "ngram " << (i+1) << '=' << counts_[i] << '\n';
}
out << '\n';
for (unsigned order = 1; order < positions.size(); ++order) {
out << "\\" << order << "-grams:" << '\n';
for (ProxyStream<NGram<ProbBackoff> > stream(positions[order - 1], NGram<ProbBackoff>(NULL, order)); stream; ++stream) {
PrintLead(vocab, stream, out);
out << '\t' << stream->Value().backoff << '\n';
}
out << '\n';
}
out << "\\" << positions.size() << "-grams:" << '\n';
for (ProxyStream<NGram<Prob> > stream(positions.back(), NGram<Prob>(NULL, positions.size())); stream; ++stream) {
PrintLead(vocab, stream, out);
out << '\n';
}
out << '\n';
out << "\\end\\\n";
}
} // namespace lm