mirror of
https://github.com/moses-smt/mosesdecoder.git
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85 lines
3.4 KiB
C++
85 lines
3.4 KiB
C++
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#include "lm/quantize.hh"
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#include "lm/lm_exception.hh"
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#include <algorithm>
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#include <numeric>
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#include <unistd.h>
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namespace lm {
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namespace ngram {
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/* Quantize into bins of equal size as described in
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* M. Federico and N. Bertoldi. 2006. How many bits are needed
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* to store probabilities for phrase-based translation? In Proc.
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* of the Workshop on Statistical Machine Translation, pages
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* 94–101, New York City, June. Association for Computa-
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* tional Linguistics.
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*/
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namespace {
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void MakeBins(float *values, float *values_end, float *centers, uint32_t bins) {
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std::sort(values, values_end);
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const float *start = values, *finish;
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for (uint32_t i = 0; i < bins; ++i, ++centers, start = finish) {
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finish = values + (((values_end - values) * static_cast<uint64_t>(i + 1)) / bins);
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if (finish == start) {
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// zero length bucket.
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*centers = i ? *(centers - 1) : -std::numeric_limits<float>::infinity();
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} else {
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*centers = std::accumulate(start, finish, 0.0) / static_cast<float>(finish - start);
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}
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}
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}
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const char kSeparatelyQuantizeVersion = 1;
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} // namespace
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void SeparatelyQuantize::UpdateConfigFromBinary(int fd, const std::vector<uint64_t> &/*counts*/, Config &config) {
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char version;
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if (read(fd, &version, 1) != 1 || read(fd, &config.prob_bits, 1) != 1 || read(fd, &config.backoff_bits, 1) != 1)
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UTIL_THROW(util::ErrnoException, "Failed to read header for quantization.");
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if (version != kSeparatelyQuantizeVersion) UTIL_THROW(FormatLoadException, "This file has quantization version " << (unsigned)version << " but the code expects version " << (unsigned)kSeparatelyQuantizeVersion);
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}
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void SeparatelyQuantize::SetupMemory(void *start, const Config &config) {
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// Reserve 8 byte header for bit counts.
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start_ = reinterpret_cast<float*>(static_cast<uint8_t*>(start) + 8);
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prob_bits_ = config.prob_bits;
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backoff_bits_ = config.backoff_bits;
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// We need the reserved values.
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if (config.prob_bits == 0) UTIL_THROW(ConfigException, "You can't quantize probability to zero");
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if (config.backoff_bits == 0) UTIL_THROW(ConfigException, "You can't quantize backoff to zero");
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if (config.prob_bits > 25) UTIL_THROW(ConfigException, "For efficiency reasons, quantizing probability supports at most 25 bits. Currently you have requested " << static_cast<unsigned>(config.prob_bits) << " bits.");
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if (config.backoff_bits > 25) UTIL_THROW(ConfigException, "For efficiency reasons, quantizing backoff supports at most 25 bits. Currently you have requested " << static_cast<unsigned>(config.backoff_bits) << " bits.");
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}
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void SeparatelyQuantize::Train(uint8_t order, std::vector<float> &prob, std::vector<float> &backoff) {
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TrainProb(order, prob);
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// Backoff
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float *centers = start_ + TableStart(order) + ProbTableLength();
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*(centers++) = kNoExtensionBackoff;
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*(centers++) = kExtensionBackoff;
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MakeBins(&*backoff.begin(), &*backoff.end(), centers, (1ULL << backoff_bits_) - 2);
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}
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void SeparatelyQuantize::TrainProb(uint8_t order, std::vector<float> &prob) {
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float *centers = start_ + TableStart(order);
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*(centers++) = kBlankProb;
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MakeBins(&*prob.begin(), &*prob.end(), centers, (1ULL << prob_bits_) - 1);
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}
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void SeparatelyQuantize::FinishedLoading(const Config &config) {
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uint8_t *actual_base = reinterpret_cast<uint8_t*>(start_) - 8;
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*(actual_base++) = kSeparatelyQuantizeVersion; // version
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*(actual_base++) = config.prob_bits;
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*(actual_base++) = config.backoff_bits;
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}
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} // namespace ngram
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} // namespace lm
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