xls-r-300m-sv-robust / kenlm /lm /quantize.cc

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1ce325b about 2 years ago

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	/* Quantize into bins of equal size as described in
	* M. Federico and N. Bertoldi. 2006. How many bits are needed
	* to store probabilities for phrase-based translation? In Proc.
	* of the Workshop on Statistical Machine Translation, pages
	* 94–101, New York City, June. Association for Computa-
	* tional Linguistics.
	*/

	#include "quantize.hh"

	#include "binary_format.hh"
	#include "lm_exception.hh"
	#include "../util/file.hh"

	#include <algorithm>
	#include <numeric>

	namespace lm {
	namespace ngram {

	namespace {

	void MakeBins(std::vector<float> &values, float *centers, uint32_t bins) {
	std::sort(values.begin(), values.end());
	std::vector<float>::const_iterator start = values.begin(), finish;
	for (uint32_t i = 0; i < bins; ++i, ++centers, start = finish) {
	finish = values.begin() + ((values.size() * static_cast<uint64_t>(i + 1)) / bins);
	if (finish == start) {
	// zero length bucket.
	centers = i ? (centers - 1) : -std::numeric_limits<float>::infinity();
	} else {
	*centers = std::accumulate(start, finish, 0.0) / static_cast<float>(finish - start);
	}
	}
	}

	const char kSeparatelyQuantizeVersion = 2;

	} // namespace

	void SeparatelyQuantize::UpdateConfigFromBinary(const BinaryFormat &file, uint64_t offset, Config &config) {
	unsigned char buffer[3];
	file.ReadForConfig(buffer, 3, offset);
	char version = buffer[0];
	config.prob_bits = buffer[1];
	config.backoff_bits = buffer[2];
	if (version != kSeparatelyQuantizeVersion) UTIL_THROW(FormatLoadException, "This file has quantization version " << (unsigned)version << " but the code expects version " << (unsigned)kSeparatelyQuantizeVersion);
	}

	void SeparatelyQuantize::SetupMemory(void *base, unsigned char order, const Config &config) {
	prob_bits_ = config.prob_bits;
	backoff_bits_ = config.backoff_bits;
	// We need the reserved values.
	if (config.prob_bits == 0) UTIL_THROW(ConfigException, "You can't quantize probability to zero");
	if (config.backoff_bits == 0) UTIL_THROW(ConfigException, "You can't quantize backoff to zero");
	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.");
	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.");
	// Reserve 8 byte header for bit counts.
	actual_base_ = static_cast<uint8_t*>(base);
	float start = reinterpret_cast<float>(actual_base_ + 8);
	for (unsigned char i = 0; i < order - 2; ++i) {
	tables_[i][0] = Bins(prob_bits_, start);
	start += (1ULL << prob_bits_);
	tables_[i][1] = Bins(backoff_bits_, start);
	start += (1ULL << backoff_bits_);
	}
	longest_ = tables_[order - 2][0] = Bins(prob_bits_, start);
	}

	void SeparatelyQuantize::Train(uint8_t order, std::vector<float> &prob, std::vector<float> &backoff) {
	TrainProb(order, prob);

	// Backoff
	float *centers = tables_[order - 2][1].Populate();
	*(centers++) = kNoExtensionBackoff;
	*(centers++) = kExtensionBackoff;
	MakeBins(backoff, centers, (1ULL << backoff_bits_) - 2);
	}

	void SeparatelyQuantize::TrainProb(uint8_t order, std::vector<float> &prob) {
	float *centers = tables_[order - 2][0].Populate();
	MakeBins(prob, centers, (1ULL << prob_bits_));
	}

	void SeparatelyQuantize::FinishedLoading(const Config &config) {
	uint8_t *actual_base = actual_base_;
	*(actual_base++) = kSeparatelyQuantizeVersion; // version
	*(actual_base++) = config.prob_bits;
	*(actual_base++) = config.backoff_bits;
	}

	} // namespace ngram
	} // namespace lm