xls-r-300m-sv-robust / kenlm /lm /interpolate /tune_instances.hh

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	#ifndef LM_INTERPOLATE_TUNE_INSTANCE_H
	#define LM_INTERPOLATE_TUNE_INSTANCE_H

	#include "tune_matrix.hh"
	#include "../word_index.hh"
	#include "../../util/scoped.hh"
	#include "../../util/stream/config.hh"
	#include "../../util/string_piece.hh"

	#include <boost/optional.hpp>

	#include <vector>

	namespace util { namespace stream {
	class Chain;
	class FileBuffer;
	}} // namespaces

	namespace lm { namespace interpolate {

	typedef uint32_t InstanceIndex;
	typedef uint32_t ModelIndex;

	struct Extension {
	// Which tuning instance does this belong to?
	InstanceIndex instance;
	WordIndex word;
	ModelIndex model;
	// ln p_{model} (word \| context(instance))
	float ln_prob;

	bool operator<(const Extension &other) const;
	};

	class ExtensionsFirstIteration;

	struct InstancesConfig {
	// For batching the model reads. This is per order.
	std::size_t model_read_chain_mem;
	// This is being sorted, make it larger.
	std::size_t extension_write_chain_mem;
	std::size_t lazy_memory;
	util::stream::SortConfig sort;
	};

	class Instances {
	private:
	typedef Eigen::Matrix<Accum, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> BackoffMatrix;

	public:
	Instances(int tune_file, const std::vector<StringPiece> &model_names, const InstancesConfig &config);

	// For destruction of forward-declared classes.
	~Instances();

	// Full backoff from unigram for each model.
	typedef BackoffMatrix::ConstRowXpr FullBackoffs;
	FullBackoffs LNBackoffs(InstanceIndex instance) const {
	return ln_backoffs_.row(instance);
	}

	InstanceIndex NumInstances() const { return ln_backoffs_.rows(); }

	const Vector &CorrectGradientTerm() const { return neg_ln_correct_sum_; }

	const Matrix &LNUnigrams() const { return ln_unigrams_; }

	// Entry size to use to configure the chain (since in practice order is needed).
	std::size_t ReadExtensionsEntrySize() const;
	void ReadExtensions(util::stream::Chain &chain);

	// Vocab id of the beginning of sentence. Used to ignore it for normalization.
	WordIndex BOS() const { return bos_; }

	private:
	// Allow the derivatives test to get access.
	friend class MockInstances;
	Instances();

	// backoffs_(instance, model) is the backoff all the way to unigrams.
	BackoffMatrix ln_backoffs_;

	// neg_correct_sum_(model) = -\sum_{instances} ln p_{model}(correct(instance) \| context(instance)).
	// This appears as a term in the gradient.
	Vector neg_ln_correct_sum_;

	// ln_unigrams_(word, model) = ln p_{model}(word).
	Matrix ln_unigrams_;

	// This is the source of data for the first iteration.
	util::scoped_ptr<ExtensionsFirstIteration> extensions_first_;

	// Source of data for subsequent iterations. This contains already-sorted data.
	util::scoped_ptr<util::stream::FileBuffer> extensions_subsequent_;

	WordIndex bos_;

	std::string temp_prefix_;
	};

	}} // namespaces
	#endif // LM_INTERPOLATE_TUNE_INSTANCE_H