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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
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