Files
lms/src/libs/recommendation/impl/features/FeaturesClassifier.hpp
T

115 lines
4.4 KiB
C++

/*
* Copyright (C) 2018 Emeric Poupon
*
* This file is part of LMS.
*
* LMS is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* LMS is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with LMS. If not, see <http://www.gnu.org/licenses/>.
*/
#pragma once
#include <functional>
#include <unordered_map>
#include <optional>
#include <string>
#include "som/DataNormalizer.hpp"
#include "som/Network.hpp"
#include "FeaturesClassifierCache.hpp"
#include "FeaturesDefs.hpp"
#include "IClassifier.hpp"
namespace Database
{
class Session;
}
namespace Recommendation {
using FeatureWeight = double;
class FeaturesClassifier : public IClassifier
{
public:
FeaturesClassifier() = default;
FeaturesClassifier(const FeaturesClassifier&) = delete;
FeaturesClassifier(FeaturesClassifier&&) = delete;
FeaturesClassifier& operator=(const FeaturesClassifier&) = delete;
FeaturesClassifier& operator=(FeaturesClassifier&&) = delete;
using FeaturesFetchFunc = std::function<std::optional<std::unordered_map<std::string, std::vector<double>>>(Database::IdType /*trackId*/, const std::unordered_set<std::string>& /*features*/)>;
// Default is to retrieve the features from the database (may be slow).
// Use this only if you want to train different searchers with some cached data
static void setFeaturesFetchFunc(FeaturesFetchFunc func) { _featuresFetchFunc = func; }
static const FeatureSettingsMap& getDefaultTrainFeatureSettings();
private:
std::string_view getName() const override { return "Features"; }
bool load(Database::Session& session, bool forceReload, const ProgressCallback& progressCallback) override;
void requestCancelLoad() override;
std::unordered_set<Database::IdType> getSimilarTracksFromTrackList(Database::Session& session, Database::IdType tracklistId, std::size_t maxCount) const override;
std::unordered_set<Database::IdType> getSimilarTracks(Database::Session& session, const std::unordered_set<Database::IdType>& tracksId, std::size_t maxCount) const override;
std::unordered_set<Database::IdType> getSimilarReleases(Database::Session& session, Database::IdType releaseId, std::size_t maxCount) const override;
std::unordered_set<Database::IdType> getSimilarArtists(Database::Session& session, Database::IdType artistId, std::size_t maxCount) const override;
bool loadFromCache(Database::Session& session, const FeaturesClassifierCache& cache);
// Use training (may be very slow)
struct TrainSettings
{
std::size_t iterationCount {10};
float sampleCountPerNeuron {4};
FeatureSettingsMap featureSettingsMap;
};
bool loadFromTraining(Database::Session& session, const TrainSettings& trainSettings, const ProgressCallback& progressCallback);
using ObjectPositions = std::unordered_map<Database::IdType, std::unordered_set<SOM::Position>>;
using MatrixOfObjects = SOM::Matrix<std::unordered_set<Database::IdType>>;
bool load(Database::Session& session,
SOM::Network network,
const ObjectPositions& tracksPosition);
FeaturesClassifierCache toCache() const;
static std::unordered_set<SOM::Position> getMatchingRefVectorsPosition(const std::unordered_set<Database::IdType>& ids, const ObjectPositions& objectPositions);
static std::unordered_set<Database::IdType> getObjectsIds(const std::unordered_set<SOM::Position>& positionSet, const MatrixOfObjects& objectsMap);
std::unordered_set<Database::IdType> getSimilarObjects(const std::unordered_set<Database::IdType>& ids,
const SOM::Matrix<std::unordered_set<Database::IdType>>& objectsMap,
const ObjectPositions& objectPosition,
std::size_t maxCount) const;
bool _loadCancelled {};
std::unique_ptr<SOM::Network> _network;
double _networkRefVectorsDistanceMedian {};
MatrixOfObjects _artistsMap;
ObjectPositions _artistPositions;
MatrixOfObjects _releasesMap;
ObjectPositions _releasePositions;
MatrixOfObjects _tracksMap;
ObjectPositions _trackPositions;
static inline FeaturesFetchFunc _featuresFetchFunc;
};
} // ns Recommendation