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Auto reformatted the base, ref #470

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This commit is contained in:
emeric
2024-05-24 23:31:52 +02:00
parent 83b868673c
commit 39941d90a3
460 changed files with 8583 additions and 8514 deletions
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src/libs/services/recommendation/impl/features/FeaturesEngine.cpp
+37 -41
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@@ -21,6 +21,8 @@
#include <numeric>
#include "core/ILogger.hpp"
#include "core/Random.hpp"
#include "database/Artist.hpp"
#include "database/Db.hpp"
#include "database/Release.hpp"
@@ -30,8 +32,6 @@
#include "database/TrackFeatures.hpp"
#include "database/TrackList.hpp"
#include "som/DataNormalizer.hpp"
#include "core/ILogger.hpp"
#include "core/Random.hpp"
namespace lms::recommendation
{
@@ -47,7 +47,7 @@ namespace lms::recommendation
std::optional<som::InputVector> convertFeatureValuesMapToInputVector(const FeatureValuesMap& featureValuesMap, std::size_t nbDimensions)
{
std::size_t i{};
std::optional<som::InputVector> res{ som::InputVector {nbDimensions} };
std::optional<som::InputVector> res{ som::InputVector{ nbDimensions } };
for (const auto& [featureName, values] : featureValuesMap)
{
if (values.size() != getFeatureDef(featureName).nbDimensions)
@@ -80,17 +80,16 @@ namespace lms::recommendation
return weights;
}
}
} // namespace
const FeatureSettingsMap& FeaturesEngine::getDefaultTrainFeatureSettings()
{
static const FeatureSettingsMap defaultTrainFeatureSettings
{
{ "lowlevel.spectral_energyband_high.mean", {1}},
{ "lowlevel.spectral_rolloff.median", {1}},
{ "lowlevel.spectral_contrast_valleys.var", {1}},
{ "lowlevel.erbbands.mean", {1}},
{ "lowlevel.gfcc.mean", {1}},
static const FeatureSettingsMap defaultTrainFeatureSettings{
{ "lowlevel.spectral_energyband_high.mean", { 1 } },
{ "lowlevel.spectral_rolloff.median", { 1 } },
{ "lowlevel.spectral_contrast_valleys.var", { 1 } },
{ "lowlevel.erbbands.mean", { 1 } },
{ "lowlevel.gfcc.mean", { 1 } },
};
return defaultTrainFeatureSettings;
@@ -104,12 +103,12 @@ namespace lms::recommendation
std::transform(std::cbegin(trainSettings.featureSettingsMap), std::cend(trainSettings.featureSettingsMap), std::inserter(featureNames, std::begin(featureNames)),
[](const auto& itFeatureSetting) { return itFeatureSetting.first; });
const std::size_t nbDimensions{ std::accumulate(std::cbegin(featureNames), std::cend(featureNames), std::size_t {0},
[](std::size_t sum, const FeatureName& featureName) { return sum + getFeatureDef(featureName).nbDimensions; }) };
const std::size_t nbDimensions{ std::accumulate(std::cbegin(featureNames), std::cend(featureNames), std::size_t{ 0 },
[](std::size_t sum, const FeatureName& featureName) { return sum + getFeatureDef(featureName).nbDimensions; }) };
LMS_LOG(RECOMMENDATION, DEBUG, "Features dimension = " << nbDimensions);
Session & session{ _db.getTLSSession() };
Session& session{ _db.getTLSSession() };
RangeResults<TrackFeaturesId> trackFeaturesIds;
{
@@ -178,10 +177,9 @@ namespace lms::recommendation
som::InputVector weights{ getInputVectorWeights(trainSettings.featureSettingsMap, nbDimensions) };
network.setDataWeights(weights);
auto somProgressCallback{ [&](const som::Network::CurrentIteration& iter)
{
auto somProgressCallback{ [&](const som::Network::CurrentIteration& iter) {
LMS_LOG(RECOMMENDATION, DEBUG, "Current pass = " << iter.idIteration << " / " << iter.iterationCount);
progressCallback(Progress {iter.idIteration, iter.iterationCount});
progressCallback(Progress{ iter.idIteration, iter.iterationCount });
} };
LMS_LOG(RECOMMENDATION, DEBUG, "Training network...");
@@ -216,15 +214,14 @@ namespace lms::recommendation
TrackContainer FeaturesEngine::findSimilarTracksFromTrackList(TrackListId trackListId, std::size_t maxCount) const
{
const TrackContainer trackIds{ [&]
{
const TrackContainer trackIds{ [&] {
TrackContainer res;
Session& session {_db.getTLSSession()};
Session& session{ _db.getTLSSession() };
auto transaction {session.createReadTransaction()};
auto transaction{ session.createReadTransaction() };
const TrackList::pointer trackList {TrackList::find(session, trackListId)};
const TrackList::pointer trackList{ TrackList::find(session, trackListId) };
if (trackList)
res = trackList->getTrackIds();
@@ -245,10 +242,10 @@ namespace lms::recommendation
auto transaction{ session.createReadTransaction() };
similarTrackIds.erase(std::remove_if(std::begin(similarTrackIds), std::end(similarTrackIds),
[&](TrackId trackId)
{
return !Track::exists(session, trackId);
}), std::end(similarTrackIds));
[&](TrackId trackId) {
return !Track::exists(session, trackId);
}),
std::end(similarTrackIds));
}
return similarTrackIds;
@@ -256,7 +253,7 @@ namespace lms::recommendation
ReleaseContainer FeaturesEngine::getSimilarReleases(ReleaseId releaseId, std::size_t maxCount) const
{
auto similarReleaseIds{ getSimilarObjects({releaseId}, _releaseMatrix, _releasePositions, maxCount) };
auto similarReleaseIds{ getSimilarObjects({ releaseId }, _releaseMatrix, _releasePositions, maxCount) };
Session& session{ _db.getTLSSession() };
@@ -266,10 +263,10 @@ namespace lms::recommendation
auto transaction{ session.createReadTransaction() };
similarReleaseIds.erase(std::remove_if(std::begin(similarReleaseIds), std::end(similarReleaseIds),
[&](ReleaseId releaseId)
{
return !Release::exists(session, releaseId);
}), std::end(similarReleaseIds));
[&](ReleaseId releaseId) {
return !Release::exists(session, releaseId);
}),
std::end(similarReleaseIds));
}
return similarReleaseIds;
@@ -277,17 +274,16 @@ namespace lms::recommendation
ArtistContainer FeaturesEngine::getSimilarArtists(ArtistId artistId, core::EnumSet<TrackArtistLinkType> linkTypes, std::size_t maxCount) const
{
auto getSimilarArtistIdsForLinkType{ [&](TrackArtistLinkType linkType)
{
auto getSimilarArtistIdsForLinkType{ [&](TrackArtistLinkType linkType) {
ArtistContainer similarArtistIds;
const auto itArtists {_artistMatrix.find(linkType)};
const auto itArtists{ _artistMatrix.find(linkType) };
if (itArtists == std::cend(_artistMatrix))
{
return similarArtistIds;
}
return getSimilarObjects({artistId}, itArtists->second, _artistPositions, maxCount);
return getSimilarObjects({ artistId }, itArtists->second, _artistPositions, maxCount);
} };
std::unordered_set<ArtistId> similarArtistIds;
@@ -306,10 +302,10 @@ namespace lms::recommendation
auto transaction{ session.createReadTransaction() };
res.erase(std::remove_if(std::begin(res), std::end(res),
[&](ArtistId artistId)
{
return !Artist::exists(session, artistId);
}), std::end(res));
[&](ArtistId artistId) {
return !Artist::exists(session, artistId);
}),
std::end(res));
}
while (res.size() > maxCount)
@@ -364,7 +360,7 @@ namespace lms::recommendation
LMS_LOG(RECOMMENDATION, DEBUG, "Constructing maps...");
Session & session{ _db.getTLSSession() };
Session& session{ _db.getTLSSession() };
for (const auto& [trackId, positions] : trackPositions)
{
@@ -410,4 +406,4 @@ namespace lms::recommendation
LMS_LOG(RECOMMENDATION, INFO, "Classifier successfully loaded!");
}
} // ns Recommendation
} // namespace lms::recommendation