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// SPDX-License-Identifier: GPL-3.0-or-later
#ifndef ML_HOST_H
#define ML_HOST_H
#include "Mutex.h"
#include "Config.h"
#include "Dimension.h"
#include "Chart.h"
#include "Queue.h"
#include "ml-private.h"
#include "json/single_include/nlohmann/json.hpp"
namespace ml
{
class Host {
friend void* train_main(void *);
friend void *detect_main(void *);
public:
Host(RRDHOST *RH) :
RH(RH),
MLS(),
TS(),
HostAnomalyRate(0.0),
ThreadsRunning(false),
ThreadsCancelled(false),
ThreadsJoined(false)
{}
void addChart(Chart *C);
void removeChart(Chart *C);
void getConfigAsJson(nlohmann::json &Json) const;
void getModelsAsJson(nlohmann::json &Json);
void getDetectionInfoAsJson(nlohmann::json &Json) const;
void startAnomalyDetectionThreads();
void stopAnomalyDetectionThreads(bool join);
void scheduleForTraining(TrainingRequest TR);
void train();
void detect();
void detectOnce();
private:
RRDHOST *RH;
MachineLearningStats MLS;
TrainingStats TS;
CalculatedNumber HostAnomalyRate{0.0};
std::atomic<bool> ThreadsRunning;
std::atomic<bool> ThreadsCancelled;
std::atomic<bool> ThreadsJoined;
Queue<TrainingRequest> TrainingQueue;
Mutex M;
std::unordered_map<RRDSET *, Chart *> Charts;
netdata_thread_t TrainingThread;
netdata_thread_t DetectionThread;
};
} // namespace ml
#endif /* ML_HOST_H */
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