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Refactor library structure

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Ricardo Montañana Gómez
2024-03-08 22:20:54 +01:00
parent 1231f4522a
commit 635ef22520
56 changed files with 64 additions and 68 deletions
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59
bayesnet/classifiers/Classifier.h Normal file
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#ifndef CLASSIFIER_H
#define CLASSIFIER_H
#include <torch/torch.h>
#include "bayesnet/utils/BayesMetrics.h"
#include "bayesnet/network/Network.h"
#include "bayesnet/BaseClassifier.h"
namespace bayesnet {
class Classifier : public BaseClassifier {
public:
Classifier(Network model);
virtual ~Classifier() = default;
Classifier& fit(std::vector<std::vector<int>>& X, std::vector<int>& y, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states) override;
Classifier& fit(torch::Tensor& X, torch::Tensor& y, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states) override;
Classifier& fit(torch::Tensor& dataset, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states) override;
Classifier& fit(torch::Tensor& dataset, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states, const torch::Tensor& weights) override;
void addNodes();
int getNumberOfNodes() const override;
int getNumberOfEdges() const override;
int getNumberOfStates() const override;
int getClassNumStates() const override;
torch::Tensor predict(torch::Tensor& X) override;
std::vector<int> predict(std::vector<std::vector<int>>& X) override;
torch::Tensor predict_proba(torch::Tensor& X) override;
std::vector<std::vector<double>> predict_proba(std::vector<std::vector<int>>& X) override;
status_t getStatus() const override { return status; }
std::string getVersion() override { return { project_version.begin(), project_version.end() }; };
float score(torch::Tensor& X, torch::Tensor& y) override;
float score(std::vector<std::vector<int>>& X, std::vector<int>& y) override;
std::vector<std::string> show() const override;
std::vector<std::string> topological_order() override;
std::vector<std::string> getNotes() const override { return notes; }
void dump_cpt() const override;
void setHyperparameters(const nlohmann::json& hyperparameters) override; //For classifiers that don't have hyperparameters
protected:
bool fitted;
unsigned int m, n; // m: number of samples, n: number of features
Network model;
Metrics metrics;
std::vector<std::string> features;
std::string className;
std::map<std::string, std::vector<int>> states;
torch::Tensor dataset; // (n+1)xm tensor
status_t status = NORMAL;
std::vector<std::string> notes; // Used to store messages occurred during the fit process
void checkFitParameters();
virtual void buildModel(const torch::Tensor& weights) = 0;
void trainModel(const torch::Tensor& weights) override;
void buildDataset(torch::Tensor& y);
private:
Classifier& build(const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states, const torch::Tensor& weights);
};
}
#endif