mirror of
https://github.com/Relintai/pmlpp.git
synced 2024-12-23 15:06:52 +01:00
61 lines
2.0 KiB
C
61 lines
2.0 KiB
C
|
#ifndef MLPP_SOFTMAX_NET_OLD_H
|
||
|
|
#define MLPP_SOFTMAX_NET_OLD_H
|
||
|
|
|
||
|
|
//
|
||
|
|
// SoftmaxNet.hpp
|
||
|
|
//
|
||
|
|
// Created by Marc Melikyan on 10/2/20.
|
||
|
|
//
|
||
|
|
|
||
|
|
#include "core/math/math_defs.h"
|
||
|
|
|
||
|
|
#include <string>
|
||
|
|
#include <vector>
|
||
|
|
|
||
|
|
class MLPPSoftmaxNetOld {
|
||
|
|
public:
|
||
|
|
MLPPSoftmaxNetOld(std::vector<std::vector<real_t>> inputSet, std::vector<std::vector<real_t>> outputSet, int n_hidden, std::string reg = "None", real_t lambda = 0.5, real_t alpha = 0.5);
|
||
|
|
std::vector<real_t> modelTest(std::vector<real_t> x);
|
||
|
|
std::vector<std::vector<real_t>> modelSetTest(std::vector<std::vector<real_t>> X);
|
||
|
|
void gradientDescent(real_t learning_rate, int max_epoch, bool UI = false);
|
||
|
|
void SGD(real_t learning_rate, int max_epoch, bool UI = false);
|
||
|
|
void MBGD(real_t learning_rate, int max_epoch, int mini_batch_size, bool UI = false);
|
||
|
|
real_t score();
|
||
|
|
void save(std::string fileName);
|
||
|
|
|
||
|
|
std::vector<std::vector<real_t>> getEmbeddings(); // This class is used (mostly) for word2Vec. This function returns our embeddings.
|
||
|
|
private:
|
||
|
|
real_t Cost(std::vector<std::vector<real_t>> y_hat, std::vector<std::vector<real_t>> y);
|
||
|
|
|
||
|
|
std::vector<std::vector<real_t>> Evaluate(std::vector<std::vector<real_t>> X);
|
||
|
|
std::tuple<std::vector<std::vector<real_t>>, std::vector<std::vector<real_t>>> propagate(std::vector<std::vector<real_t>> X);
|
||
|
|
std::vector<real_t> Evaluate(std::vector<real_t> x);
|
||
|
|
std::tuple<std::vector<real_t>, std::vector<real_t>> propagate(std::vector<real_t> x);
|
||
|
|
void forwardPass();
|
||
|
|
|
||
|
|
std::vector<std::vector<real_t>> inputSet;
|
||
|
|
std::vector<std::vector<real_t>> outputSet;
|
||
|
|
std::vector<std::vector<real_t>> y_hat;
|
||
|
|
|
||
|
|
std::vector<std::vector<real_t>> weights1;
|
||
|
|
std::vector<std::vector<real_t>> weights2;
|
||
|
|
|
||
|
|
std::vector<real_t> bias1;
|
||
|
|
std::vector<real_t> bias2;
|
||
|
|
|
||
|
|
std::vector<std::vector<real_t>> z2;
|
||
|
|
std::vector<std::vector<real_t>> a2;
|
||
|
|
|
||
|
|
int n;
|
||
|
|
int k;
|
||
|
|
int n_class;
|
||
|
|
int n_hidden;
|
||
|
|
|
||
|
|
// Regularization Params
|
||
|
|
std::string reg;
|
||
|
|
real_t lambda;
|
||
|
|
real_t alpha; /* This is the controlling param for Elastic Net*/
|
||
|
|
};
|
||
|
|
|
||
|
|
#endif /* SoftmaxNet_hpp */
|