conv_layer.h

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#pragma once
#ifndef CONV_LAYER_H 
#define CONV_LAYER_H
 
#include <iostream>
#include <eigen3/Eigen/Dense>
#include <EigenRand/EigenRand>
#include "layer.h"
#include <chrono>
using namespace Eigen;
 
typedef Matrix<double,Dynamic,Dynamic,RowMajor> RowMajMat; 
 
namespace Neural
{
    class Conv_Layer : public Layer
    {
 
        public:
            Conv_Layer(std::tuple<int,int,int> dimensions, 
                    std::tuple<int,int,int> filter, 
                    int stride, 
                    int padding);
 
            virtual Eigen::MatrixXd Forward_propagation(Eigen::MatrixXd input);
            virtual Eigen::MatrixXd Backward_propagation(Eigen::MatrixXd output_error, float learning_rate);
            virtual Json::Value toJSON();
            Eigen::MatrixXd Init_filters(int dim, int nb);
            Eigen::MatrixXd GetWeights();
            Eigen::MatrixXd GetBias();
            
        protected:
            int m_depth;
            int m_height;
            int m_width;
            int m_filter_size;
            int m_nb_filters;
            int m_stride;
            int m_padding;
 
            RowMajMat m_weights;
            RowMajMat m_bias;
 
            RowMajMat m_filter;
    };
}
#endif