sosokker/CPP-Neural-Network
1
0
Fork 0
mirror of https://github.com/Sosokker/CPP-Neural-Network.git synced 2025-12-18 18:14:04 +01:00
Code Issues Actions Packages Projects Releases Wiki Activity

Fix Indentation

Browse Source
This commit is contained in:
sosokker 2023-08-22 01:12:42 +07:00
parent fde93f30ac
commit dcd8ff7172
1 changed files with 41 additions and 43 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

84
src/Layers/Layers.hpp
View File

@ -1,53 +1,51 @@
#pragma once
#include <vector>
#include <utility>
#pragma once
#include <vector>
#include <utility>
class Layer {
public:
virtual void forward(const std::vector<double>& inputs, bool training) = 0;
virtual void backward(std::vector<double>& dvalues) = 0;
virtual std::pair<std::vector<std::vector<double>>, std::vector<std::vector<double>>> get_parameters() const = 0;
virtual void set_parameters(const std::vector<std::vector<double>>& weights, const std::vector<std::vector<double>>& biases) = 0;
};
class Layer {
public:
virtual void forward(const std::vector<double>& inputs, bool training) = 0;
virtual void backward(std::vector<double>& dvalues) = 0;
virtual std::pair<std::vector<std::vector<double>>, std::vector<std::vector<double>>> get_parameters() const = 0;
virtual void set_parameters(const std::vector<std::vector<double>>& weights, const std::vector<std::vector<double>>& biases) = 0;
};
class Layer_Dense : public Layer {
private:
double weight_regularizer_l1, weight_regularizer_l2,
bias_regularizer_l1, bias_regularizer_l2;
std::vector<std::vector<double>> weights, biases;
std::vector<double> inputs;
class Layer_Dense : public Layer {
private:
double weight_regularizer_l1, weight_regularizer_l2,
bias_regularizer_l1, bias_regularizer_l2;
std::vector<std::vector<double>> weights, biases;
std::vector<double> inputs;
public:
Layer_Dense(int n_inputs, int n_neurons,
double weight_regularizer_l1,
double weight_regularizer_l2,
double bias_regularizer_l1,
double bias_regularizer_l2);
public:
Layer_Dense(int n_inputs, int n_neurons,
double weight_regularizer_l1,
double weight_regularizer_l2,
double bias_regularizer_l1,
double bias_regularizer_l2);
void forward(const std::vector<double>& inputs, bool training) override;
void backward(std::vector<double>& dvalues) override;
std::pair<std::vector<std::vector<double>>, std::vector<std::vector<double>>> get_parameters() const override;
void set_parameters(const std::vector<std::vector<double>>& weights, const std::vector<std::vector<double>>& biases) override;
};
void forward(const std::vector<double>& inputs, bool training) override;
void backward(std::vector<double>& dvalues) override;
std::pair<std::vector<std::vector<double>>, std::vector<std::vector<double>>> get_parameters() const override;
void set_parameters(const std::vector<std::vector<double>>& weights, const std::vector<std::vector<double>>& biases) override;
};
class Layer_Dropout : public Layer {
private:
double rate;
class Layer_Dropout : public Layer {
private:
double rate;
public:
Layer_Dropout(double rate);
public:
Layer_Dropout(double rate);
void forward(const std::vector<double>& inputs, bool training) override;
void backward(std::vector<double>& dvalues) override;
};
void forward(const std::vector<double>& inputs, bool training) override;
void backward(std::vector<double>& dvalues) override;
};
class Layer_Input {
private:
std::vector<double> output;
class Layer_Input {
private:
std::vector<double> output;
public:
void forward(const std::vector<double>& inputs, bool training);
};
// Add other Layer classes as needed
public:
void forward(const std::vector<double>& inputs, bool training);
};