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Network.cpp
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Network.cpp
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#include "Network.h"
#include <iostream>
#include <sstream>
#include <fstream>
#include <sstream>
#include <istream>
#include <ostream>
void NeuralNetwork::CreateNeurons() {
_V2(float) NewNeurons;
for (int x = 0; x < this->Layers.size(); x++) {
_V(float) NewNeuronsArray;
for (int y = 0; y < this->Layers[x]; y++) {
NewNeuronsArray.push_back(0);
}
NewNeurons.push_back(NewNeuronsArray);
}
this->Neurons = NewNeurons;
}
void NeuralNetwork::CreateBiases() {
_V2(float) NewBiases;
for (int x = 0; x < this->Layers.size(); x++) {
_V(float) NewBiasesArray;
for (int y = 0; y < this->Layers[x]; y++) {
NewBiasesArray.push_back(Random(-0.5f, 0.5f));
}
NewBiases.push_back(NewBiasesArray);
}
this->Biases = NewBiases;
}
void NeuralNetwork::CreateWeights() {
_V3(float) NewWeights;
for (int x = 1; x < this->Layers.size(); x++) {
_V2(float) NewWeightsArray;
int NeuronsInPreviousLayer = this->Layers[x - 1];
for (int y = 0; y < this->Neurons[x].size(); y++) {
_V(float) NewWeightsArrayArray;
for (int z = 0; z < NeuronsInPreviousLayer; z++) {
NewWeightsArrayArray.push_back(Random(-0.5f, 0.5f));
}
NewWeightsArray.push_back(NewWeightsArrayArray);
}
NewWeights.push_back(NewWeightsArray);
}
this->Weights = NewWeights;
}
_V(float) NeuralNetwork::Forward(_V(float) Input) {
for (int x = 0; x < Input.size(); x++) {
this->Neurons[0][x] = Input[x];
}
for (int x = 1; x < this->Layers.size(); x++) {
int WorkingLayer = x - 1;
for (int y = 0; y < this->Neurons[x].size(); y++) {
float Value = 0.0f;
for (int z = 0; z < this->Neurons[WorkingLayer].size(); z++) {
Value += this->Weights[WorkingLayer][y][z] * this->Neurons[WorkingLayer][z];
}
this->Neurons[x][y] = tanh(Value + this->Biases[x][y]);
}
}
return this->Neurons[Neurons.size() - 1];
}
void NeuralNetwork::Mutate(float Chance, float Value) {
for (int x = 0; x < this->Biases.size(); x++) {
for (int y = 0; y < this->Biases[x].size(); y++) {
if (Random(0.0f, Chance) <= 0.5) {
this->Biases[x][y] += Random(-Value, Value);
}
}
}
for (int x = 0; x < this->Weights.size(); x++) {
for (int y = 0; y < this->Weights[x].size(); y++) {
for (int z = 0; z < this->Weights[x][y].size(); z++) {
if (Random(0.0f, Chance) <= 0.5) {
this->Weights[x][y][z] += Random(-Value, Value);
}
}
}
}
}
void NeuralNetwork::CloneFrom(NeuralNetwork Other) {
this->Biases = Other.Biases;
this->Weights = Other.Weights;
this->Fitness = Other.Fitness;
}
NeuralNetwork::ComparisonResults NeuralNetwork::CompareTo(NeuralNetwork Other) {
if (Other.Fitness < this->Fitness)
return NeuralNetwork::ComparisonResults::Worse;
else if (Other.Fitness > this->Fitness)
return NeuralNetwork::ComparisonResults::Better;
return NeuralNetwork::ComparisonResults::Equal;
}
bool NeuralNetwork::Save(std::string Path) {
std::ofstream File(Path);
if (!File.is_open())
return false;
for (int x = 0; x < this->Biases.size(); x++) {
for (int y = 0; y < this->Biases[x].size(); y++) {
File << std::to_string(this->Biases[x][y]) << "\n";
}
}
for (int x = 0; x < this->Weights.size(); x++) {
for (int y = 0; y < this->Weights[x].size(); y++) {
for (int z = 0; z < this->Weights[x][y].size(); z++) {
File << std::to_string(this->Weights[x][y][z]) << "\n";
}
}
}
File.close();
return true;
}
bool NeuralNetwork::Load(std::string Path) {
std::ifstream File(Path);
if (!File.is_open())
return false;
// Read all lines from file
_V(std::string) Lines;
std::string CurrentLine;
while (getline(File, CurrentLine)) {
Lines.push_back(CurrentLine);
}
File.close();
int Index = 1;
for (int x = 0; x < this->Biases.size(); x++) {
for (int y = 0; y < this->Biases[x].size(); y++) {
Biases[x][y] = std::stof(Lines[Index]);
Index++;
}
}
for (int x = 0; x < this->Weights.size(); x++) {
for (int y = 0; y < this->Weights[x].size(); y++) {
for (int z = 0; z < this->Weights[x][y].size(); z++) {
Index++;
if (Lines.size() >= Index + 1) {
this->Weights[x][y][z] = std::stof(Lines[Index]);
}
}
}
}
return true;
}
NeuralNetwork::NeuralNetwork(_V(int) NewLayers, bool CreateID) {
#ifdef _NETWORK_ID
if (CreateID) {
this->Id = _nid::CurrentId;
_nid::CurrentId += 1;
}
#endif
this->Layers = NewLayers;
for (int i = 0; i < this->Layers.size(); i++) {
this->Layers[i] = NewLayers[i];
}
CreateNeurons();
CreateBiases();
CreateWeights();
if (CreateID) {
_L("Initialized network", false);
#ifdef _NETWORK_ID
_L(" with ID " + std::to_string(this->Id), false);
#endif
_L("!", true);
}
}