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以下神经网络代码,请添加输入:{{1,0},{1,1}},输出{1,0};添加反向传播,梯度下降等训练!

以下神经网络代码,请添加输入:{{1,0},{1,1}},输出{1,0};添加反向传播,梯度下降等训练!
#include <iostream>
#include<vector>
#include<Eigen/Dense>
#include<random>
#include<fstream>using namespace std;Eigen::MatrixXd forwardPropagation(const std::vector<Eigen::MatrixXd>& weights, const Eigen::VectorXd& input) {Eigen::MatrixXd output = input;for (const auto& w : weights) {output.conservativeResize(output.rows(), 1);  // Make sure it's a column vectoroutput = w * output;output = output.unaryExpr([](double x) { return 1.0 / (1.0 + std::exp(-x)); }); // Activation function (sigmoid)}return output;
}//Eigen::MatrixXd forwardPropagation(int main()
{// Read network architecture from filestd::vector<int> layers = readLayers("\\s.txt");// Initialize weights ra