Part 2 ChatGPT output eigen

#include <iostream>
#include <Eigen/Dense>

class LayerDense {
public:
    LayerDense(size_t n_inputs, size_t n_neurons);

    Eigen::MatrixXf forward(const Eigen::MatrixXf& inputs);

private:
    Eigen::MatrixXf weights;
    Eigen::MatrixXf biases;
};

LayerDense::LayerDense(size_t n_inputs, size_t n_neurons) {
    weights = 0.10 * Eigen::MatrixXf::Random(n_inputs, n_neurons);
    biases = Eigen::MatrixXf::Zero(1, n_neurons);
}

Eigen::MatrixXf LayerDense::forward(const Eigen::MatrixXf& inputs) {
    return inputs * weights + biases.replicate(inputs.rows(), 1);
}

int main() {
    // Define input data
    Eigen::MatrixXf inputs(3, 4);
    inputs << 1., 1., 3., 2.5,
              2., 5., -1., 2.,
              -1.5, 2.7, 3.3, -0.8;

    // Define weights and biases for the layers
    Eigen::MatrixXf weights1(4, 3);
    weights1 << 0.2, 0.8, -0.5,
                0.5, -0.91, 0.26,
                -0.26, -0.27, 0.17,
                0.87, 0.2, -0.5;

    Eigen::MatrixXf weights2(3, 3);
    weights2 << 0.2, 0.8, -0.5,
                0.5, -0.91, 0.26,
                -0.26, -0.27, 0.17;

    Eigen::MatrixXf biases1(1, 3);
    biases1 << 2., 3., 0.5;

    Eigen::MatrixXf biases2(1, 3);
    biases2 << 1., 0.4, 4.;

    // Create the layers
    LayerDense layer1(inputs.cols(), biases1.cols());
    LayerDense layer2(layer1.forward(inputs).cols(), biases2.cols());

    // Perform forward pass through the layers
    Eigen::MatrixXf layer1_output = layer1.forward(inputs);
    Eigen::MatrixXf layer2_output = layer2.forward(layer1_output);

    // Display the output
    std::cout << "Layer 1 output:\n" << layer1_output << std::endl;
    std::cout << "Layer 2 output:\n" << layer2_output << std::endl;

    return 0;
}