start of the passes class

#include <iostream>
#include <vector>
#include <cmath>

using namespace std;

// Function to apply ReLU activation
float ReLU(float x) {
    return max(0.0f, x);
}

class LayerDense {
public:
    void initialize(size_t n_inputs, size_t n_neurons, const vector<vector<float>>& weights, const vector<float>& biases);
    vector<vector<float>> forward(const vector<vector<float>>& inputs);
private:
    vector<vector<float>> weights;
    vector<float> biases;
};

void LayerDense::initialize(size_t n_inputs, size_t n_neurons, const vector<vector<float>>& init_weights, const vector<float>& init_biases) {
    weights = init_weights;
    biases = init_biases;
}

vector<vector<float>> LayerDense::forward(const vector<vector<float>>& inputs) {
    vector<vector<float>> output(inputs.size(), vector<float>(biases.size(), 0.0));
    for (size_t i = 0; i < inputs.size(); ++i) {
        for (size_t k = 0; k < biases.size(); ++k) {
            float sum = 0.0;
            for (size_t j = 0; j < inputs[i].size(); ++j) {
                sum += inputs[i][j] * weights[j][k];
            }
            output[i][k] = sum + biases[k];
            // Apply ReLU activation
            output[i][k] = ReLU(output[i][k]);
        }
    }
    return output;
}

int main() {
    // Example usage
    LayerDense layer;
    size_t num_layers = 2; // Number of layers
    size_t neurons_per_layer = 2; // Number of neurons per layer

    // Specify weights and biases for each neuron
    vector<vector<float>> weights = {{0.1, 0.2}, {0.3, 0.4}, {0.5, 0.6}}; // Example weights
    vector<float> biases = {0.7, 0.8}; // Example biases

    layer.initialize(3, neurons_per_layer, weights, biases); // Number of inputs is 3

    vector<vector<float>> inputs = {{1.2f, 2.3f, 3.4f}, {4.5f, 5.6f, 6.7f}}; // Example input data
    vector<vector<float>> output = layer.forward(inputs); // Perform forward pass

    // Display the output
    cout << "Output after forward pass:" << endl;
    for (const auto& row : output) {
        for (float val : row) {
            cout << val << " ";
        }
        cout << endl;
    }
    return 0;
}