/** @brief Shows the output of the network after being trained on the MNIST dataset.
 *  NOTE! This does not actually train the network. It only shows the output of the network.
 *  The output is exactly the one from mnist_train.c. We have trained it so you can see the accuracy.
 *  The accuracy is 95%. Please feel free to train it yourself using mnist_train.c, it takes about 3 minutes
 *  although that of course depends on your machine.
 *  
 *  @author Saleh Bubshait
 */

#include "../../src/network.h"
#include "mnist_loader.h"

int main(void) {

    load_mnist(train_image, train_label, test_image, test_label);
    printf("LOADING TRAINED MNIST DATASET. PLEASE WAIT!\n");
    // Load the trained neural network. This is the one trained in mnist_train.c
    Network *network = network_load("examples/MNIST/data/trained_mnist");

    Matrix *input = matrix_create(784, 1);
    Matrix *target = matrix_create(10, 1);
    int correct = 0;

    for (int i = 0; i < NUM_TEST; i++) {
        matrix_initialise(input, test_image[i]);

        network_predict(network, input);
        int maxIndex = 0;
        for (int j = 1; j < 10; j++) {
            if (network_output(network)[j] > network_output(network)[maxIndex]) {
                maxIndex = j;
            }
        }
        if (maxIndex == test_label[i]) {
            correct++;
        }
    }
    putchar('\n');
    printf("====================================\n");
    printf("Accuracy: %lf \n", (double)correct / NUM_TEST);
    printf("====================================\n");

    // Save the trained network
    network_store(network, "trained_mnist");

    matrix_free(input);
    matrix_free(target);
    network_free(network);

    return 0;
}