#include "network.h"
#include "utils.h"
#include "parser.h"
#include "option_list.h"
#include "blas.h"

#ifdef OPENCV
#include "opencv2/highgui/highgui_c.h"
#endif

void train_cifar(char *cfgfile, char *weightfile)
{
    data_seed = time(0);
    srand(time(0));
    float avg_loss = -1;
    char *base = basecfg(cfgfile);
    printf("%s\n", base);
    network net = parse_network_cfg(cfgfile);
    if(weightfile){
        load_weights(&net, weightfile);
    }
    printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);

    char *backup_directory = "/home/pjreddie/backup/";
    int classes = 10;
    int N = 50000;

    char **labels = get_labels("data/cifar/labels.txt");
    int epoch = (*net.seen)/N;
    data train = load_all_cifar10();
    while(get_current_batch(net) < net.max_batches || net.max_batches == 0){
        clock_t time=clock();

        float loss = train_network_sgd(net, train, 1);
        if(avg_loss == -1) avg_loss = loss;
        avg_loss = avg_loss*.9 + loss*.1;
        printf("%d, %.3f: %f, %f avg, %f rate, %lf seconds, %d images\n", get_current_batch(net), (float)(*net.seen)/N, loss, avg_loss, get_current_rate(net), sec(clock()-time), *net.seen);
        if(*net.seen/N > epoch){
            epoch = *net.seen/N;
            char buff[256];
            sprintf(buff, "%s/%s_%d.weights",backup_directory,base, epoch);
            save_weights(net, buff);
        }
        if(get_current_batch(net)%100 == 0){
            char buff[256];
            sprintf(buff, "%s/%s.backup",backup_directory,base);
            save_weights(net, buff);
        }
    }
    char buff[256];
    sprintf(buff, "%s/%s.weights", backup_directory, base);
    save_weights(net, buff);

    free_network(net);
    free_ptrs((void**)labels, classes);
    free(base);
    free_data(train);
}

void test_cifar(char *filename, char *weightfile)
{
    network net = parse_network_cfg(filename);
    if(weightfile){
        load_weights(&net, weightfile);
    }
    srand(time(0));

    clock_t time;
    float avg_acc = 0;
    float avg_top5 = 0;
    data test = load_cifar10_data("data/cifar/cifar-10-batches-bin/test_batch.bin");

    time=clock();

    float *acc = network_accuracies(net, test, 2);
    avg_acc += acc[0];
    avg_top5 += acc[1];
    printf("top1: %f, %lf seconds, %d images\n", avg_acc, sec(clock()-time), test.X.rows);
    free_data(test);
}

void run_cifar(int argc, char **argv)
{
    if(argc < 4){
        fprintf(stderr, "usage: %s %s [train/test/valid] [cfg] [weights (optional)]\n", argv[0], argv[1]);
        return;
    }

    char *cfg = argv[3];
    char *weights = (argc > 4) ? argv[4] : 0;
    if(0==strcmp(argv[2], "train")) train_cifar(cfg, weights);
    else if(0==strcmp(argv[2], "test")) test_cifar(cfg, weights);
}