| | |
| | | void train_nist(char *cfgfile) |
| | | { |
| | | srand(222222); |
| | | srand(time(0)); |
| | | network net = parse_network_cfg(cfgfile); |
| | | // srand(time(0)); |
| | | data train = load_categorical_data_csv("data/mnist/mnist_train.csv", 0, 10); |
| | | data test = load_categorical_data_csv("data/mnist/mnist_test.csv",0,10); |
| | | normalize_data_rows(train); |
| | | normalize_data_rows(test); |
| | | network net = parse_network_cfg(cfgfile); |
| | | int count = 0; |
| | | int iters = 60000/net.batch + 1; |
| | | while(++count <= 10){ |
| | | clock_t start = clock(), end; |
| | | normalize_data_rows(train); |
| | | normalize_data_rows(test); |
| | | float loss = train_network_sgd(net, train, iters); |
| | | end = clock(); |
| | | float test_acc = 0; |
| | | //if(count%1 == 0) test_acc = network_accuracy(net, test); |
| | | if(count%1 == 0) test_acc = network_accuracy(net, test); |
| | | end = clock(); |
| | | printf("%d: Loss: %f, Test Acc: %f, Time: %lf seconds\n", count, loss, test_acc,(float)(end-start)/CLOCKS_PER_SEC); |
| | | } |
| | | free_data(train); |
| | | free_data(test); |
| | | char buff[256]; |
| | | sprintf(buff, "%s.trained", cfgfile); |
| | | save_network(net, buff); |