| | |
| | | srand(0); |
| | | int i = 0; |
| | | char *labels[] = {"cat","dog"}; |
| | | double lr = .00001; |
| | | double momentum = .9; |
| | | double decay = 0.01; |
| | | while(i++ < 1000 || 1){ |
| | | data train = load_data_image_pathfile_random("train_paths.txt", 1000, labels, 2); |
| | | train_network(net, train, .0005, 0, 0); |
| | | train_network(net, train, lr, momentum, decay); |
| | | free_data(train); |
| | | printf("Round %d\n", i); |
| | | } |
| | |
| | | double lr = .0005; |
| | | double momentum = .9; |
| | | double decay = 0.01; |
| | | clock_t start = clock(), end; |
| | | while(++count <= 1000){ |
| | | double acc = train_network_sgd(net, train, 1000, lr, momentum, decay); |
| | | printf("Training Accuracy: %lf, Params: %f %f %f\n", acc, lr, momentum, decay); |
| | | double acc = train_network_sgd(net, train, 6400, lr, momentum, decay); |
| | | printf("%5d Training Loss: %lf, Params: %f %f %f, ",count*100, 1.-acc, lr, momentum, decay); |
| | | end = clock(); |
| | | printf("Time: %lf seconds\n", (double)(end-start)/CLOCKS_PER_SEC); |
| | | start=end; |
| | | visualize_network(net); |
| | | cvWaitKey(100); |
| | | //lr /= 2; |
| | |
| | | { |
| | | //test_kernel_update(); |
| | | //test_split(); |
| | | test_ensemble(); |
| | | //test_nist(); |
| | | //test_ensemble(); |
| | | test_nist(); |
| | | //test_full(); |
| | | //test_random_preprocess(); |
| | | //test_random_classify(); |