| | |
| | | |
| | | void train_imagenet() |
| | | { |
| | | network net = parse_network_cfg("/home/pjreddie/imagenet_backup/imagenet_backup_slower_larger_870.cfg"); |
| | | network net = parse_network_cfg("cfg/imagenet_backup_slowest_2340.cfg"); |
| | | printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay); |
| | | int imgs = 1000/net.batch+1; |
| | | srand(986987); |
| | | srand(6472345); |
| | | int i = 0; |
| | | char **labels = get_labels("/home/pjreddie/data/imagenet/cls.labels.list"); |
| | | list *plist = get_paths("/data/imagenet/cls.train.list"); |
| | |
| | | free_data(train); |
| | | if(i%10==0){ |
| | | char buff[256]; |
| | | sprintf(buff, "/home/pjreddie/imagenet_backup/imagenet_backup_larger_%d.cfg", i); |
| | | sprintf(buff, "/home/pjreddie/imagenet_backup/imagenet_small_%d.cfg", i); |
| | | save_network(net, buff); |
| | | } |
| | | } |
| | |
| | | |
| | | void test_visualize() |
| | | { |
| | | network net = parse_network_cfg("cfg/imagenet_test.cfg"); |
| | | network net = parse_network_cfg("cfg/imagenet.cfg"); |
| | | visualize_network(net); |
| | | cvWaitKey(0); |
| | | } |
| | |
| | | translate_data_rows(train, -144); |
| | | translate_data_rows(test, -144); |
| | | int count = 0; |
| | | int iters = 10000/net.batch; |
| | | int iters = 1000/net.batch; |
| | | while(++count <= 5){ |
| | | clock_t start = clock(), end; |
| | | float loss = train_network_sgd(net, train, iters); |
| | |
| | | float test_acc = network_accuracy(net, test); |
| | | printf("%d: Loss: %f, Test Acc: %f, Time: %lf seconds, LR: %f, Momentum: %f, Decay: %f\n", count, loss, test_acc,(float)(end-start)/CLOCKS_PER_SEC, net.learning_rate, net.momentum, net.decay); |
| | | } |
| | | #ifdef GPU |
| | | count = 0; |
| | | srand(222222); |
| | | net = parse_network_cfg("cfg/nist.cfg"); |
| | |
| | | float test_acc = network_accuracy(net, test); |
| | | printf("%d: Loss: %f, Test Acc: %f, Time: %lf seconds, LR: %f, Momentum: %f, Decay: %f\n", count, loss, test_acc,(float)(end-start)/CLOCKS_PER_SEC, net.learning_rate, net.momentum, net.decay); |
| | | } |
| | | #endif |
| | | } |
| | | |
| | | |
| | |
| | | } |
| | | if(0==strcmp(argv[1], "train")) train_imagenet(); |
| | | else if(0==strcmp(argv[1], "train_small")) train_imagenet_small(); |
| | | else if(0==strcmp(argv[1], "test_correct")) test_gpu_net(); |
| | | else if(0==strcmp(argv[1], "test")) test_imagenet(); |
| | | else if(0==strcmp(argv[1], "visualize")) test_visualize(); |
| | | #ifdef GPU |
| | | else if(0==strcmp(argv[1], "test_gpu")) test_gpu_blas(); |
| | | else if(0==strcmp(argv[1], "test")) test_gpu_net(); |
| | | //test_gpu_blas(); |
| | | //train_imagenet_small(); |
| | | //test_imagenet(); |
| | | //train_nist(); |
| | | //test_visualize(); |
| | | #endif |
| | | fprintf(stderr, "Success!\n"); |
| | | return 0; |
| | | } |