| | |
| | | network net = parse_network_cfg("cfg/nist.cfg"); |
| | | 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); |
| | | translate_data_rows(train, -144); |
| | | translate_data_rows(test, -144); |
| | | normalize_data_rows(train); |
| | | normalize_data_rows(test); |
| | | int count = 0; |
| | | int iters = 50000/net.batch; |
| | | iters = 1000/net.batch + 1; |
| | | while(++count <= 2000){ |
| | | clock_t start = clock(), end; |
| | | float loss = train_network_sgd(net, train, iters); |
| | | float loss = train_network_sgd_gpu(net, train, iters); |
| | | end = clock(); |
| | | float test_acc = network_accuracy(net, test); |
| | | float test_acc = network_accuracy_gpu(net, test); |
| | | //float test_acc = 0; |
| | | printf("%d: Loss: %f, Test Acc: %f, Time: %lf seconds\n", count, loss, test_acc,(float)(end-start)/CLOCKS_PER_SEC); |
| | | } |
| | | } |
| | |
| | | else if(0==strcmp(argv[1], "test_correct")) test_correct_alexnet(); |
| | | else if(0==strcmp(argv[1], "test")) test_imagenet(); |
| | | else if(0==strcmp(argv[1], "server")) run_server(); |
| | | else if(0==strcmp(argv[1], "client")) train_imagenet_distributed(argv[2]); |
| | | else if(0==strcmp(argv[1], "detect")) test_detection(); |
| | | else if(0==strcmp(argv[1], "visualize")) test_visualize(argv[2]); |
| | | else if(0==strcmp(argv[1], "valid")) validate_imagenet(argv[2]); |
| | | #ifdef GPU |
| | | else if(0==strcmp(argv[1], "test_gpu")) test_gpu_blas(); |
| | | #endif |
| | | else if(argc < 3){ |
| | | fprintf(stderr, "usage: %s <function>\n", argv[0]); |
| | | return 0; |
| | | } |
| | | else if(0==strcmp(argv[1], "client")) train_imagenet_distributed(argv[2]); |
| | | else if(0==strcmp(argv[1], "visualize")) test_visualize(argv[2]); |
| | | else if(0==strcmp(argv[1], "valid")) validate_imagenet(argv[2]); |
| | | fprintf(stderr, "Success!\n"); |
| | | return 0; |
| | | } |