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11
src/cnn.c
11
src/cnn.c
@ -151,10 +151,10 @@ void train_imagenet(char *cfgfile)
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//network net = parse_network_cfg("/home/pjreddie/imagenet_backup/alexnet_1270.cfg");
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srand(time(0));
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network net = parse_network_cfg(cfgfile);
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set_learning_network(&net, .000001, .9, .0005);
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set_learning_network(&net, net.learning_rate, .5, .0005);
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printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
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int imgs = 1024;
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int i = 20590;
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int i = 23030;
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char **labels = get_labels("/home/pjreddie/data/imagenet/cls.labels.list");
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list *plist = get_paths("/data/imagenet/cls.train.list");
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char **paths = (char **)list_to_array(plist);
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@ -177,7 +177,7 @@ void train_imagenet(char *cfgfile)
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avg_loss = avg_loss*.9 + loss*.1;
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printf("%d: %f, %f avg, %lf seconds, %d images\n", i, loss, avg_loss, sec(clock()-time), i*imgs);
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free_data(train);
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if(i%10==0){
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if(i%100==0){
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char buff[256];
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sprintf(buff, "/home/pjreddie/imagenet_backup/net_%d.cfg", i);
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save_network(net, buff);
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@ -370,14 +370,14 @@ void test_nist(char *path)
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void train_nist()
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{
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srand(222222);
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network net = parse_network_cfg("cfg/nist.cfg");
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network net = parse_network_cfg("cfg/nist.cfg.old");
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data train = load_categorical_data_csv("data/mnist/mnist_train.csv", 0, 10);
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data test = load_categorical_data_csv("data/mnist/mnist_test.csv",0,10);
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normalize_data_rows(train);
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normalize_data_rows(test);
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int count = 0;
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int iters = 60000/net.batch + 1;
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while(++count <= 2000){
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while(++count <= 200){
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clock_t start = clock(), end;
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float loss = train_network_sgd(net, train, iters);
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end = clock();
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@ -385,6 +385,7 @@ void train_nist()
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if(count%1 == 0) test_acc = network_accuracy(net, test);
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printf("%d: Loss: %f, Test Acc: %f, Time: %lf seconds\n", count, loss, test_acc,(float)(end-start)/CLOCKS_PER_SEC);
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}
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save_network(net, "~/nist_conv.cfg");
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}
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void train_nist_distributed(char *address)
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