36 lines
982 B
Matlab
36 lines
982 B
Matlab
%function test_example_CNN
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load mnist_uint8;
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train_x = double(reshape(train_x',28,28,60000))/255;
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test_x = double(reshape(test_x',28,28,10000))/255;
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train_y = double(train_y');
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test_y = double(test_y');
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%% ex1 Train a 6c-2s-12c-2s Convolutional neural network
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%will run 1 epoch in about 200 second and get around 11% error.
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%With 100 epochs you'll get around 1.2% error
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rand('state',0)
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cnn.layers = {
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struct('type', 'i') %input layer
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struct('type', 'c', 'outputmaps', 6, 'kernelsize', 5) %convolution layer
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struct('type', 's', 'scale', 2) %sub sampling layer
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struct('type', 'c', 'outputmaps', 12, 'kernelsize', 5) %convolution layer
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struct('type', 's', 'scale', 2) %subsampling layer
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};
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opts.alpha = 1;
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opts.batchsize = 50;
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opts.numepochs = 5;
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cnn = cnnsetup(cnn, train_x, train_y);
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cnn = cnntrain(cnn, train_x, train_y, opts);
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[er, bad] = cnntest(cnn, test_x, test_y);
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%plot mean squared error
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figure; plot(cnn.rL);
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assert(er<0.12, 'Too big error');
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