afef503d34919fb2febc0b475085f140e1a4e977,ann_architectures/cifar10/alexnet.py,,,#,24

Before Change

print("Test accuracy:", score[1])

filename = "{:2.2f}".format(score[1] * 100)
open(filename + ".json", "w").write(model.to_json())
model.save_weights(filename + ".h5", overwrite=True)

After Change

// Whether to apply global contrast normalization and ZCA whitening
gcn = True
zca = True

traingen = ImageDataGenerator(rescale=1./255, featurewise_center=gcn,
                              featurewise_std_normalization=gcn,
                              zca_whitening=zca, horizontal_flip=True,
                              rotation_range=10, width_shift_range=0.1,
                              height_shift_range=0.1)

// Compute quantities required for featurewise normalization
// (std, mean, and principal components if ZCA whitening is applied)
traingen.fit(X_train/255.)

trainflow = traingen.flow(X_train, Y_train, batch_size=batch_size)

testgen = ImageDataGenerator(rescale=1./255, featurewise_center=gcn,

Instances