# normalize data
x_train = x_train.astype('float32') / 255.
x_val = x_val.astype('float32') / 255.
x_test = x_test.astype('float32') / 255.

# convert labels to one-hot vectors
y_train = keras.utils.to_categorical(y_train, num_classes)
y_val = keras.utils.to_categorical(y_val, num_classes)
y_test = keras.utils.to_categorical(y_test, num_classes)
print(y_test.shape)