from keras.utils import np_utils

# Transofrm them to a float32 type
x_train = x_train.astype('float32')
x_test = x_test.astype('float32')

# Normalize the input
x_train /= 255
x_test /= 255

# One-hot Encoding
num_classes = 10
y_train = np_utils.to_categorical(y_train, num_classes)
y_test = np_utils.to_categorical(y_test, num_classes)