It is important to note that the AdaIN layer proposed by the authors uses no other parameters apart from mean and variance. The layer also does not have any trainable parameters. This is why we use a Python function instead of using a Keras layer. The function takes style and content feature maps, computes the mean and standard deviation of the images and returns the adaptive instance normalized feature map.