I am trying to switch my model from tensorflow-keras to pytorch but I faced a problem. I have “tf.keras.layers.experimental.preprocessing.Normalization” in my model as a layer, so the model will save the mean and std as model parameters. Therefore, when it comes to testing, I can use these data to normalize my test_set. I do that because I want my trained model be usable with different users who don’t have access to the whole training data. How can I do the same thing in Pytorch?