I have little confusion regarding timestamp and noise added at that time , as mentioned in lecture during trainig at each timestamp noise is added and model has to predict the noise but question is that lets say we have 5 images for training and 5 timestampts so for single epoch model will train on 25 images or simply different noise will be added for each image seperatly , means dataset size will remain same ?