My mentor wants me to do the image novelty detection by normal two classes classification.the positive dataset is around 800 and the negative dataset genereted by a classification inference result for 2 millions.So I want to do generate a dataset which is combined by all the 800 positive dataset and 800 sampled from negative dataset with heavy data augmentation every epoch . I know there is  randomsampler function in pytorch but it seems can’t sample only one class randomly.