But then I need to train every element of data few times (as much as number of samples). I mean for every label e.g. 1 I will make distribution built of 100 elements, so also I need to pass labeled data 100 times for every step of iteration, so for example if I work on pictures datasets - every single picture will be processed 100 times with random label. Am I right?