Assuming  size of predictions are
bs *  classes   in case multilabel multiclass classifier.
How does  nn.BCEWithLogits performs the mean in this  case…
is it simply  divide by numel ?
What about the case when we give weights to bce with logits function … would it
Sum weighted rows / size of batch  or it would does it like case one /numel
If in case ml m class classificaion  numel could diminish loss  in case there are more number of classes, so doing weighted sum/bs should be more optimal…
Please let me know how bce does a mean in case of mult label mult class