"[D]" Doubt with Loss function

I have a multi-class problem where the label vector can be like \[ 0, 1, 0, 0, 1\] , as in multiple classes can be true at the same time. What kind of loss function should i used, as in pytorch Crossentropy you can only pass only 1 correct column as target.

First thing that came into my mind was convert the target vector in a probability distribution like \[0, 0.5, 0, 0, 0.5\] and apply KLDivergence Loss. Will this …

class column function kind loss machinelearning multiple pytorch true vector