use case:
i want to cluster the encoded data into n clusters while its training so loss1 is the reconstruction error and loss 2 is euclidean distance between the centroids and encoded data.
i want to minimize both the losses so I can improve clustering efficiency.
so I did loss1+loss2    and loss.backward()