Hello,

I was wondering whether the graph that gets constructed for backpropagation can update loss/gradients that have been computed independently from multiple runs of the same network model.

For example, assuming we have a vgg architecture, and we run multiple images through the model, applying a different loss on each output, would pytorch calculate the updates properly (such that the network is guided by all losses, not just the most recent one overwriting the gradients)?