Applicability of UPGrad in Parallel Multi-Model Setup with Shared Auxiliary Loss

[ayitime]

Hi, thank you for your great work!

I have a slightly unconventional network setup and would like to ask whether UPGrad would be applicable in this case.

Specifically, I have two parallel models, model1 and model2, each processing its own dataset independently and producing predictions p1 and p2. The respective losses L1 and L2 are computed separately. Additionally, I compute a third loss L3 based on both p1 and p2.

Currently, I update model1 using the combined loss L1 + L3, and model2 using L2 + L3. However, I am unsure how to appropriately balance the weights between L1 and L3, and between L2 and L3.

Would it be feasible to apply UPGrad in this setup to adaptively balance these losses?

Looking forward to your insights — thank you in advance!