Did Modulus.sym support the PINN+DeepONet （only physics-informed）？

Physics Simulation PhysicsNeMo-ML Model Framework Technical Support (PhysicsNeMo Only)
1

I am trying to use the Modulus library to solve a set of partial differential equations, specifically, a set of heat diffusion equations with varying heat source terms. This requires DeepONet, and the methods in the manual all rely on prepared training data, but I hope to introduce physical information as constraints (predicted temperature results are brought into the equation to calculate the loss) without using training data, because I need to obtain training data through the finite element method, which is time-consuming. So, is there an example of this method that is completely physically driven? Or has anyone else tried this? Can you give me some guidance, thank you!

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If you know the governing PDE, you may define it and use it as a constraint.