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computed. These values are plugged into the loss function and the PINN is trained. The following code snippet illustrates the auto-differentiation and loss formulation in “Pytorch”. def u(t, x): u = neural_net(torch.concat([t, x])) return u def f(t, x): u = u(t, x) u_t = torch.autograd.grad(u, t,