Casting issue torch.nn.Parameter

[JHnvidia]

Not sure if this should be solved here, in cholespy, or nanobind. The from_differential function throws an error if the second argument is a torch.nn.Parameter rather than a tensor. Parameter is directly derived from Tensor, so there's no reason the cast should fail.

TypeError: solve(): incompatible function arguments. The following argument types are supported:
    1. solve(self, b: tensor[dtype=float32, order='C'], x: tensor[dtype=float32, order='C']) -> None

Invoked with types: CholeskySolverF, Parameter, Tensor

It's quite hard to workaround this "from the outside". E.g. doing from_differential(M, x.data) doesn't work because the gradient will be written to x.data.grad whereas the optimizer expects x.grad.