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This pull request adds an optional callback to KernelSolve which allows a user to implement their own linear solver and still get gradients. This creates a nice way to extend KeOps with different solver implementations (e.g. which are specialized to a given kernel).

…nt a custom linear solver instead of the default conjugate gradient one while still getting derivatives.
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