Fix late-binding closure in RBF params_gradient#1
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JonasTurnwald merged 1 commit intoApr 14, 2026
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…cales The lambda in the loop captured the loop variable i by reference, so all lengthscale gradient functions ended up using the last index. Added i=i default arg to bind the value at each iteration. Also added a finite-difference test for params_gradient covering both 1D and 2D lengthscale cases.
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Summary
RadialBasisFunction.params_gradient()where the loop variableiwas captured by reference instead of by value. With multi-dimensional lengthscales, all gradient functions incorrectly computed the gradient for the last lengthscale dimension only.test_rbf_params_gradientwhich validates the analytical gradient against central finite differences for both 1D and 2D lengthscale cases.Details
The fix is a single
i=idefault argument addition on the lambda atkernels.py:167. Without it, Python's late-binding closures cause every lambda created in the loop to share the final value ofi, producing wrong gradients for all but the last lengthscale whenlog_likelihood_grad()is called on a kernel with multiple lengthscale dimensions.