docs: use more of Lux official API for training and inference #438
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avik-pal
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Aug 29, 2025
| k = SqExponentialKernel() ∘ FunctionTransform(x -> neural_transform(x, ps)) | ||
| fx = AbstractGPs.FiniteGP(GP(k), x_train, noise_std^2) | ||
| _, loss_val, _, tstate = Training.single_train_step!( | ||
| AutoZygote(), update_kernel_and_loss, (), tstate |
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Wanted to keep changes as minimal as possible but this can also be switched to Mooncake
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Thanks @avik-pal! |
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Aug 29, 2025
* Initial plan * Replace Flux with Lux in deep kernel learning example Co-authored-by: yebai <[email protected]> * Improve Lux implementation with proper parameter handling Co-authored-by: yebai <[email protected]> * Apply suggestions from code review Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> * Fix Literate.jl parsing issue in deep kernel learning example Co-authored-by: yebai <[email protected]> * Clean up comments in script.jl * docs: use more of Lux official API for training and inference (#438) * Update examples/2-deep-kernel-learning/script.jl Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> --------- Co-authored-by: copilot-swe-agent[bot] <[email protected]> Co-authored-by: yebai <[email protected]> Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: Avik Pal <[email protected]>
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@yebai added some of my lux related changes here