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Hey, thanks again for the call. As discussed, it would be nice to compare the AD performance on Microsoft's ADBench Benchmark set. Here is a PyTorch implementation, since you mentioned that this might be best to get started from burn: https://github.com/microsoft/ADBench/blob/master/src/python/modules/PyTorch/gmm_objective.py Here is a Rust implementation: https://github.com/EnzymeAD/Enzyme/blob/64fd1d341bd171f3f54beacc92f81bd81f59a53d/enzyme/benchmarks/ReverseMode/gmm/src/lib.rs
If someone has the time to set up a burn version of any of gmm/ba/lstm/hand, then I would love to run some benchmarks against it. The main issue is probably that burn is more high-level so this benchmarks might be harder to model, while rust-enzyme isn't stable enough yet to test classical Neural Network implementations. So it might also might sense to postpone this for a while.