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A comment on Trade-Offs in Automatic Differentiation: TensorFlow, PyTorch, Jax, and Julia. Parent comment

Re:Trade-Offs in Automatic Differentiation: TensorFlow, PyTo... by fault1 on Saturday December 25, 2021 @05:51PM (#29687774)
yes, see: https://juliadiff.org/ChainRulesCore.jl/dev/maths/nondiff_po...

and related neat usages in set based optimization methods in MathOptInterface (part of JuMP.jl): https://matbesancon.xyz/post/2020-12-24-chains_sets2/

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Re:Trade-Offs in Automatic Differentiation: TensorFlow, PyTo... by ogogmad on Sunday December 26, 2021 @07:26AM (#29691877)
To me, it looks like you're computing a single element from the set, instead of the whole set. Which makes sense, but it's an important caveat.
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