How to optimize neural network parameters with non-gradient algorithms?

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Is there any simple example code for optimizing neural network (e.g. from Flux.jl) parameters using non-gradient algorithms such as simulated annealing and genetic algorithms?

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Here’s an unconventional one

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If you use Lux with Optimization.jl

then just change to a gradient-free algorithm, like the ones in

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