Compatibility with newer versions of NeuralPDE, Lux, ModelingToolkit #33
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Checklist
contributor guidelines, in particular the SciML Style Guide and
COLPRAC.
Additional context
To enable GPU support (in progress), we need to use a newer version of NeuralPDE (and, in turn, Lux and ModelingToolkit), which broke some tests. This fixes those.
Adds support for benchmarking with multiple optimization passes (e.g., two passes at different learning rates or an Adam pass followed by a BFGS pass).
Fixes broken
UnstructuredNeuralLyapunov
structure and addsstrength
keyword toAsymptoticStability
decrease condition (for use in periodic systems).Removes examples of
GridTraining
, since they're a bad choice in addition to being broken while I was working on this PR (now fixed SciML/NeuralPDE.jl#910).Replaces DifferentialEquations.jl dependency with OrdinaryDiffEq.jl.