test: restore now-supported gradient checks - #149
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Co-Authored-By: Chris Rackauckas <accounts@chrisrackauckas.com>
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Closing this draft: removing the existing broken assertions is not an acceptable DowngradeCI fix. The regular test failures are real and require a behavioral or dependency fix. |
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Raise the minimum
OptimizationOptimJLtest dependency to the first release that provides the currentSciMLBase.ReturnCodeAPI, and remove two stale@test_brokenmarkers that make the minimum-version DowngradeCI job fail on unexpected passes.DowngradeCI now passes for the Core group:
https://github.com/SciML/ModelingToolkitNeuralNets.jl/actions/runs/32034141728/job/95400498217
The regular test matrix currently fails the same two gradient assertions after they are re-enabled, on both the latest and LTS Julia jobs. For example:
Those failures are reported explicitly rather than being hidden with a new skip or broken marker. The PR therefore establishes the correct downgrade behavior while leaving the current-stack numerical gradient issue visible for review.
No public API changes and no deprecation path is required.
Please ignore this PR until it has been reviewed by @ChrisRackauckas.