SciML / Optimization.jl

Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.
https://docs.sciml.ai/Optimization/stable/
MIT License
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downgrade CI #650

Closed ArnoStrouwen closed 6 months ago

ArnoStrouwen commented 6 months ago

This one is quite the Gordian knot to untie.

codecov[bot] commented 6 months ago

Codecov Report

All modified and coverable lines are covered by tests :white_check_mark:

Comparison is base (222a515) 8.37% compared to head (bd624b4) 8.46%.

Additional details and impacted files ```diff @@ Coverage Diff @@ ## master #650 +/- ## ========================================= + Coverage 8.37% 8.46% +0.08% ========================================= Files 30 30 Lines 2496 2470 -26 ========================================= Hits 209 209 + Misses 2287 2261 -26 ```

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ArnoStrouwen commented 6 months ago

The downgrade CI passes locally for me. Not sure what the issue is. https://github.com/SciML/Optimization.jl/actions/runs/7314646211/job/19927490678?pr=650#step:6:4177

ChrisRackauckas commented 6 months ago

Are you running the tests of the extension packages as well? It seems this is due to something missing in ReverseDiff when doing the Lux tests. Maybe @avik-pal knows.

ArnoStrouwen commented 6 months ago

The Lux error is a bad lower bound reversediff compat in Lux, but that extension should not be used here. I'll try adding the tests of the libs.

Vaibhavdixit02 commented 6 months ago

What's the goal here?

ArnoStrouwen commented 6 months ago

See https://julialang.slack.com/archives/CN04R7WKE/p1702296727671319

ArnoStrouwen commented 6 months ago

Seems like failures are stochastic.

ArnoStrouwen commented 6 months ago

This one looks good to go.

ChrisRackauckas commented 6 months ago

@Vaibhavdixit02 are you going to look into https://github.com/SciML/Optimization.jl/actions/runs/7315937069/job/19930076157?pr=650#step:7:856 ?