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fix: use SII instead of explicitly accessing SciMLFunction.syms #626

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merged 1 commit into from
Dec 14, 2023
Merged

fix: use SII instead of explicitly accessing SciMLFunction.syms #626

merged 1 commit into from
Dec 14, 2023

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AayushSabharwal
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Vaibhavdixit02
Vaibhavdixit02 reviewed Nov 15, 2023
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Project.toml
@@ -51,6 +52,7 @@ ProgressLogging = "0.1"
Reexport = "0.2, 1.0"
Requires = "1.0"
SciMLBase = "1.79.0, 2"
SymbolicIndexingInterface = "0.3"
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This seems to not get resolved

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@AayushSabharwal AayushSabharwal Nov 16, 2023 •
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It's not released yet
SciML/SymbolicIndexingInterface.jl#12

The changes here are due to SciML/SciMLBase.jl#532

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codecov bot commented Dec 13, 2023 •
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Codecov Report

All modified and coverable lines are covered by tests ✅

Comparison is base (8d53748) 0.11% compared to head (50e1e9e) 0.00%.
Report is 2 commits behind head on master.

Additional details and impacted files 
@@            Coverage Diff            @@
##           master    #626      +/-   ##
=========================================
- Coverage    0.11%   0.00%   -0.12%     
=========================================
  Files          40      12      -28     
  Lines        2689    1141    -1548     
=========================================
- Hits            3       0       -3     
+ Misses       2686    1141    -1545

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

@ChrisRackauckas
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Did this work locally with the other pieces checked out?

@AayushSabharwal
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AayushSabharwal commented Dec 13, 2023 •
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I haven't tested it yet. There are more libraries that need a bump, but it looks like for some reason it can't pull in 0.14 Flux during tests which caps CUDA at 4, whereas LinearSolve needs 5.

EDIT: it seems test/Project.toml caps Flux at 0.13. My guess is that before this change, Optimization could pull in an older version of LinearSolve compatible with CUDA 4. Now it needs the latest LinearSolve, but can't pull in latest Flux.

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ERROR: LoadError: Unsatisfiable requirements detected for package SparseArrays [2f01184e]:
 SparseArrays [2f01184e] log:
 ├─possible versions are: 0.0.0 or uninstalled (package in sysimage!)
 ├─restricted to versions 1.9.0-1 by OrdinaryDiffEq [1dea7af3] — no versions left
 │ └─OrdinaryDiffEq [1dea7af3] log:
 │   ├─possible versions are: 6.61.0 or uninstalled
 │   ├─restricted to versions 6.19.1-6 by SciMLSensitivity [1ed8b502], leaving only versions: 6.61.0
 │   │ └─SciMLSensitivity [1ed8b502] log:
 │   │   ├─possible versions are: 7.47.0 or uninstalled
 │   │   └─SciMLSensitivity [1ed8b502] is fixed to version 7.47.0
 │   └─OrdinaryDiffEq [1dea7af3] is fixed to version 6.61.0
 └─SparseArrays [2f01184e] is fixed to version 0.0.0

I don't even know what to make of this

@AayushSabharwal
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This passes if Flux compat is bumped and 1.10 is used

ChrisRackauckas
ChrisRackauckas reviewed Dec 14, 2023
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Project.toml
@@ -61,6 +62,7 @@ ReverseDiff = "1"
SciMLBase = "1.79.0, 2"
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Doesn't this need to be bumped?

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Why would it? Nothing in Optimization changed that prevents it from being compatible with previous versions of SciMLBase.

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oh I thought the RAT v3 or SII v0.3 changes would require it, but if that back compatibility is kept then we're good.

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Merging to unblock others.

@ChrisRackauckas ChrisRackauckas merged commit 5c01e51 into SciML:master Dec 14, 2023
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@ChrisRackauckas ChrisRackauckas mentioned this pull request Dec 14, 2023
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ChrisRackauckas
ChrisRackauckas reviewed Dec 14, 2023
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lib/OptimizationMOI/src/nlp.jl
@@ -85,7 +85,7 @@ function SciMLBase.get_syms(sol::SciMLBase.OptimizationSolution{
C <:
MOIOptimizationNLPCache,
}
sol.cache.evaluator.f.syms
variable_symbols(sol.cache.evaluator.f)
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Doesn't OptimizationMOI need its Project.toml updated?

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Bump on this.

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Ah, I didn't realize. Thanks. I'll push these changes to the rerun CI PR

@Vaibhavdixit02
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I think this broke CI https://github.com/SciML/Optimization.jl/actions/runs/7209658584/job/19641063898?

@AayushSabharwal
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AayushSabharwal commented Dec 15, 2023 •
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Yeah it won't pass until MTK is tagged. I ran it locally and tests pass.

@sunxd3 sunxd3 mentioned this pull request Dec 18, 2023
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@AayushSabharwal @ChrisRackauckas @Vaibhavdixit02