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This works, but it's not ready to merge because a decision needs to be made RE. See my comment in #611.

@ajwheeler ajwheeler changed the title make it work it ForwardDiff v1 make it work with ForwardDiff v1 Apr 11, 2025
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codecov bot commented Apr 11, 2025

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 87.74%. Comparing base (fab0496) to head (90f7e09).
Report is 12 commits behind head on master.

Additional details and impacted files
@@            Coverage Diff             @@
##           master     #614      +/-   ##
==========================================
+ Coverage   87.07%   87.74%   +0.66%     
==========================================
  Files          28       28              
  Lines        1888     1811      -77     
==========================================
- Hits         1644     1589      -55     
+ Misses        244      222      -22     

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@ajwheeler ajwheeler marked this pull request as ready for review April 15, 2025 20:28
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It turns out that it's possible to keep the julia lower bound at 1.6. There are, however, failing tests for 1.6 than for 1.11, so it may still be worth bumping the compatibility requirement. It's just not required to fix compatibility with forward diff.

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The main thing I need to clarify here is the dependency on ForwardDiff. It seems to be both a regular (strong?) dependency and a weak dependency. If this is about compatibility with 1.6, I would prefer to drop 1.6 support in favor of 1.9 with extensions.

I would normally prefer formatting changes to be made in independent pull requests, but I think the amount of such changes in tolerable at the moment.

Project.toml Outdated
Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
AxisAlgorithms = "13072b0f-2c55-5437-9ae7-d433b7a33950"
ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
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Why is ForwardDiff both a strong dep and a weak dep?

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This was in error. Fixed, and restricted Julia version to >= 1.9.

A2 = rand(Float64, nx, nx) * 100

# random array and vector to store gradient
A2 = rand(Float64, 3, 3) * 100
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Why is this hard coded at 3 now?

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Just to make the test less noisy if it fails. There's no particular reason that it had to be nx and I don't there there are any conditions that are hit with 10 points that aren't with 3. That said, I'm happy to change back. It is not an important change.

@mkitti mkitti merged commit 9684d74 into JuliaMath:master Apr 21, 2025
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2 participants