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## main #31 +/- ##
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+ Coverage 85.09% 85.16% +0.07%
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Files 6 6
Lines 711 708 -3
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- Hits 605 603 -2
+ Misses 106 105 -1 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
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sshin23
approved these changes
Apr 7, 2026
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This appears to make very little difference for performance and allocations/memory. Using the quadrotor example from our benchmarks with 1000 time points, I get the following with the current release: using NLPModelsIpopt, InfiniteOpt, InfiniteExaModels
m = quad(num_supports = 1000, backend = ExaTranscriptionBackend(IpoptSolver))
set_silent(m)
@time build_transcription_backend!(m) # builds the ExaModel
@time optimize!(m)0.168895 seconds (450.06 k allocations: 24.030 MiB)
0.865922 seconds (310 allocations: 2.626 MiB)With this PR, I get: 0.174419 seconds (449.24 k allocations: 24.468 MiB)
0.856932 seconds (310 allocations: 2.629 MiB) |
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This tests out the ExaModels changes proposed in exanauts/ExaModels.jl#256.