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1 | | -using BenchmarkTools, ADNLPModels |
| 1 | +using BenchmarkTools, ADNLPModels, NLPModels |
2 | 2 | using OptimizationProblems |
3 | 3 | using TimerNLPModels |
4 | 4 |
|
5 | 5 | # Run locally with `tune!(SUITE)` and then `run(SUITE)` |
6 | 6 | const SUITE = BenchmarkGroup() |
7 | 7 |
|
8 | 8 | for n in [100, 1000] |
9 | | - g = zeros(n) |
10 | | - SUITE["grad! ref"]["$n"] = @benchmarkable grad!(nlp, get_x0(nlp), $g) setup = (nlp = OptimizationProblems.ADNLPProblems.arglina(n = $n)) |
11 | | - SUITE["grad! tim"]["$n"] = @benchmarkable grad!(timed_nlp, get_x0(timed_nlp), $g) setup = (timed_nlp = TimerNLPModel(OptimizationProblems.ADNLPProblems.arglina(n = $n))) |
| 9 | + g = zeros(n) |
| 10 | + SUITE["grad! ref"]["$n"] = @benchmarkable grad!(nlp, get_x0(nlp), $g) setup = |
| 11 | + (nlp = OptimizationProblems.ADNLPProblems.arglina(n = $n)) |
| 12 | + SUITE["grad! tim"]["$n"] = @benchmarkable grad!(timed_nlp, get_x0(timed_nlp), $g) setup = |
| 13 | + (timed_nlp = TimerNLPModel(OptimizationProblems.ADNLPProblems.arglina(n = $n))) |
12 | 14 | end |
13 | 15 | for n in [100, 1000] |
14 | | - Hv = zeros(n) |
15 | | - SUITE["hprod! ref"]["$n"] = @benchmarkable hprod!(nlp, get_x0(nlp), get_x0(nlp), $Hv) setup = (nlp = OptimizationProblems.ADNLPProblems.arglina(n = $n)) |
16 | | - SUITE["hprod! tim"]["$n"] = @benchmarkable hprod!(timed_nlp, get_x0(timed_nlp), get_x0(timed_nlp), $Hv) setup = (timed_nlp = TimerNLPModel(OptimizationProblems.ADNLPProblems.arglina(n = $n))) |
| 16 | + Hv = zeros(n) |
| 17 | + SUITE["hprod! ref"]["$n"] = @benchmarkable hprod!(nlp, get_x0(nlp), get_x0(nlp), $Hv) setup = |
| 18 | + (nlp = OptimizationProblems.ADNLPProblems.arglina(n = $n)) |
| 19 | + SUITE["hprod! tim"]["$n"] = |
| 20 | + @benchmarkable hprod!(timed_nlp, get_x0(timed_nlp), get_x0(timed_nlp), $Hv) setup = |
| 21 | + (timed_nlp = TimerNLPModel(OptimizationProblems.ADNLPProblems.arglina(n = $n))) |
17 | 22 | end |
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