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remove Pkg.add from Benchmark (#711)
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* remove Pkg.add from Benchmark

* update

* use median

* disable retune

* increase time tolerance

* robustify

* try forcing tuning

* only run benchmark ci manually
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palday committed Mar 5, 2024
1 parent ff82b8f commit cfd3023
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21 changes: 11 additions & 10 deletions .github/workflows/benchmark.yml
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Expand Up @@ -3,16 +3,17 @@ concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
on:
pull_request:
branches:
- main
paths-ignore:
- 'LICENSE.md'
- 'README.md'
- 'docs/**'
- 'issues/**'
- 'format/**'
- 'test/**'
workflow_dispatch:
# pull_request:
# branches:
# - main
# paths-ignore:
# - 'LICENSE.md'
# - 'README.md'
# - 'docs/**'
# - 'issues/**'
# - 'format/**'
# - 'test/**'
jobs:
benchmarks:
runs-on: ubuntu-latest
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2 changes: 1 addition & 1 deletion benchmark/Project.toml
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Expand Up @@ -2,7 +2,7 @@
BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
MixedModels = "ff71e718-51f3-5ec2-a782-8ffcbfa3c316"
PkgBenchmark = "32113eaa-f34f-5b0d-bd6c-c81e245fc73d"
StatsModels = "3eaba693-59b7-5ba5-a881-562e759f1c8d"
Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"

[compat]
BenchmarkTools = "1"
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4 changes: 2 additions & 2 deletions benchmark/benchmarks.jl
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@@ -1,4 +1,4 @@
using BenchmarkTools, MixedModels, StatsModels
using BenchmarkTools, MixedModels
using MixedModels: dataset

const SUITE = BenchmarkGroup()
Expand Down Expand Up @@ -85,7 +85,7 @@ function fitbobyqa(dsnm::Symbol, i::Integer)
return fit(MixedModel, fms[dsnm][i], dataset(dsnm); contrasts, progress=false)
end

# these tests are so fast that they can be very noisy because the denominator is so small,
# these tests are so fast that they can be very noisy because the denominator is so small,
# so we disable them by default for auto-benchmarking
# SUITE["simplescalar"] = BenchmarkGroup(["single", "simple", "scalar"])
# for (ds, i) in [
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9 changes: 5 additions & 4 deletions benchmark/run.jl
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@@ -1,9 +1,10 @@
using Pkg
Pkg.develop(PackageSpec(path=dirname(@__DIR__)))
Pkg.instantiate()
using PkgBenchmark, MixedModels
# explicit `Pkg.add` is a crutch until we've got a good base on main
using PkgBenchmark, MixedModels, Statistics
# Pkg.update() allows us to benchmark even when dependencies/compat requirements change
juliacmd = `$(Base.julia_cmd()) -O3 -e "using Pkg; Pkg.update(); Pkg.add([\"BenchmarkTools\", \"StatsModels\"])"`
juliacmd = `$(Base.julia_cmd()) -O3 -e "using Pkg; Pkg.update()"`
config = BenchmarkConfig(; id="origin/HEAD", juliacmd)
export_markdown("benchmark.md", judge(MixedModels, config; verbose=true))
# for many of the smaller models, we get a lot of noise at the default 5% tolerance
# TODO: specify a tune.json with per model time tolerances
export_markdown("benchmark.md", judge(MixedModels, config; verbose=true, retune=false, f=median, judgekwargs=(;time_tolerance=0.1, memory_tolerance=0.05)))
1 change: 1 addition & 0 deletions benchmark/tune.json
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@@ -0,0 +1 @@
[{"Julia":"1.9.2","BenchmarkTools":"1.0.0"},[["BenchmarkGroup",{"data":{"singlevector":["BenchmarkGroup",{"data":{"sleepstudy:3":["Parameters",{"gctrial":true,"time_tolerance":0.05,"samples":10000,"evals":1,"gcsample":false,"seconds":5.0,"overhead":0.0,"memory_tolerance":0.01}],"sleepstudy:2":["Parameters",{"gctrial":true,"time_tolerance":0.05,"samples":10000,"evals":1,"gcsample":false,"seconds":5.0,"overhead":0.0,"memory_tolerance":0.01}],"sleepstudy:4":["Parameters",{"gctrial":true,"time_tolerance":0.05,"samples":10000,"evals":1,"gcsample":false,"seconds":5.0,"overhead":0.0,"memory_tolerance":0.01}]},"tags":["single","vector"]}],"crossed":["BenchmarkGroup",{"data":{"kb07:1":["Parameters",{"gctrial":true,"time_tolerance":0.05,"samples":10000,"evals":1,"gcsample":false,"seconds":5.0,"overhead":0.0,"memory_tolerance":0.01}],"ml1m:1":["Parameters",{"gctrial":true,"time_tolerance":0.05,"samples":10000,"evals":1,"gcsample":false,"seconds":5.0,"overhead":0.0,"memory_tolerance":0.01}],"insteval:1":["Parameters",{"gctrial":true,"time_tolerance":0.05,"samples":10000,"evals":1,"gcsample":false,"seconds":5.0,"overhead":0.0,"memory_tolerance":0.01}],"insteval:2":["Parameters",{"gctrial":true,"time_tolerance":0.05,"samples":10000,"evals":1,"gcsample":false,"seconds":5.0,"overhead":0.0,"memory_tolerance":0.01}],"machines:1":["Parameters",{"gctrial":true,"time_tolerance":0.05,"samples":10000,"evals":1,"gcsample":false,"seconds":5.0,"overhead":0.0,"memory_tolerance":0.01}],"mrk17_exp1:1":["Parameters",{"gctrial":true,"time_tolerance":0.05,"samples":10000,"evals":1,"gcsample":false,"seconds":5.0,"overhead":0.0,"memory_tolerance":0.01}],"penicillin:1":["Parameters",{"gctrial":true,"time_tolerance":0.05,"samples":10000,"evals":1,"gcsample":false,"seconds":5.0,"overhead":0.0,"memory_tolerance":0.01}]},"tags":["multiple","crossed","scalar"]}],"crossedvector":["BenchmarkGroup",{"data":{"kb07:2":["Parameters",{"gctrial":true,"time_tolerance":0.05,"samples":10000,"evals":1,"gcsample":false,"seconds":5.0,"overhead":0.0,"memory_tolerance":0.01}],"d3:1":["Parameters",{"gctrial":true,"time_tolerance":0.05,"samples":10000,"evals":1,"gcsample":false,"seconds":5.0,"overhead":0.0,"memory_tolerance":0.01}],"kb07:3":["Parameters",{"gctrial":true,"time_tolerance":0.05,"samples":10000,"evals":1,"gcsample":false,"seconds":5.0,"overhead":0.0,"memory_tolerance":0.01}],"mrk17_exp1:2":["Parameters",{"gctrial":true,"time_tolerance":0.05,"samples":10000,"evals":1,"gcsample":false,"seconds":5.0,"overhead":0.0,"memory_tolerance":0.01}]},"tags":["multiple","crossed","vector"]}],"nested":["BenchmarkGroup",{"data":{"pastes:2":["Parameters",{"gctrial":true,"time_tolerance":0.05,"samples":10000,"evals":1,"gcsample":false,"seconds":5.0,"overhead":0.0,"memory_tolerance":0.01}]},"tags":["multiple","nested","scalar"]}]},"tags":[]}]]]

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