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🤖 Format .jl files (#43)
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Co-authored-by: paraynaud <[email protected]>
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github-actions[bot] and paraynaud authored Dec 29, 2024
1 parent 2095df9 commit 77933f3
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Showing 2 changed files with 21 additions and 21 deletions.
36 changes: 18 additions & 18 deletions .breakage/get_jso_users.jl
Original file line number Diff line number Diff line change
@@ -1,18 +1,18 @@
import GitHub, PkgDeps # both export users()

length(ARGS) >= 1 || error("specify at least one JSO package as argument")

jso_repos, _ = GitHub.repos("JuliaSmoothOptimizers")
jso_names = [splitext(x.name)[1] for x jso_repos]

name = splitext(ARGS[1])[1]
name jso_names || error("argument should be one of ", jso_names)

dependents = String[]
try
global dependents = filter(x -> x jso_names, PkgDeps.users(name))
catch e
# package not registered; don't insert into dependents
end

println(dependents)
import GitHub, PkgDeps # both export users()

length(ARGS) >= 1 || error("specify at least one JSO package as argument")

jso_repos, _ = GitHub.repos("JuliaSmoothOptimizers")
jso_names = [splitext(x.name)[1] for x jso_repos]

name = splitext(ARGS[1])[1]
name jso_names || error("argument should be one of ", jso_names)

dependents = String[]
try
global dependents = filter(x -> x jso_names, PkgDeps.users(name))
catch e
# package not registered; don't insert into dependents
end

println(dependents)
6 changes: 3 additions & 3 deletions benchmark/benchmarks.jl
Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
using LinearAlgebra, StatsBase
using BenchmarkTools
using Krylov, LinearOperators
using Krylov, LinearOperators
using PartitionedStructures
using PartitionedVectors

Expand Down Expand Up @@ -31,12 +31,12 @@ res = similar(pv_x)

Krylov.solve!(solver, lo_epm, -pv_gradient)
SUITE["Krylov small PartitionedVectors"] = BenchmarkGroup()
SUITE["Krylov small PartitionedVectors"] = @benchmarkable Krylov.solve!(solver, lo_epm, -pv_gradient)
SUITE["Krylov small PartitionedVectors"] =
@benchmarkable Krylov.solve!(solver, lo_epm, -pv_gradient)

SUITE["small broadcast"] = BenchmarkGroup()
SUITE["small broadcast"] = @benchmarkable res .= pv_gradient .+ 3 .* pv_gradient


N = 1500
n = 20000
nie = 15
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