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klamike merged 3 commits into from
Jul 24, 2025
Merged

Add coverage badge #10

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3affcb7
badge
klamike Jul 24, 2025
4aa2ca6
exclude kernels.jl
klamike Jul 24, 2025
229b8de
test empty intervals
klamike Jul 24, 2025
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5 changes: 3 additions & 2 deletions README.md
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Original file line number Diff line number Diff line change
@@ -1,7 +1,8 @@
# BatchNLPKernels.jl

[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://LearningToOptimize.github.io/BatchNLPKernels.jl/dev/)
[![Build Status](https://github.com/LearningToOptimize/BatchNLPKernels.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/LearningToOptimize/BatchNLPKernels.jl/actions/workflows/CI.yml?query=branch%3Amain)
[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://klamike.github.io/BatchNLPKernels.jl/dev/)
[![Build Status](https://github.com/klamike/BatchNLPKernels.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/klamike/BatchNLPKernels.jl/actions/workflows/CI.yml?query=branch%3Amain)
[![Coverage](https://codecov.io/gh/LearningToOptimize/BatchNLPKernels.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/LearningToOptimize/BatchNLPKernels.jl)

`BatchNLPKernels.jl` provides [`KernelAbstractions.jl`](https://github.com/JuliaGPU/KernelAbstractions.jl) kernels for evaluating problem data from a (parametric) [`ExaModel`](https://github.com/exanauts/ExaModels.jl) for batches of solutions (and parameters). Currently the following functions (as well as their non-parametric variants) are exported:

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1 change: 0 additions & 1 deletion src/interval.jl
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Expand Up @@ -15,7 +15,6 @@ Base.broadcastable(s::Interval) = Ref(s)
Base.isempty(s::Interval{VT}) where {VT} = isempty(s.l) || isempty(s.u)

# empty support (unconstrained)
Interval(::Nothing) = Interval()
Interval() = Interval(nothing, nothing)
Base.isempty(::Interval{Nothing}) = true
@inline _violation(v, ::Interval{Nothing}) = zero(v)
6 changes: 5 additions & 1 deletion src/kernels.jl
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@@ -1,3 +1,5 @@
## COV_EXCL_START

@kernel function kerf_batch(Y, @Const(f), @Const(itr), @Const(X), @Const(Θ))
I, batch_idx = @index(Global, NTuple)
@inbounds Y[ExaModels.offset0(f, itr, I), batch_idx] = f.f(itr[I], view(X, :, batch_idx), view(Θ, :, batch_idx))
Expand Down Expand Up @@ -102,4 +104,6 @@ end
Y[j, batch_idx] += V[ind, batch_idx] * X[i, batch_idx]
end
end
end
end

## COV_EXCL_STOP
7 changes: 7 additions & 0 deletions test/runtests.jl
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Expand Up @@ -38,6 +38,13 @@ if haskey(ENV, "BNK_TEST_CUDA")
@info "CUDA detected"
end

@testset "Empty Intervals" begin
empt = BNK.Interval()
@test isempty(empt)
@test isnothing(empt.l)
@test isnothing(empt.u)
@test BNK._violation([1.0, 2.0, 3.0], empt) == [0.0, 0.0, 0.0]
end

include("luksan.jl")
include("power.jl")
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