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Merge pull request #488 from ReactiveBayes/remove-lv
remove lv from the package
2 parents b9137f6 + 21623e0 commit 98c0191

4 files changed

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.github/workflows/ci.yml

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@@ -32,6 +32,7 @@ jobs:
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version:
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- '1.10'
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- '1.11'
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- '1.12'
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os:
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- ubuntu-latest
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arch:
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- uses: actions/checkout@v4
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- uses: julia-actions/setup-julia@v2
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with:
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include-all-prereleases: true
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version: ${{ matrix.version }}
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arch: ${{ matrix.arch }}
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- uses: julia-actions/cache@v2
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- uses: julia-actions/julia-buildpkg@v1
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- uses: julia-actions/julia-runtest@v1
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steps:
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- uses: actions/checkout@v4
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- uses: julia-actions/setup-julia@v2
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with:
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version: '1'
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- uses: julia-actions/cache@v2
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- uses: julia-actions/julia-buildpkg@v1
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- run: make docs

Project.toml

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@@ -18,7 +18,6 @@ ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
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HCubature = "19dc6840-f33b-545b-b366-655c7e3ffd49"
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LazyArrays = "5078a376-72f3-5289-bfd5-ec5146d43c02"
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LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
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LoopVectorization = "bdcacae8-1622-11e9-2a5c-532679323890"
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MacroTools = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
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MatrixCorrectionTools = "41f81499-25de-46de-b591-c3cfc21e9eaf"
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Optim = "429524aa-4258-5aef-a3af-852621145aeb"
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HCubature = "1.0.0"
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LazyArrays = "0.21, 0.22, 1, 2"
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LinearAlgebra = "1.9"
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LoopVectorization = "0.12"
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MacroTools = "0.5"
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MatrixCorrectionTools = "1.2.0"
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Optim = "1.0.0"

src/helpers/algebra/common.jl

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@@ -2,7 +2,6 @@ export diageye
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using StatsFuns: logistic
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using StatsFuns: softmax, softmax!
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using LoopVectorization
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using SpecialFunctions: gamma, loggamma
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import LinearAlgebra
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@assert (sA === sB) && (length(sA) === 2) && (first(sA) === last(sA))
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result = zero(promote_type(eltype(A), eltype(B)))
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n = first(sA)
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@turbo for i in 1:n
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for i in 1:n
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for j in 1:n
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result += A[i, j] * B[j, i]
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end

test/helpers/algebra/common_tests.jl

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A = rand(rng, T1, size, size)
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B = rand(rng, T2, size, size)
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# See: https://github.com/JuliaSIMD/LoopVectorization.jl/issues/377
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# Remove if statement once fixed
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if T1 !== Float32 || T2 !== Float32
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@test ReactiveMP.mul_trace(A, B) tr(A * B)
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end
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@test ReactiveMP.mul_trace(A, B) tr(A * B)
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a = rand(rng, T1)
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b = rand(rng, T2)

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