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Reformat four files that drifted from Runic #1271

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Merged
ChrisRackauckas merged 1 commit into from
Aug 29, 2026
+18 −18
Merged

Reformat four files that drifted from Runic #1271

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6 changes: 3 additions & 3 deletions ext/LinearSolveForwardDiffExt.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -858,9 +858,9 @@ function partials_to_list(partial_matrix::SparseMatrixCSC)
V = ForwardDiff.valtype(T) # use type for concrete array below in empty-nz case (e.g. all-zero Jacobian at init)
return [
SparseMatrixCSC(
m, n, partial_matrix.colptr, partial_matrix.rowval,
V[nz[i][k] for i in eachindex(nz)]
) for k in 1:p
m, n, partial_matrix.colptr, partial_matrix.rowval,
V[nz[i][k] for i in eachindex(nz)]
) for k in 1:p
]
end

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10 changes: 5 additions & 5 deletions test/Core/forwarddiff_gpu.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -30,8 +30,8 @@ end
function dual_problem(n, p)
A = [
ForwardDiff.Dual{Nothing}(
float(i == j ? 10 + i : 0.3 * (i + j)), ntuple(k -> 0.1k + 0.01 * (i + j), p)
) for i in 1:n, j in 1:n
float(i == j ? 10 + i : 0.3 * (i + j)), ntuple(k -> 0.1k + 0.01 * (i + j), p)
) for i in 1:n, j in 1:n
]
b = [ForwardDiff.Dual{Nothing}(float(i), ntuple(k -> 0.05k + 0.1i, p)) for i in 1:n]
return A, b
Expand All @@ -42,9 +42,9 @@ value_error(got, ref) = maximum(abs, ForwardDiff.value.(got) .- ForwardDiff.valu
function partials_error(got, ref)
return maximum(
maximum(
abs,
collect(ForwardDiff.partials(x)) .- collect(ForwardDiff.partials(y))
) for (x, y) in zip(got, ref)
abs,
collect(ForwardDiff.partials(x)) .- collect(ForwardDiff.partials(y))
) for (x, y) in zip(got, ref)
)
end

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16 changes: 8 additions & 8 deletions test/Core/forwarddiff_overloads.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -303,8 +303,8 @@ prob = LinearProblem(sparse(plain_A), b)
for nchunk in (1, 2, 3)
bd = [
ForwardDiff.Dual{Nothing, Float64, nchunk}(
Float64(i), ForwardDiff.Partials(ntuple(k -> sin(i + k), nchunk))
) for i in 1:5
Float64(i), ForwardDiff.Partials(ntuple(k -> sin(i + k), nchunk))
) for i in 1:5
]
cache = LinearSolve.__init(LinearProblem(Asp, bd), PureKLUFactorization())
@test eltype(cache.A) == Float64 # A not promoted
Expand All @@ -313,9 +313,9 @@ prob = LinearProblem(sparse(plain_A), b)
@test isapprox(ForwardDiff.value.(u), ForwardDiff.value.(uref); rtol = 1.0e-10)
@test all(
isapprox(
ForwardDiff.partials(u[i], j), ForwardDiff.partials(uref[i], j);
rtol = 1.0e-8, atol = 1.0e-12
) for i in 1:5, j in 1:nchunk
ForwardDiff.partials(u[i], j), ForwardDiff.partials(uref[i], j);
rtol = 1.0e-8, atol = 1.0e-12
) for i in 1:5, j in 1:nchunk
)
end

Expand Down Expand Up @@ -863,9 +863,9 @@ end
p = 3
A = [
ForwardDiff.Dual{Nothing}(
float(i == j ? 10 + i : 0.3 * (i + j)),
ntuple(k -> 0.1k + 0.01 * (i + j), p)
) for i in 1:n, j in 1:n
float(i == j ? 10 + i : 0.3 * (i + j)),
ntuple(k -> 0.1k + 0.01 * (i + j), p)
) for i in 1:n, j in 1:n
]
b = [ForwardDiff.Dual{Nothing}(float(i), ntuple(k -> 0.05k + 0.1i, p)) for i in 1:n]
reference = solve(LinearProblem(A, b), LUFactorization()).u
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4 changes: 2 additions & 2 deletions test/qa/allocations.jl
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Expand Up @@ -112,8 +112,8 @@ const DUAL_XP_LINSOLVE_RHS! = getproperty(
function dual_linear_problem(n, p)
A = [
ForwardDiff.Dual{Nothing}(
float(i == j ? 10 + i : 0.3 * (i + j)), ntuple(k -> 0.1k + 0.01 * (i + j), p)
) for i in 1:n, j in 1:n
float(i == j ? 10 + i : 0.3 * (i + j)), ntuple(k -> 0.1k + 0.01 * (i + j), p)
) for i in 1:n, j in 1:n
]
b = [ForwardDiff.Dual{Nothing}(float(i), ntuple(k -> 0.05k + 0.1i, p)) for i in 1:n]
return A, b
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