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Add an option to provide the sparsity pattern of jacobians and hessians #284

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Aug 5, 2024
Merged

Add an option to provide the sparsity pattern of jacobians and hessians #284

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863d921
Add an option to provide the sparsity pattern of jacobians and hessians
amontoison Aug 4, 2024
3624a9e
Apply suggestions from code review
amontoison Aug 4, 2024
8c73f99
Update sparse_jacobian.jl
amontoison Aug 4, 2024
492b15e
Update sparse_hessian.jl
amontoison Aug 4, 2024
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34 changes: 30 additions & 4 deletions src/sparse_hessian.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -20,13 +20,26 @@ function SparseADHessian(
f,
ncon,
c!;
x0::S = rand(nvar),
x0::AbstractVector = rand(nvar),
coloring::AbstractColoringAlgorithm = GreedyColoringAlgorithm(),
detector::AbstractSparsityDetector = TracerSparsityDetector(),
kwargs...,
)
H = compute_hessian_sparsity(f, nvar, c!, ncon, detector = detector)
SparseADHessian(nvar, f, ncon, c!, H; x0, coloring, kwargs...)
end

function SparseADHessian(
nvar,
f,
ncon,
c!,
H::SparseMatrixCSC{Bool,Int64};
x0::S = rand(nvar),
coloring::AbstractColoringAlgorithm = GreedyColoringAlgorithm(),
kwargs...,
) where {S}
T = eltype(S)
H = compute_hessian_sparsity(f, nvar, c!, ncon, detector = detector)

colors, star_set = symmetric_coloring_detailed(H, coloring)
ncolors = maximum(colors)
Expand Down Expand Up @@ -111,12 +124,25 @@ function SparseReverseADHessian(
f,
ncon,
c!;
x0::AbstractVector{T} = rand(nvar),
x0::AbstractVector = rand(nvar),
coloring::AbstractColoringAlgorithm = GreedyColoringAlgorithm(),
detector::AbstractSparsityDetector = TracerSparsityDetector(),
kwargs...,
) where {T}
)
H = compute_hessian_sparsity(f, nvar, c!, ncon, detector = detector)
SparseReverseADHessian(nvar, f, ncon, c!, H; x0, coloring, kwargs...)
end

function SparseReverseADHessian(
nvar,
f,
ncon,
c!,
H::SparseMatrixCSC{Bool,Int64};
x0::AbstractVector{T} = rand(nvar),
coloring::AbstractColoringAlgorithm = GreedyColoringAlgorithm(),
kwargs...,
) where {T}

colors, star_set = symmetric_coloring_detailed(H, coloring)
ncolors = maximum(colors)
Expand Down
16 changes: 14 additions & 2 deletions src/sparse_jacobian.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -15,14 +15,26 @@ function SparseADJacobian(
f,
ncon,
c!;
x0::AbstractVector{T} = rand(nvar),
x0::AbstractVector = rand(nvar),
coloring::AbstractColoringAlgorithm = GreedyColoringAlgorithm(),
detector::AbstractSparsityDetector = TracerSparsityDetector(),
kwargs...,
) where {T}
)
output = similar(x0, ncon)
J = compute_jacobian_sparsity(c!, output, x0, detector = detector)
SparseADJacobian(nvar, f, ncon, c!, J; x0, coloring, kwargs...)
end

function SparseADJacobian(
nvar,
f,
ncon,
c!,
J::SparseMatrixCSC{Bool,Int64};
x0::AbstractVector{T} = rand(nvar),
coloring::AbstractColoringAlgorithm = GreedyColoringAlgorithm(),
kwargs...,
) where {T}
# TODO: use ADTypes.row_coloring instead if you have the right decompression and some heuristic recommends it
colors = ADTypes.column_coloring(J, coloring)
ncolors = maximum(colors)
Expand Down
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