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[BREAKING] Move sparse functionality into package extensions (#448)
* Move extras in core code * Update backend extensions * Update docs * Typos * Typos * Fixes * Typos * Fix * Fix ForwardDiff * Fixes * Fixes * Fix Enzyme * Bump versions and compats * Move sparse functionality to extensions * Remove prefixes and add docs
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13 changes: 13 additions & 0 deletions
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...ce/ext/DifferentiationInterfaceSparseArraysExt/DifferentiationInterfaceSparseArraysExt.jl
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| module DifferentiationInterfaceSparseArraysExt | ||
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| using ADTypes: ADTypes | ||
| using Compat | ||
| using DifferentiationInterface | ||
| using DifferentiationInterface: | ||
| DenseSparsityDetector, PushforwardFast, PushforwardSlow, basis, pushforward_performance | ||
| import DifferentiationInterface as DI | ||
| using SparseArrays: SparseMatrixCSC, nonzeros, nzrange, rowvals, sparse | ||
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| include("sparsity_detector.jl") | ||
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| end |
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114
DifferentiationInterface/ext/DifferentiationInterfaceSparseArraysExt/sparsity_detector.jl
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| ## Direct | ||
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| function ADTypes.jacobian_sparsity(f, x, detector::DenseSparsityDetector{:direct}) | ||
| @compat (; backend, atol) = detector | ||
| J = jacobian(f, backend, x) | ||
| return sparse(abs.(J) .> atol) | ||
| end | ||
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| function ADTypes.jacobian_sparsity(f!, y, x, detector::DenseSparsityDetector{:direct}) | ||
| @compat (; backend, atol) = detector | ||
| J = jacobian(f!, y, backend, x) | ||
| return sparse(abs.(J) .> atol) | ||
| end | ||
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| function ADTypes.hessian_sparsity(f, x, detector::DenseSparsityDetector{:direct}) | ||
| @compat (; backend, atol) = detector | ||
| H = hessian(f, backend, x) | ||
| return sparse(abs.(H) .> atol) | ||
| end | ||
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| ## Iterative | ||
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| function ADTypes.jacobian_sparsity(f, x, detector::DenseSparsityDetector{:iterative}) | ||
| @compat (; backend, atol) = detector | ||
| y = f(x) | ||
| n, m = length(x), length(y) | ||
| I, J = Int[], Int[] | ||
| if pushforward_performance(backend) isa PushforwardFast | ||
| p = similar(y) | ||
| extras = prepare_pushforward_same_point( | ||
| f, backend, x, basis(backend, x, first(CartesianIndices(x))) | ||
| ) | ||
| for (kj, j) in enumerate(CartesianIndices(x)) | ||
| pushforward!(f, p, extras, backend, x, basis(backend, x, j)) | ||
| for ki in LinearIndices(p) | ||
| if abs(p[ki]) > atol | ||
| push!(I, ki) | ||
| push!(J, kj) | ||
| end | ||
| end | ||
| end | ||
| else | ||
| p = similar(x) | ||
| extras = prepare_pullback_same_point( | ||
| f, backend, x, basis(backend, y, first(CartesianIndices(y))) | ||
| ) | ||
| for (ki, i) in enumerate(CartesianIndices(y)) | ||
| pullback!(f, p, extras, backend, x, basis(backend, y, i)) | ||
| for kj in LinearIndices(p) | ||
| if abs(p[kj]) > atol | ||
| push!(I, ki) | ||
| push!(J, kj) | ||
| end | ||
| end | ||
| end | ||
| end | ||
| return sparse(I, J, ones(Bool, length(I)), m, n) | ||
| end | ||
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| function ADTypes.jacobian_sparsity(f!, y, x, detector::DenseSparsityDetector{:iterative}) | ||
| @compat (; backend, atol) = detector | ||
| n, m = length(x), length(y) | ||
| I, J = Int[], Int[] | ||
| if pushforward_performance(backend) isa PushforwardFast | ||
| p = similar(y) | ||
| extras = prepare_pushforward_same_point( | ||
| f!, y, backend, x, basis(backend, x, first(CartesianIndices(x))) | ||
| ) | ||
| for (kj, j) in enumerate(CartesianIndices(x)) | ||
| pushforward!(f!, y, p, extras, backend, x, basis(backend, x, j)) | ||
| for ki in LinearIndices(p) | ||
| if abs(p[ki]) > atol | ||
| push!(I, ki) | ||
| push!(J, kj) | ||
| end | ||
| end | ||
| end | ||
| else | ||
| p = similar(x) | ||
| extras = prepare_pullback_same_point( | ||
| f!, y, backend, x, basis(backend, y, first(CartesianIndices(y))) | ||
| ) | ||
| for (ki, i) in enumerate(CartesianIndices(y)) | ||
| pullback!(f!, y, p, extras, backend, x, basis(backend, y, i)) | ||
| for kj in LinearIndices(p) | ||
| if abs(p[kj]) > atol | ||
| push!(I, ki) | ||
| push!(J, kj) | ||
| end | ||
| end | ||
| end | ||
| end | ||
| return sparse(I, J, ones(Bool, length(I)), m, n) | ||
| end | ||
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| function ADTypes.hessian_sparsity(f, x, detector::DenseSparsityDetector{:iterative}) | ||
| @compat (; backend, atol) = detector | ||
| n = length(x) | ||
| I, J = Int[], Int[] | ||
| p = similar(x) | ||
| extras = prepare_hvp_same_point( | ||
| f, backend, x, basis(backend, x, first(CartesianIndices(x))) | ||
| ) | ||
| for (kj, j) in enumerate(CartesianIndices(x)) | ||
| hvp!(f, p, extras, backend, x, basis(backend, x, j)) | ||
| for ki in LinearIndices(p) | ||
| if abs(p[ki]) > atol | ||
| push!(I, ki) | ||
| push!(J, kj) | ||
| end | ||
| end | ||
| end | ||
| return sparse(I, J, ones(Bool, length(I)), n, n) | ||
| end |
47 changes: 47 additions & 0 deletions
47
...tionInterfaceSparseMatrixColoringsExt/DifferentiationInterfaceSparseMatrixColoringsExt.jl
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,47 @@ | ||
| module DifferentiationInterfaceSparseMatrixColoringsExt | ||
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| using ADTypes: | ||
| ADTypes, | ||
| AbstractADType, | ||
| AutoSparse, | ||
| dense_ad, | ||
| coloring_algorithm, | ||
| sparsity_detector, | ||
| jacobian_sparsity, | ||
| hessian_sparsity | ||
| using Compat | ||
| using DifferentiationInterface | ||
| using DifferentiationInterface: | ||
| GradientExtras, | ||
| HessianExtras, | ||
| HVPExtras, | ||
| JacobianExtras, | ||
| PullbackExtras, | ||
| PushforwardExtras, | ||
| PushforwardFast, | ||
| PushforwardSlow, | ||
| Tangents, | ||
| dense_ad, | ||
| maybe_dense_ad, | ||
| maybe_inner, | ||
| maybe_outer, | ||
| multibasis, | ||
| pick_batchsize, | ||
| pushforward_performance | ||
| import DifferentiationInterface as DI | ||
| using SparseMatrixColorings: | ||
| AbstractColoringResult, | ||
| ColoringProblem, | ||
| GreedyColoringAlgorithm, | ||
| coloring, | ||
| column_colors, | ||
| row_colors, | ||
| column_groups, | ||
| row_groups, | ||
| decompress, | ||
| decompress! | ||
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| include("jacobian.jl") | ||
| include("hessian.jl") | ||
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| end |
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