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test: untoggle newly-passing Enzyme tests (#856)
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-24
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+6
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DifferentiationInterface/docs/src/explanation/backends.md

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -63,7 +63,7 @@ Moreover, each context type is supported by a specific subset of backends:
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| `AutoChainRules` |||
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| `AutoDiffractor` |||
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| `AutoEnzyme` (forward) |||
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| `AutoEnzyme` (reverse) || ❌ (soon) |
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| `AutoEnzyme` (reverse) || |
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| `AutoFastDifferentiation` |||
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| `AutoFiniteDiff` |||
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| `AutoFiniteDifferences` |||

DifferentiationInterface/test/Back/Enzyme/test.jl

Lines changed: 5 additions & 23 deletions
Original file line numberDiff line numberDiff line change
@@ -1,3 +1,5 @@
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# see https://github.com/JuliaDiff/DifferentiationInterface.jl/issues/855
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using Pkg
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Pkg.add("Enzyme")
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@@ -14,15 +16,6 @@ check_no_implicit_imports(DifferentiationInterface)
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LOGGING = get(ENV, "CI", "false") == "false"
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function remove_matrix_inputs(scens::Vector{<:Scenario}) # TODO: remove
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if VERSION < v"1.11"
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return scens
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else
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# for https://github.com/EnzymeAD/Enzyme.jl/issues/2071
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return filter(s -> s.x isa Union{Number,AbstractVector}, scens)
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end
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end
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backends = [
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AutoEnzyme(; mode=nothing),
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AutoEnzyme(; mode=Enzyme.Forward),
@@ -55,7 +48,7 @@ end;
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)
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test_differentiation(
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backends[2],
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backends[2:3],
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default_scenarios(;
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include_normal=false,
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include_cachified=true,
@@ -82,16 +75,10 @@ end
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AutoEnzyme(; mode=Enzyme.Reverse), AutoEnzyme(; mode=Enzyme.Forward)
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),
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],
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remove_matrix_inputs(default_scenarios(; include_constantified=true));
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default_scenarios(; include_constantified=true, include_cachified=true);
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excluded=FIRST_ORDER,
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logging=LOGGING,
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)
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test_differentiation(
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AutoEnzyme(; mode=Enzyme.Forward);
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excluded=vcat(FIRST_ORDER, [:hessian, :hvp]),
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logging=LOGGING,
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)
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end
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@testset "Sparse" begin
@@ -100,12 +87,7 @@ end
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if VERSION < v"1.11"
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sparse_scenarios()
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else
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filter(sparse_scenarios()) do s
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# for https://github.com/EnzymeAD/Enzyme.jl/issues/2168
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(s.x isa AbstractVector) &&
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(s.f != DIT.sumdiffcube) &&
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(s.f != DIT.sumdiffcube_mat)
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end
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filter(s -> s.x isa AbstractVector, sparse_scenarios())
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end;
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sparsity=true,
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logging=LOGGING,

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