DifferentiationInterface.jl/DifferentiationInterface/test/Core/SimpleFiniteDiff/test.jl at c194ec52af60e2e1cc43857c9aa542f9b864e579 · JuliaDiff/DifferentiationInterface.jl · GitHub

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using DifferentiationInterface, DifferentiationInterfaceTest
using DifferentiationInterface:
    AutoSimpleFiniteDiff, AutoReverseFromPrimitive, DenseSparsityDetector
using SparseMatrixColorings
using Test

LOGGING = get(ENV, "CI", "false") == "false"

backends = [ #
    AutoSimpleFiniteDiff(; chunksize=5),
    AutoReverseFromPrimitive(AutoSimpleFiniteDiff(; chunksize=4)),
]

second_order_backends = [ #
    SecondOrder(
        AutoSimpleFiniteDiff(; chunksize=5),
        AutoReverseFromPrimitive(AutoSimpleFiniteDiff(; chunksize=4)),
    ),
    SecondOrder(
        AutoReverseFromPrimitive(AutoSimpleFiniteDiff(; chunksize=5)),
        AutoSimpleFiniteDiff(; chunksize=4),
    ),
]

adaptive_backends = [ #
    AutoSimpleFiniteDiff(),
    AutoReverseFromPrimitive(AutoSimpleFiniteDiff()),
    SecondOrder(AutoSimpleFiniteDiff(), AutoReverseFromPrimitive(AutoSimpleFiniteDiff())),
    SecondOrder(AutoReverseFromPrimitive(AutoSimpleFiniteDiff()), AutoSimpleFiniteDiff()),
]

for backend in vcat(backends, second_order_backends)
    @test check_available(backend)
    @test check_inplace(backend)
end

## Dense scenarios

@testset "Dense" begin
    test_differentiation(
        vcat(backends, second_order_backends),
        default_scenarios(; include_constantified=true);
        logging=LOGGING,
    )

    test_differentiation(backends, complex_scenarios(); logging=LOGGING)
end

@testset "Sparse" begin
    test_differentiation(
        MyAutoSparse.(adaptive_backends),
        default_scenarios(; include_constantified=true);
        logging=LOGGING,
    )

    test_differentiation(
        MyAutoSparse.(
            vcat(adaptive_backends, MixedMode(adaptive_backends[1], adaptive_backends[2]))
        ),
        sparse_scenarios(; include_constantified=true, include_cachified=true);
        sparsity=true,
        logging=LOGGING,
    )

    @testset "Complex numbers" begin
        test_differentiation(
            AutoSparse.(
                vcat(
                    adaptive_backends, MixedMode(adaptive_backends[1], adaptive_backends[2])
                );
                sparsity_detector=DenseSparsityDetector(AutoSimpleFiniteDiff(); atol=1e-5),
                coloring_algorithm=GreedyColoringAlgorithm(),
            ),
            complex_sparse_scenarios();
            logging=LOGGING,
        )
    end

    @testset "SparseMatrixColorings access" begin
        jac_for_prep = prepare_jacobian(copy, MyAutoSparse(adaptive_backends[1]), rand(10))
        jac_rev_prep = prepare_jacobian(copy, MyAutoSparse(adaptive_backends[2]), rand(10))
        hess_prep = prepare_hessian(
            x -> sum(abs2, x), MyAutoSparse(adaptive_backends[1]), rand(10)
        )

        @test all(==(1), column_colors(jac_for_prep))
        @test all(==(1), row_colors(jac_rev_prep))
        @test all(==(1), column_colors(hess_prep))
        @test ncolors(jac_for_prep) == 1
        @test ncolors(hess_prep) == 1
        @test only(column_groups(jac_for_prep)) == 1:10
        @test only(row_groups(jac_rev_prep)) == 1:10
        @test only(column_groups(hess_prep)) == 1:10
    end
end