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test.jl
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# see https://github.com/JuliaDiff/DifferentiationInterface.jl/issues/855
using Pkg
Pkg.activate(@__DIR__)
include("../../testutils.jl")
using ADTypes: ADTypes
using DifferentiationInterface, DifferentiationInterfaceTest
import DifferentiationInterfaceTest as DIT
using Enzyme: Enzyme
using LinearAlgebra
using StaticArrays
using Test
using ExplicitImports
check_no_implicit_imports(DifferentiationInterface)
backends = [
AutoEnzyme(; mode = nothing),
AutoEnzyme(; mode = Enzyme.Forward),
AutoEnzyme(; mode = Enzyme.Reverse),
AutoEnzyme(; mode = nothing, function_annotation = Enzyme.Const),
]
duplicated_backends = [
AutoEnzyme(; mode = Enzyme.Forward, function_annotation = Enzyme.Duplicated),
AutoEnzyme(; mode = Enzyme.Reverse, function_annotation = Enzyme.Duplicated),
]
@testset "Checks" begin
@testset "Check $(typeof(backend))" for backend in backends
@test check_available(backend)
@test check_inplace(backend)
end
end;
@testset "First order" begin
test_differentiation(
backends, default_scenarios(); excluded = SECOND_ORDER, logging = LOGGING
)
test_differentiation(
backends[1:3],
default_scenarios(; include_normal = false, include_constantified = true);
excluded = SECOND_ORDER,
logging = LOGGING,
)
test_differentiation(
backends[2:3],
default_scenarios(;
include_normal = false,
include_cachified = true,
include_constantorcachified = true,
use_tuples = true,
);
excluded = SECOND_ORDER,
logging = LOGGING,
)
test_differentiation(
duplicated_backends,
default_scenarios(; include_normal = false, include_closurified = true);
excluded = SECOND_ORDER,
logging = LOGGING,
)
end
@testset "Second order" begin
test_differentiation(
[
AutoEnzyme(),
SecondOrder(
AutoEnzyme(; mode = Enzyme.Reverse), AutoEnzyme(; mode = Enzyme.Forward)
),
],
default_scenarios(; include_constantified = true, include_cachified = true);
excluded = FIRST_ORDER,
logging = LOGGING,
)
end
@testset "Sparse" begin
test_differentiation(
MyAutoSparse.(AutoEnzyme(; function_annotation = Enzyme.Const)),
if VERSION < v"1.11"
sparse_scenarios()
else
filter(s -> s.x isa AbstractVector, sparse_scenarios())
end;
sparsity = true,
logging = LOGGING,
)
end
@testset "Static" begin
filtered_static_scenarios = filter(static_scenarios()) do s
DIT.operator_place(s) == :out && DIT.function_place(s) == :out
end
test_differentiation(
[AutoEnzyme(; mode = Enzyme.Forward), AutoEnzyme(; mode = Enzyme.Reverse)],
filtered_static_scenarios;
excluded = SECOND_ORDER,
logging = LOGGING,
)
end
@testset "Coverage" begin
# ConstantOrCache without cache
f_nocontext(x, p) = x
@test I == DifferentiationInterface.jacobian(
f_nocontext, AutoEnzyme(; mode = Enzyme.Forward), rand(10), ConstantOrCache(nothing)
)
@test I == DifferentiationInterface.jacobian(
f_nocontext, AutoEnzyme(; mode = Enzyme.Reverse), rand(10), ConstantOrCache(nothing)
)
end
@testset "Hints" begin
@testset "MutabilityError" begin
f = let
cache = [0.0]
x -> sum(copyto!(cache, x))
end
e = nothing
try
gradient(f, AutoEnzyme(), [1.0])
catch e
end
msg = sprint(showerror, e)
@test occursin("AutoEnzyme", msg)
@test occursin("function_annotation", msg)
@test occursin("ADTypes", msg)
end
@testset "RuntimeActivityError" begin
function g(active_var, constant_var, cond)
if cond
return active_var
else
return constant_var
end
end
function h(active_var, constant_var, cond)
return [g(active_var, constant_var, cond), g(active_var, constant_var, cond)]
end
e = nothing
try
pushforward(
h,
AutoEnzyme(; mode = Enzyme.Forward),
[1.0],
([1.0],),
Constant([1.0]),
Constant(true),
)
catch e
end
msg = sprint(showerror, e)
@test_broken occursin("AutoEnzyme", msg)
@test_broken occursin("ADTypes", msg)
end
end
@testset "Empty arrays" begin
test_differentiation(
[AutoEnzyme(; mode = Enzyme.Forward), AutoEnzyme(; mode = Enzyme.Reverse)],
empty_scenarios();
excluded = [:jacobian],
)
end;