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Fix @test_broken problems #546

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merged 4 commits into from
Feb 6, 2024
Merged

Fix @test_broken problems #546

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e3fd7dc
Fix `@test_broken` problems
simsurace Feb 6, 2024
b860116
Correct remaining tests
simsurace Feb 6, 2024
6412453
Merge branch 'master' into fix-CI
simsurace Feb 6, 2024
50de544
Bump version
simsurace Feb 6, 2024
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3 changes: 2 additions & 1 deletion test/basekernels/periodic.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,7 @@
TestUtils.test_interface(PeriodicKernel(; r=[0.8, 0.7]), RowVecs{Float64})

# test_ADs(r->PeriodicKernel(r =exp.(r)), log.(r), ADs = [:ForwardDiff, :ReverseDiff])
@test_broken "Undefined adjoint for Sinus metric, and failing randomly for ForwardDiff and ReverseDiff"
# Undefined adjoint for Sinus metric, and failing randomly for ForwardDiff and ReverseDiff
@test_broken false
test_params(k, (r,))
end
3 changes: 2 additions & 1 deletion test/basekernels/sm.jl
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Expand Up @@ -57,5 +57,6 @@
end

# test_ADs(x->spectral_mixture_kernel(exp.(x[1:3]), reshape(x[4:18], 5, 3), reshape(x[19:end], 5, 3)), vcat(log.(αs₁), γs[:], ωs[:]), dims = [5,5])
@test_broken "No tests passing (BaseKernel)"
# No tests passing (BaseKernel)
@test_broken false
end
3 changes: 2 additions & 1 deletion test/basekernels/wiener.jl
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Expand Up @@ -44,5 +44,6 @@
TestUtils.test_interface(k2, x0, x1, x2)
TestUtils.test_interface(k3, x0, x1, x2)
# test_ADs(()->WienerKernel(i=1))
@test_broken "No tests passing"
# No tests passing
@test_broken false
end
40 changes: 32 additions & 8 deletions test/transform/selecttransform.jl
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Expand Up @@ -104,17 +104,41 @@
end

@testset "$(AD)" for AD in [:ReverseDiff]
@test_broken ga = gradient(AD, A) do a
testfunction(ta_row, a, 2)
@test_broken let
gx = gradient(AD, X) do x
testfunction(tx_row, x, 2)
end
ga = gradient(AD, A) do a
testfunction(ta_row, a, 2)
end
gx ≈ ga
end
@test_broken ga = gradient(AD, A) do a
testfunction(ta_col, a, 1)
@test_broken let
gx = gradient(AD, X) do x
testfunction(tx_col, x, 1)
end
ga = gradient(AD, A) do a
testfunction(ta_col, a, 1)
end
gx ≈ ga
end
@test_broken ga = gradient(AD, A) do a
testfunction(ta_row, a, B, 2)
@test_broken let
gx = gradient(AD, X) do x
testfunction(tx_row, x, Y, 2)
end
ga = gradient(AD, A) do a
testfunction(ta_row, a, B, 2)
end
gx ≈ ga
end
@test_broken ga = gradient(AD, A) do a
testfunction(ta_col, a, C, 1)
@test_broken let
gx = gradient(AD, X) do x
testfunction(tx_col, x, Z, 1)
end
ga = gradient(AD, A) do a
testfunction(ta_col, a, C, 1)
end
gx ≈ ga
end
end

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