Tests
- Compiler/effects @test Base.infer_effects((Some{Any}, Bool)) do some, boundscheck #= /cache/build/default-aws-aarch64-ci-0-1/julialang/julia-master/julia-fb01f9159c/share/julia/Compiler/test/effects.jl:471 =# getfield(some, 1, boundscheck) end |> Compiler.is_nothrowshare/julia/Compiler/test/effects.jl:470github100% reliable0μs average duration
- Compiler/ssair @test !(Compiler.visit_conditional_successors(ir, 1) do succ::Int #= /usr/home/julia/.buildkite-agent/builds/freebsd13-amdci6-1/julialang/julia-master/julia-4e2c472a3b/share/julia/Compiler/test/ssair.jl:291 =# push!(visited, succ) #= /usr/home/julia/.buildkite-agent/builds/freebsd13-amdci6-1/julialang/julia-master/julia-4e2c472a3b/share/julia/Compiler/test/ssair.jl:292 =# return false end)share/julia/Compiler/test/ssair.jl:290github100% reliable0μs average duration
- LinearAlgebra/addmul/mul!(::Matrix{Float64}, ::LinearAlgebra.Bidiagonal{Int64, V} where V<:AbstractVector{Int64}, ::LinearAlgebra.LowerTriangular{Float32, S} where S<:AbstractMatrix{Float32}, α, β)/α = true, β = -0.06258350287739653/adjoint and transpose/fa = transpose, fb = identity @test ≈(collect(returned_mat), exp_val, rtol = rtol, atol = atol)stdlib/LinearAlgebra/test/addmul.jl:145github100% reliable0μs average duration
- LinearAlgebra/addmul/mul!(::Matrix{ComplexF64}, ::LinearAlgebra.UnitLowerTriangular{ComplexF64, S} where S<:AbstractMatrix{ComplexF64}, ::LinearAlgebra.UnitLowerTriangular{Float32, S} where S<:AbstractMatrix{Float32}, α, β)/α = 0.8403739176877895 + 0.3738141625380433im, β = 0.0 + 0.0im/adjoint and transpose/fa = adjoint, fb = transpose @test returned_mat === Ccopystdlib/LinearAlgebra/test/addmul.jl:141github100% reliable0μs average duration
- LinearAlgebra/dense/For A containing Float64/For b containing ComplexF64/Test nullspace @test #= /Users/julia/.julia/scratchspaces/a66863c6-20e8-4ff4-8a62-49f30b1f605e/agent-cache/default-honeycrisp-HL2F7YQ3XH.0/build/default-honeycrisp-HL2F7YQ3XH-0/julialang/julia-master/julia-5b9d2fa086/share/julia/stdlib/v1.13/LinearAlgebra/test/dense.jl:130 =# @inferred(nullspace((b[1, 1:0])')) == Matrix(I, 0, 0)stdlib/LinearAlgebra/test/dense.jl:130github100% reliable0μs average duration
- Compiler/inference @test map((x->begin #= C:\buildkite-agent\builds\win2k22-amdci6-0\julialang\julia-master\julia-133e48b9ff\share\julia\Compiler\test\inference.jl:4484 =# if x[1] == 0 0 else Compiler.get_enter_idx(handlers[x[1]]) end end), handler_at) == first.(x)share/julia/Compiler/test/inference.jl:4484github100% reliable0μs average duration
- abstractarray/T = Main.Test72Main_abstractarray.TSlow, shape = (24,)/test_vector_indexing{Main.Test72Main_abstractarray.TSlow} @test B[1:var"end"] == A[1:var"end"] == 1:Nshare/julia/test/abstractarray.jl:501github100% reliable0μs average duration
- LinearAlgebra/addmul/mul!(::Matrix{Float64}, ::LinearAlgebra.Bidiagonal{Float32, V} where V<:AbstractVector{Float32}, ::LinearAlgebra.UnitLowerTriangular{Float64, S} where S<:AbstractMatrix{Float64}, α, β)/α = -0.9437976116618128, β = false/adjoint and transpose/fa = transpose, fb = adjoint @test ≈(collect(returned_mat), exp_val, rtol = rtol, atol = atol)stdlib/LinearAlgebra/test/addmul.jl:145github100% reliable0μs average duration
- Printf/Printf/%e @test #= C:\buildkite-agent\builds\win2k22-amdci6-1\julialang\julia-master\julia-e1e3d4f63a\share\julia\stdlib\v1.13\Printf\test\runtests.jl:174 =# Printf.@sprintf("% #e", Inf) == " Inf"stdlib/Printf/test/runtests.jl:174github100% reliable0μs average duration
- LinearAlgebra/lq/eltya = Float32, n = 13/eltyb = Float64/isview = false/Binary ops @test ≈(begin sq = size(q.factors, 2) #= /usr/home/julia/.buildkite-agent/builds/freebsd13-amdci6-2/julialang/julia-master/julia-03861bbbaf/share/julia/stdlib/v1.13/LinearAlgebra/test/lq.jl:72 =# (Matrix{eltyb}(I, sq, sq) * adjoint(q)) * squareQ(q) end, Matrix(I, n, n), rtol = 5000ε)stdlib/LinearAlgebra/test/lq.jl:72github100% reliable0μs average duration
- LinearAlgebra/givens/Test Givens for ComplexF64/A = ComplexF64[0.36940104479601177 + 0.766001336444963im 0.8852788640021116 + 1.0976624705126263im 0.8828338849162136 - 1.2411847161172875im -0.4881708625511341 + 0.37626280908018117im 0.6476167502044059 + 0.9817554762905771im 1.5478500701350786 + 0.9600087576939358im 0.21440970640341261 + 0.007814700049325156im 2.378809323041021 + 0.645294344186809im 0.35052158810772416 + 1.9995111255939424im 0.9480604209758219 - 0.11153771138997082im; 3.531598629640855 - 1.1147715993397376im -0.2634103820244933 + 0.5151350314955532im -0.13897011593150588 - 0.8961723793473328im 0.8064358328312485 - 1.016159919088572im 0.15784118821899484 + 0.15067557813881158im -0.4625647725872468 - 1.4623774520855777im -1.0557414247098518 + 0.20740472049419334im 0.5504195831092503 - 0.9089408524662802im -0.4737187178279387 + 0.8821135691988868im 0.48872336669128147 - 1.403161976683863im; -4.0584211772135956e-17 + 6.95372017634359e-17im 1.155446744363462 - 3.432957388699944im -1.531155470969218 @test (R')' === Rstdlib/LinearAlgebra/test/givens.jl:38github100% reliable0μs average duration
- LinearAlgebra/dense/inverse of Adjoint @test #= C:\buildkite-agent\builds\win2k22-amdci6-0\julialang\julia-master\julia-86829c5883\share\julia\stdlib\v1.13\LinearAlgebra\test\dense.jl:1237 =# @inferred(inv(B')) * B' ≈ Istdlib/LinearAlgebra/test/dense.jl:1237github100% reliable0μs average duration
- LinearAlgebra/addmul/mul!(::Matrix{BigFloat}, ::LinearAlgebra.Symmetric{Int64, S} where S<:(AbstractMatrix{<:Int64}), ::LinearAlgebra.UpperTriangular{Float32, S} where S<:AbstractMatrix{Float32}, α, β)/α = 0.57702225153321407002948717490653507411479949951171875, β = false/adjoint and transpose/fa = transpose, fb = adjoint @test returned_mat === Ccopystdlib/LinearAlgebra/test/addmul.jl:141github100% reliable0μs average duration
- LinearAlgebra/addmul/mul!(::Matrix{Float64}, ::LinearAlgebra.SymTridiagonal{Int64, V} where V<:AbstractVector{Int64}, ::LinearAlgebra.Symmetric{Int64, S} where S<:(AbstractMatrix{<:Int64}), α, β)/α = 1.0665073455115428, β = 1.0665073455115428/β = 0 ignores C .= NaN @test ≈(collect(returned_mat), exp_val, rtol = rtol, atol = atol)stdlib/LinearAlgebra/test/addmul.jl:145github100% reliable0μs average duration
- LinearAlgebra/tridiag/elty = ComplexF64/tril/triu @test #= /cache/build/default-aws-aarch64-ci-0-4/julialang/julia-master/julia-0df5ad78d0/share/julia/stdlib/v1.13/LinearAlgebra/test/tridiag.jl:174 =# @inferred(triu!(copy(Tridiagonal(dl, d, du)), 2)) == Tridiagonal(zerosdl, zerosd, zerosdu)stdlib/LinearAlgebra/test/tridiag.jl:174github100% reliable0μs average duration
- atomics/Main.Test66Main_atomics.ARefxy{Float64}(NaN, Inf) @test_throws nothing swapfield!(r, :x, x)share/julia/test/atomics.jl:254github100% reliable0μs average duration
- LinearAlgebra/addmul/mul!(::Matrix{ComplexF64}, ::LinearAlgebra.LowerTriangular{Int64, S} where S<:AbstractMatrix{Int64}, ::LinearAlgebra.Hermitian{Float64, S} where S<:(AbstractMatrix{<:Float64}), α, β)/α = true, β = 0.0 + 0.0im/adjoint and transpose/fa = adjoint, fb = adjoint @test returned_mat === Ccopystdlib/LinearAlgebra/test/addmul.jl:141github100% reliable0μs average duration
- LinearAlgebra/addmul/mul!(::Matrix{ComplexF64}, ::LinearAlgebra.LowerTriangular{Float32, S} where S<:AbstractMatrix{Float32}, ::LinearAlgebra.Tridiagonal{Float64, V} where V<:AbstractVector{Float64}, α, β)/α = 1.0 + 0.0im, β = false/adjoint and transpose/fa = adjoint, fb = transpose @test ≈(collect(returned_mat), exp_val, rtol = rtol, atol = atol)stdlib/LinearAlgebra/test/addmul.jl:145github100% reliable0μs average duration
- LinearAlgebra/addmul/mul!(::LinearAlgebra.UpperTriangular{Float64, S} where S<:AbstractMatrix{Float64}, ::LinearAlgebra.UnitUpperTriangular{Float32, S} where S<:AbstractMatrix{Float32}, ::LinearAlgebra.UnitUpperTriangular{Float32, S} where S<:AbstractMatrix{Float32}, α, β)/α = true, β = -2.3545112866991373 @test returned_mat === Ccopystdlib/LinearAlgebra/test/addmul.jl:141github100% reliable0μs average duration
- LinearAlgebra/addmul/mul!(::Matrix{ComplexF64}, ::LinearAlgebra.Bidiagonal{ComplexF64, V} where V<:AbstractVector{ComplexF64}, ::LinearAlgebra.SymTridiagonal{Float32, V} where V<:AbstractVector{Float32}, α, β)/α = 1.0 + 0.0im, β = 0.0 + 0.0im @test ≈(collect(returned_mat), exp_val, rtol = rtol, atol = atol)stdlib/LinearAlgebra/test/addmul.jl:145github100% reliable1s average duration