Tests
- LinearAlgebra/diagonal/relty = BigFloat, elty = BigFloat/diag @test isempty(#= /cache/build/default-aws-aarch64-ci-1-0/julialang/julia-master/julia-649aee791d/share/julia/stdlib/v1.13/LinearAlgebra/test/diagonal.jl:111 =# @inferred(diag(D, -n - 1)))stdlib/LinearAlgebra/test/diagonal.jl:111github100% reliable0μs average duration
- ccall @test #= /Users/julia/.julia/scratchspaces/a66863c6-20e8-4ff4-8a62-49f30b1f605e/agent-cache/default-honeycrisp-R17H3W25T9.0/build/default-honeycrisp-R17H3W25T9-0/julialang/julia-master/julia-ed9f4405c6/share/julia/test/ccall.jl:105 =# @ccall_echo_load(Ref([144, 172], 2), Ptr{Int}, Ref{Int}) === 172share/julia/test/ccall.jl:105github100% reliable0μs average duration
- LinearAlgebra/addmul/mul!(::Matrix{BigFloat}, ::LinearAlgebra.Bidiagonal{BigFloat, V} where V<:AbstractVector{BigFloat}, ::LinearAlgebra.Diagonal{Float32, V} where V<:AbstractVector{Float32}, α, β)/α = -0.2116482313867567299769945066145737655460834503173828125, β = -0.2116482313867567299769945066145737655460834503173828125/β = 0 ignores C .= NaN @test returned_mat === Ccopystdlib/LinearAlgebra/test/addmul.jl:141github100% reliable0μs average duration
- iterators/Pairs type @test #= /cache/build/tester-amdci5-9/julialang/julia-master/julia-79b39a5eda/share/julia/test/iterators.jl:735 =# @inferred(Base.IteratorEltype(d)) == Base.HasEltype()share/julia/test/iterators.jl:735github100% reliable0μs average duration
- LinearAlgebra/bidiag/relty = Int32, elty = Int32/uplo = U/diag @test #= C:\buildkite-agent\builds\win2k22-amdci6-2\julialang\julia-master\julia-d6af199c5d\share\julia\stdlib\v1.13\LinearAlgebra\test\bidiag.jl:393 =# @inferred(diag(T, if uplo === :U 1 else -1 end))::typeof(dv) == evstdlib/LinearAlgebra/test/bidiag.jl:393github100% reliable0μs average duration
- Compiler/inference @test Base.return_types((f->begin #= /cache/build/tester-amdci5-10/julialang/julia-master/julia-123a556434/share/julia/Compiler/test/inference.jl:1121 =# f(1) end), (typeof((x::String->begin #= /cache/build/tester-amdci5-10/julialang/julia-master/julia-123a556434/share/julia/Compiler/test/inference.jl:1121 =# x end)),)) == Any[Union{}]share/julia/Compiler/test/inference.jl:1121github100% reliable0μs average duration
- LinearAlgebra/tridiag/elty = Int64/mat_type = LinearAlgebra.Tridiagonal/Multiplication with strided matrix/vector @test begin x = fill(1.0, n) #= /usr/home/julia/.buildkite-agent/builds/freebsd13-amdci6-1/julialang/julia-master/julia-e1e3a46a3a/share/julia/stdlib/v1.13/LinearAlgebra/test/tridiag.jl:338 =# A * x ≈ Array(A) * x endstdlib/LinearAlgebra/test/tridiag.jl:338github100% reliable0μs average duration
- reducedim/test reductions over region: 2 @test #= C:\buildkite-agent\builds\win2k22-amdci6-4\julialang\julia-master\julia-ed9f4405c6\share\julia\test\reducedim.jl:88 =# @inferred(count(!, Breduc, dims = region)) ≈ safe_count(.!(Breduc), region)share/julia/test/reducedim.jl:88github100% reliable0μs average duration
- LinearAlgebra/addmul/mul!(::LinearAlgebra.Diagonal{ComplexF64, V} where V<:AbstractVector{ComplexF64}, ::LinearAlgebra.Diagonal{Float64, V} where V<:AbstractVector{Float64}, ::LinearAlgebra.Diagonal{ComplexF64, V} where V<:AbstractVector{ComplexF64}, α, β)/α = 1.5138291889953628 - 0.8562980174826337im, β = 1.5138291889953628 - 0.8562980174826337im @test returned_mat === Ccopystdlib/LinearAlgebra/test/addmul.jl:141github100% reliable0μs average duration
- LinearAlgebra/addmul/mul!(::Matrix{BigFloat}, ::LinearAlgebra.Hermitian{Float32, S} where S<:(AbstractMatrix{<:Float32}), ::LinearAlgebra.UnitUpperTriangular{BigFloat, S} where S<:AbstractMatrix{BigFloat}, α, β)/α = 1.0, β = false/adjoint and transpose/fa = identity, fb = adjoint @test ≈(collect(returned_mat), exp_val, rtol = rtol, atol = atol)stdlib/LinearAlgebra/test/addmul.jl:145github100% reliable0μs average duration
- Printf/Printf/integers @test #= /cache/build/tester-amdci4-13/julialang/julia-master/julia-123a556434/share/julia/stdlib/v1.13/Printf/test/runtests.jl:649 =# Printf.@sprintf("%1i", 1024) == "1024"stdlib/Printf/test/runtests.jl:649github100% reliable0μs average duration
- LinearAlgebra/addmul/mul!(::Matrix{ComplexF64}, ::LinearAlgebra.LowerTriangular{Float64, S} where S<:AbstractMatrix{Float64}, ::LinearAlgebra.Bidiagonal{ComplexF32, V} where V<:AbstractVector{ComplexF32}, α, β)/α = true, β = -0.12704690988767064 - 0.5335890643008331im/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/basics @test #= /Users/julia/.julia/scratchspaces/a66863c6-20e8-4ff4-8a62-49f30b1f605e/agent-cache/default-grannysmith-C07ZQ07FJYVY.0/build/default-grannysmith-C07ZQ07FJYVY-0/julialang/julia-master/julia-621d14977a/share/julia/stdlib/v1.13/Printf/test/runtests.jl:449 =# Printf.@sprintf("%f", parse(BigFloat, "1e400")) == "10000000000000000000000000000000000000000000000000000000000000000000000000000025262527574416492004687051900140830217136998040684679611623086405387447100385714565637522507383770691831689647535911648520404034824470543643098638520633064715221151920028135130764414460468236314621044034960475540018328999334468948008954289495190631358190153259681118693204411689043999084305348398480210026863210192871358464.000000"stdlib/Printf/test/runtests.jl:449github100% reliable0μs average duration
- ranges/constant-valued ranges (issues #10391 and #29052)/with UnitRange of Int64 @test #= /cache/build/default-aws-aarch64-ci-0-3/julialang/julia-master/julia-4969ab080f/share/julia/test/ranges.jl:2024 =# @inferred(r - r) == [0.0, 0.0, 0.0, 0.0]share/julia/test/ranges.jl:2024github100% reliable0μs average duration
- LinearAlgebra/addmul/mul!(::Matrix{ComplexF64}, ::LinearAlgebra.Symmetric{Int32, S} where S<:(AbstractMatrix{<:Int32}), ::LinearAlgebra.Diagonal{ComplexF64, V} where V<:AbstractVector{ComplexF64}, α, β)/α = 1.6100384207231075 - 0.7473249079543374im, β = 0.0 + 0.0im @test returned_mat === Ccopystdlib/LinearAlgebra/test/addmul.jl:141github100% reliable0μs average duration
- LinearAlgebra/addmul/mul!(::LinearAlgebra.Diagonal{Float64, V} where V<:AbstractVector{Float64}, ::LinearAlgebra.Diagonal{Int64, V} where V<:AbstractVector{Int64}, ::LinearAlgebra.Diagonal{Float32, V} where V<:AbstractVector{Float32}, α, β)/α = 1.0, β = -1.1570235881322553 @test ≈(collect(returned_mat), exp_val, rtol = rtol, atol = atol)stdlib/LinearAlgebra/test/addmul.jl:145github100% reliable0μs average duration
- bitarray/map over bitarrays/map! for length 0 @test map!(min, b, b1, b2) == map!(((x, y)->begin #= /cache/build/tester-amdci4-14/julialang/julia-master/julia-6b43c1aa5f/share/julia/test/bitarray.jl:1502 =# min(x, y) end), b, b1, b2) == min.(b1, b2) == bshare/julia/test/bitarray.jl:1502github100% reliable0μs average duration
- LinearAlgebra/matmul/muladd & structured matrices @test #= C:\buildkite-agent\builds\win2k22-amdci6-7\julialang\julia-master\julia-9c8c57e067\share\julia\stdlib\v1.13\LinearAlgebra\test\matmul.jl:655 =# @evalpoly(A33, 1.0I, 1.0I) == I + A33stdlib/LinearAlgebra/test/matmul.jl:655github100% reliable0μs average duration
- LinearAlgebra/addmul/mul!(::Matrix{BigFloat}, ::LinearAlgebra.UpperTriangular{Float64, S} where S<:AbstractMatrix{Float64}, ::LinearAlgebra.LowerTriangular{Float64, S} where S<:AbstractMatrix{Float64}, α, β)/α = 0.167285049282090148015100794509635306894779205322265625, β = 0.0/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!(::Matrix{Float64}, ::LinearAlgebra.SymTridiagonal{Int64, V} where V<:AbstractVector{Int64}, ::LinearAlgebra.SymTridiagonal{Float32, V} where V<:AbstractVector{Float32}, α, β)/α = true, β = 1.356840860805939/adjoint and transpose/fa = transpose, fb = transpose @test ≈(collect(returned_mat), exp_val, rtol = rtol, atol = atol)stdlib/LinearAlgebra/test/addmul.jl:145github100% reliable0μs average duration