Package evaluation of DifferentiableFlatten on Julia 1.11.4 (a71dd056e0*) started at 2025-04-08T08:24:19.945


################################################################################
# Set-up
#

Installing PkgEval dependencies (TestEnv)...

Set-up completed after 8.57s


################################################################################
# Installation
#

Installing DifferentiableFlatten...
   Resolving package versions...
    Updating `~/.julia/environments/v1.11/Project.toml`
  [c78775a3] + DifferentiableFlatten v0.1.1
    Updating `~/.julia/environments/v1.11/Manifest.toml`
  [d360d2e6] + ChainRulesCore v1.25.1
  [34da2185] + Compat v4.16.0
  [c78775a3] + DifferentiableFlatten v0.1.1
  [d9ec5142] + NamedTupleTools v0.14.3
  [bac558e1] + OrderedCollections v1.8.0
  [ae029012] + Requires v1.3.1
  [56f22d72] + Artifacts v1.11.0
  [ade2ca70] + Dates v1.11.0
  [8f399da3] + Libdl v1.11.0
  [37e2e46d] + LinearAlgebra v1.11.0
  [de0858da] + Printf v1.11.0
  [9a3f8284] + Random v1.11.0
  [ea8e919c] + SHA v0.7.0
  [9e88b42a] + Serialization v1.11.0
  [2f01184e] + SparseArrays v1.11.0
  [fa267f1f] + TOML v1.0.3
  [cf7118a7] + UUIDs v1.11.0
  [4ec0a83e] + Unicode v1.11.0
  [e66e0078] + CompilerSupportLibraries_jll v1.1.1+0
  [4536629a] + OpenBLAS_jll v0.3.27+1
  [bea87d4a] + SuiteSparse_jll v7.7.0+0
  [8e850b90] + libblastrampoline_jll v5.11.0+0

Installation completed after 1.89s


################################################################################
# Precompilation
#

Precompiling PkgEval dependencies...

Precompiling package dependencies...

Precompilation completed after 19.24s


################################################################################
# Testing
#

     Testing DifferentiableFlatten
      Status `/tmp/jl_hGnXqS/Project.toml`
  [d360d2e6] ChainRulesCore v1.25.1
  [c78775a3] DifferentiableFlatten v0.1.1
  [4076af6c] JuMP v1.25.0
  [d9ec5142] NamedTupleTools v0.14.3
  [bac558e1] OrderedCollections v1.8.0
  [ae029012] Requires v1.3.1
  [e88e6eb3] Zygote v0.7.6
  [37e2e46d] LinearAlgebra v1.11.0
  [2f01184e] SparseArrays v1.11.0
  [8dfed614] Test v1.11.0
      Status `/tmp/jl_hGnXqS/Manifest.toml`
  [621f4979] AbstractFFTs v1.5.0
  [79e6a3ab] Adapt v4.3.0
  [6e4b80f9] BenchmarkTools v1.6.0
  [082447d4] ChainRules v1.72.3
  [d360d2e6] ChainRulesCore v1.25.1
  [523fee87] CodecBzip2 v0.8.5
  [944b1d66] CodecZlib v0.7.8
  [bbf7d656] CommonSubexpressions v0.3.1
  [34da2185] Compat v4.16.0
  [187b0558] ConstructionBase v1.5.8
  [9a962f9c] DataAPI v1.16.0
  [864edb3b] DataStructures v0.18.22
  [e2d170a0] DataValueInterfaces v1.0.0
  [163ba53b] DiffResults v1.1.0
  [b552c78f] DiffRules v1.15.1
  [c78775a3] DifferentiableFlatten v0.1.1
  [ffbed154] DocStringExtensions v0.9.4
  [1a297f60] FillArrays v1.13.0
  [f6369f11] ForwardDiff v1.0.1
  [46192b85] GPUArraysCore v0.2.0
  [7869d1d1] IRTools v0.4.14
  [92d709cd] IrrationalConstants v0.2.4
  [82899510] IteratorInterfaceExtensions v1.0.0
  [692b3bcd] JLLWrappers v1.7.0
  [682c06a0] JSON v0.21.4
  [0f8b85d8] JSON3 v1.14.2
  [4076af6c] JuMP v1.25.0
  [2ab3a3ac] LogExpFunctions v0.3.29
  [1914dd2f] MacroTools v0.5.15
  [b8f27783] MathOptInterface v1.38.1
  [d8a4904e] MutableArithmetics v1.6.4
  [77ba4419] NaNMath v1.1.3
  [d9ec5142] NamedTupleTools v0.14.3
  [bac558e1] OrderedCollections v1.8.0
  [69de0a69] Parsers v2.8.1
⌅ [aea7be01] PrecompileTools v1.2.1
  [21216c6a] Preferences v1.4.3
  [c1ae055f] RealDot v0.1.0
  [ae029012] Requires v1.3.1
  [dc90abb0] SparseInverseSubset v0.1.2
  [276daf66] SpecialFunctions v2.5.0
  [1e83bf80] StaticArraysCore v1.4.3
  [10745b16] Statistics v1.11.1
  [09ab397b] StructArrays v0.7.1
  [856f2bd8] StructTypes v1.11.0
  [3783bdb8] TableTraits v1.0.1
  [bd369af6] Tables v1.12.0
  [3bb67fe8] TranscodingStreams v0.11.3
  [e88e6eb3] Zygote v0.7.6
  [700de1a5] ZygoteRules v0.2.7
  [6e34b625] Bzip2_jll v1.0.9+0
  [efe28fd5] OpenSpecFun_jll v0.5.6+0
  [56f22d72] Artifacts v1.11.0
  [2a0f44e3] Base64 v1.11.0
  [ade2ca70] Dates v1.11.0
  [8ba89e20] Distributed v1.11.0
  [b77e0a4c] InteractiveUtils v1.11.0
  [8f399da3] Libdl v1.11.0
  [37e2e46d] LinearAlgebra v1.11.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [a63ad114] Mmap v1.11.0
  [de0858da] Printf v1.11.0
  [9abbd945] Profile v1.11.0
  [9a3f8284] Random v1.11.0
  [ea8e919c] SHA v0.7.0
  [9e88b42a] Serialization v1.11.0
  [6462fe0b] Sockets v1.11.0
  [2f01184e] SparseArrays v1.11.0
  [4607b0f0] SuiteSparse
  [fa267f1f] TOML v1.0.3
  [8dfed614] Test v1.11.0
  [cf7118a7] UUIDs v1.11.0
  [4ec0a83e] Unicode v1.11.0
  [e66e0078] CompilerSupportLibraries_jll v1.1.1+0
  [4536629a] OpenBLAS_jll v0.3.27+1
  [05823500] OpenLibm_jll v0.8.5+0
  [bea87d4a] SuiteSparse_jll v7.7.0+0
  [83775a58] Zlib_jll v1.2.13+1
  [8e850b90] libblastrampoline_jll v5.11.0+0
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading.
     Testing Running tests...
Precompiling LogExpFunctionsChainRulesCoreExt...
   3183.5 ms  ✓ LogExpFunctions → LogExpFunctionsChainRulesCoreExt
  1 dependency successfully precompiled in 4 seconds. 11 already precompiled.
Precompiling SpecialFunctionsChainRulesCoreExt...
   4281.3 ms  ✓ SpecialFunctions → SpecialFunctionsChainRulesCoreExt
  1 dependency successfully precompiled in 4 seconds. 18 already precompiled.
Precompiling Zygote...
   2462.5 ms  ✓ ZygoteRules
  13007.2 ms  ✓ ChainRules
  65216.5 ms  ✓ Zygote
  3 dependencies successfully precompiled in 81 seconds. 62 already precompiled.
┌ Warning: Axis contains one element: 1. If intended, you can safely ignore this warning. To explicitly pass the axis with one element, pass `[1]` instead of `1`.
└ @ JuMP.Containers ~/.julia/packages/JuMP/RGIK3/src/Containers/DenseAxisArray.jl:185
x = 1.0
DifferentiableFlatten._zero(x) = 0.0
x = [1.0]
DifferentiableFlatten._zero(x) = [0.0]
x = [1.0, 2.0]
DifferentiableFlatten._zero(x) = [0.0, 0.0]
x = Any[1.0, [1.0, 2.0]]
DifferentiableFlatten._zero(x) = Any[0.0, [0.0, 0.0]]
x = Any[1.0, (1.0, 2.0)]
DifferentiableFlatten._zero(x) = Any[0.0, (0.0, 0.0)]
x = Any[1.0, OrderedDict(1 => [1.0, 2.0])]
DifferentiableFlatten._zero(x) = Any[0.0, Dict(1 => [0.0, 0.0])]
x = Any[[1.0], OrderedDict(1 => [1.0, 2.0])]
DifferentiableFlatten._zero(x) = Any[[0.0], Dict(1 => [0.0, 0.0])]
x = Any[(1.0,), [1.0], OrderedDict(1 => [1.0, 2.0])]
DifferentiableFlatten._zero(x) = Any[(0.0,), [0.0], Dict(1 => [0.0, 0.0])]
x = [1.0 1.0; 1.0 1.0]
DifferentiableFlatten._zero(x) = [0.0 0.0; 0.0 0.0]
x = [0.671113727353506 0.41319327708519793; 0.6012869465498808 0.6006275893606459;;; 0.6469604243223988 0.1371036405341005; 0.7166598114527072 0.11978223560471124]
DifferentiableFlatten._zero(x) = [0.0 0.0; 0.0 0.0;;; 0.0 0.0; 0.0 0.0]
x = [[1.0, 2.0], [3.0, 4.0]]
DifferentiableFlatten._zero(x) = [[0.0, 0.0], [0.0, 0.0]]
x = OrderedDict(1 => 1.0)
DifferentiableFlatten._zero(x) = Dict(1 => 0.0)
x = OrderedDict(1 => [1.0])
DifferentiableFlatten._zero(x) = Dict(1 => [0.0])
x = OrderedDict{Int64, Any}(1 => 1.0, 2 => [2.0])
DifferentiableFlatten._zero(x) = Dict{Int64, Any}(2 => [0.0], 1 => 0.0)
x = OrderedDict{Int64, Any}(1 => 1.0, 2 => [2.0], 3 => [[1.0, 2.0], [3.0, 4.0]])
DifferentiableFlatten._zero(x) = Dict{Int64, Any}(2 => [0.0], 3 => [[0.0, 0.0], [0.0, 0.0]], 1 => 0.0)
x = 1-dimensional DenseAxisArray{Float64,1,...} with index sets:
    Dimension 1, [1]
And data, a 2-element Vector{Float64}:
 1.0
 1.0
DifferentiableFlatten._zero(x) = 1-dimensional DenseAxisArray{Float64,1,...} with index sets:
    Dimension 1, [1]
And data, a 2-element Vector{Float64}:
 0.0
 0.0
x = (1.0,)
DifferentiableFlatten._zero(x) = (0.0,)
x = (1.0, 2.0)
DifferentiableFlatten._zero(x) = (0.0, 0.0)
x = (1.0, (1.0, 2.0))
DifferentiableFlatten._zero(x) = (0.0, (0.0, 0.0))
x = (1.0, [1.0, 2.0])
DifferentiableFlatten._zero(x) = (0.0, [0.0, 0.0])
x = (1.0, OrderedDict(1 => [1.0, 2.0]))
DifferentiableFlatten._zero(x) = (0.0, Dict(1 => [0.0, 0.0]))
x = ([1.0], OrderedDict(1 => [1.0, 2.0]))
DifferentiableFlatten._zero(x) = ([0.0], Dict(1 => [0.0, 0.0]))
x = ((1.0,), [1.0], OrderedDict(1 => [1.0, 2.0]))
DifferentiableFlatten._zero(x) = ((0.0,), [0.0], Dict(1 => [0.0, 0.0]))
x = (a = 1.0,)
DifferentiableFlatten._zero(x) = (a = 0.0,)
x = (a = 1.0, b = 2.0)
DifferentiableFlatten._zero(x) = (a = 0.0, b = 0.0)
x = (a = 1.0, b = (1.0, 2.0))
DifferentiableFlatten._zero(x) = (a = 0.0, b = (0.0, 0.0))
x = (a = 1.0, b = [1.0, 2.0])
DifferentiableFlatten._zero(x) = (a = 0.0, b = [0.0, 0.0])
x = (a = 1.0, b = OrderedDict(1 => [1.0, 2.0]))
DifferentiableFlatten._zero(x) = (a = 0.0, b = Dict(1 => [0.0, 0.0]))
x = (a = [1.0], b = OrderedDict(1 => [1.0, 2.0]))
DifferentiableFlatten._zero(x) = (a = [0.0], b = Dict(1 => [0.0, 0.0]))
x = (a = (1.0,), b = [1.0], c = OrderedDict(1 => [1.0, 2.0]))
DifferentiableFlatten._zero(x) = (a = (0.0,), b = [0.0], c = Dict(1 => [0.0, 0.0]))
x = sparsevec([1, 2], [1, 3], 10)
DifferentiableFlatten._zero(x) = sparsevec(Int64[], Int64[], 10)
x = sparse([2, 1, 2, 3], [1, 2, 3, 4], [3.0, 1.0, 2.0, 4.0], 10, 10)
DifferentiableFlatten._zero(x) = sparse(Int64[], Int64[], Float64[], 10, 10)
x = SS(1.0, 2.0)
DifferentiableFlatten._zero(x) = SS(0.0, 0.0)
x = Any[SS(1.0, 2.0), 1.0]
DifferentiableFlatten._zero(x) = Any[SS(0.0, 0.0), 0.0]
x = MyStruct{Float64, Float64, Float64}(1.0, 1.0)
DifferentiableFlatten._zero(x) = MyStruct{Float64, Float64, Float64}(0.0, 0.0)
┌ Warning: Axis contains one element: 1. If intended, you can safely ignore this warning. To explicitly pass the axis with one element, pass `[1]` instead of `1`.
└ @ JuMP.Containers ~/.julia/packages/JuMP/RGIK3/src/Containers/DenseAxisArray.jl:185
Test Summary:            | Pass  Total     Time
DifferentiableFlatten.jl |  227    227  3m57.2s
     Testing DifferentiableFlatten tests passed 

Testing completed after 341.71s

PkgEval succeeded after 378.23s