Julia 1.3, 1.4 on MacOS and Intel MKL Error

Internals & Design Internals
4

Looking around it seems MKL throws such issues upon seeing corrupted values (inf, nans…)

Anyway I tried running the tests locally for MLJModels 0.9.1 (latest release) on my machine (a mac without MKL) and they fail as well with:

SpectralClustering: Error During Test at /Users/tlienart/.julia/packages/MLJModels/8gw1p/test/ScikitLearn/clustering.jl:139
  Got exception outside of a @test
  PyError ($(Expr(:escape, :(ccall(#= /Users/tlienart/.julia/packages/PyCall/zqDXB/src/pyfncall.jl:43 =# @pysym(:PyObject_Call), PyPtr, (PyPtr, PyPtr, PyPtr), o, pyargsptr, kw))))) <class 'ValueError'>
  ValueError('array must not contain infs or NaNs')

Later on

BayesianRidge: Test Failed at /Users/tlienart/.julia/packages/MLJModels/8gw1p/test/ScikitLearn/linear-regressors.jl:29
  Expression: isapprox(norm(predict(m, f, X) .- y) / norm(y), 0.0326918, rtol = 1.0e-5)
   Evaluated: isapprox(15.425555763884265, 0.0326918; rtol = 1.0e-5)
Stacktrace:
 [1] top-level scope at /Users/tlienart/.julia/packages/MLJModels/8gw1p/test/ScikitLearn/linear-regressors.jl:29
 [2] top-level scope at /Users/julia/buildbot/worker/package_macos64/build/usr/share/julia/stdlib/v1.5/Test/src/Test.jl:1114
 [3] top-level scope at /Users/tlienart/.julia/packages/MLJModels/8gw1p/test/ScikitLearn/linear-regressors.jl:26

Intel MKL ERROR: Parameter 4 was incorrect on entry to DLASCL.

I don’t think that’s an issue on the Julia’s side.

Edit: ok actually I don’t know, I also tested locally MLJModels 0.8.4 (previous minor release) and it also fails on Julia 1.4 and nightly with similar errors.

Edit2: I’ll try with a compat bound on MKL_jll → well I managed to try with the most recent 2020 one but that also failed. :man_shrugging: