PAN Blend Project
Summary
Bugs of task machine-learning
Total bugs: 50
Open bugs: 41
Fixed bugs: 9
Links to other tasks
Control-systems 21 (240)
Diffraction 21 (198)
Imaging 232 (1916)
Laue 0 (0)
Machine-learning 41 (485)
Modelling 13 (141)
Mx 87 (712)
Mx-dev 1 (5)
Powder 12 (123)
Spectroscopy 12 (135)
Tomography 43 (419)
Xas 9 (78)
Legend
SeverityDependentSuggested
critical 0 0
grave 0 0
serious 0 0
important 28 1
normal 6 0
minor 2 0
wishlist 4 0

Summary bugs page of task Machine-learning

Immediately looking into bugs of the dependencies of this task is advised (485)*

Open bugs in dependent packages

28 important, 6 normal, 2 minor, 4 wishlist
971478 keras-applications: autopkgtest must be marked superficial
1116268 python3-keras-applications: recommends python3-keras which is not in unstable
1116269 python3-keras-preprocessing: recommends python3-keras which is not in unstable
1007813 Newer LIBSVM breaks mdp
1085687 mdp: Python SyntaxWarning
1116832 onnx: FTBFS with the nocheck build profile forky, ftbfs, sid
989958 libopencv-*-dev: Missing pkg-config file (.pc) upstream, wontfix
1100979 python3-opencv: please provide typing stubs
1115048 opencv: FTBFS with ffmpeg 8.0 forky, ftbfs, help, sid
1035220 python-pyclustering: please add autopkgtests (to add coverage for python3-numpy)
1036493 python-pyclustering: please add autopkgtests (to add coverage for python3-matplotlib)
1086924 python-pyclustering: Python SyntaxWarning
983517 pytorch: Build documentation
1057644 pytorch: build for all supported Python versions wontfix
1102203 pytorch: CVE-2025-3136 security, upstream
1102219 pytorch: CVE-2025-2148 security, upstream
1102220 pytorch: CVE-2025-2149 security, upstream
1102229 pytorch: CVE-2025-2953 fixed-upstream, security, upstream
1102230 pytorch: CVE-2025-2998 security, upstream
1102231 pytorch: CVE-2025-2999 security, upstream
1102232 pytorch: CVE-2025-3000 security, upstream
1102233 pytorch: CVE-2025-3001 security, upstream
1102236 pytorch: CVE-2025-3121 security, upstream
1103455 pytorch: CVE-2025-3730 fixed-upstream, security, upstream
1104931 pytorch: CVE-2025-4287 security, upstream
1108733 RuntimeError: operator torchvision::nms does not exist
1116531 pytorch: CVE-2025-55560 fixed-upstream, security, upstream
1116532 pytorch: CVE-2025-55558 fixed-upstream, security, upstream
1116533 pytorch: CVE-2025-55557 fixed-upstream, security, upstream
1116534 pytorch: CVE-2025-55554 security, upstream
1116535 pytorch: CVE-2025-55553 fixed-upstream, security, upstream
1116536 pytorch: CVE-2025-55552 security, upstream
1116537 pytorch: CVE-2025-55551 security, upstream
1116538 pytorch: CVE-2025-46153 fixed-upstream, security, upstream
1116539 pytorch: CVE-2025-46152 fixed-upstream, security, upstream
1116540 pytorch: CVE-2025-46150 fixed-upstream, security, upstream
1116541 pytorch: CVE-2025-46149 fixed-upstream, security, upstream
1116543 pytorch: CVE-2025-46148 fixed-upstream, security, upstream
1064280 scikit-learn: armhf tests failing: not giving expected divide-by-zero warning
1088436 scikit-learn: move from twitter-bootstrap{3,4} to bootstrap-html (v5) upstream

Open bugs in suggested packages

1 important
1086774 Please drop dependency on python3-astunparse

Done bugs

1114696 brian: FTBFS with NumPy 2.3 forky, ftbfs, sid
1113355 opencv: FTBFS with CMake 4 forky, ftbfs, sid
1116253 opencv fails to build on ppc64el forky, ftbfs, patch, sid
1113436 pytorch: FTBFS with CMake 4 forky, ftbfs, sid
1115701 pytorch: FTBFS: ProcessGroupGloo.cpp:792:76: error: no matching function for call to ‘gloo::rendezvous::PrefixStore::PrefixStore(std::string, gloo::rendezvous::Store&)’ forky, ftbfs, sid
1008369 scikit-learn: FTBFS: dh_auto_test: error: pybuild --test -i python{version} -p "3.10 3.9" returned exit code 13 bookworm, ftbfs, moreinfo, sid, trixie, unreproducible
1074234 scikit-learn: CVE-2024-5206 security, upstream
1088593 python-sklearn-doc: move from twitter-bootstrap{3,4} to bootstrap-html (v5) upstream
1109955 scikit-learn: deprecated API fails with scipy 1.16 fixed-upstream, forky, sid
*To estimate the overall status of the packages in the dependencies of a metapackage a weighted severity is calculated. Done bugs are ignored and bugs in dependent and recommended packages are weighted by factor three compared to suggested packages. Release critical bugs have a much larger weight than important, while the contribution of normal bugs is even smaller and minor bugs have a very small weight. Wishlist bugs are ignored in this calculation. The resulting sum is compared to some boundaries to find a verbal form. The actual numbers need some adjustment to make real sense - this evaluation method is in testing phase.
The severities of bugs are weighted as follows:
critical10
grave10
serious10
important5
normal3
minor1
wishlist0
Last update: Mon, 13 Oct 2025 15:55:44 -0000