Summary

Bugs of task machine-learning

Total bugs: 31

Open bugs: 27

Fixed bugs: 4

Links to other tasks

Tasks overview

Coherent-diffraction 0 (0)

Control-systems 21 (210)

Control-systems-dev 21 (210)

Data-reduction-frameworks 300 (2700)

Data-reduction-frameworks-dev 4 (42)

Diffraction 22 (192)

Grazing-incidence 4 (36)

Imaging 228 (1817)

Laue 0 (0)

Machine-learning 27 (293)

Modelling 7 (60)

Mx 86 (640)

Mx-dev 2 (10)

Powder 12 (108)

Small-angle-scattering 14 (132)

Spectroscopy 12 (120)

Tomography 47 (389)

Xas 9 (63)

Legend

Severity	Dependent	Suggested
critical	0	0
grave	0	0
serious	0	0
important	15	1
normal	7	0
minor	0	0
wishlist	4	0

Summary bugs page of task Machine-learning

Immediately looking into bugs of the dependencies of this task is advised (293)^*

Open bugs in dependent packages

15 important, 7 normal, 4 wishlist

keras-applications (1) Homepage: https://keras.io/ Vcs Debian Science Maintainers
971478	keras-applications: autopkgtest must be marked superficial
mdp (2) Homepage: https://mdp-toolkit.github.io/ Vcs Debian Python Team
1007813	Newer LIBSVM breaks mdp
1085687	mdp: Python SyntaxWarning
opencv (2) Homepage: https://opencv.org Vcs Debian Science Team
989958	libopencv-*-dev: Missing pkg-config file (.pc)	upstream, wontfix
1100979	python3-opencv: please provide typing stubs
python-pyclustering (3) Homepage: https://github.com/annoviko/pyclustering Vcs Debian Science Maintainers
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
pytorch (14) Homepage: https://pytorch.org/ Vcs Debian Deep Learning Team
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
scikit-learn (4) Homepage: https://scikit-learn.org Vcs Debian Science Maintainers
1064280	scikit-learn: armhf tests failing: not giving expected divide-by-zero warning
1074234	scikit-learn: CVE-2024-5206	security, upstream
1088436	scikit-learn: move from twitter-bootstrap{3,4} to bootstrap-html (v5)	upstream
1088593	python-sklearn-doc: move from twitter-bootstrap{3,4} to bootstrap-html (v5)	upstream

Open bugs in suggested packages

1 important

pytorch-cuda (1) Homepage: https://pytorch.org/ Vcs Debian Deep Learning Team
1086774	Please drop dependency on python3-astunparse

Done bugs

pytorch (1) Homepage: https://pytorch.org/ Vcs Debian Deep Learning Team
994423	pytorch: Baseline violation on armhf	bookworm, bullseye, experimental, ftbfs, sid, trixie
pytorch-cuda (1) Homepage: https://pytorch.org/ Vcs Debian Deep Learning Team
1105066	pytorch-cuda: FTBFS: ld.lld: error: undefined reference: std::ios_base_library_init()@GLIBCXX_3.4.32	ftbfs, sid, trixie
scikit-learn (2) Homepage: https://scikit-learn.org Vcs Debian Science Maintainers
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
1029701	scikit-learn: tests fail with scipy 1.10	fixed-upstream

^*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:

critical	10
grave	10
serious	10
important	5
normal	3
minor	1
wishlist	0