scikit-learn 1.1.2+dfsg-6 fails autopkgtest on armhf, which appears to have started around 1.1.2+dfsg-3. The previous version, 0.23.x, was passing reliably.
This issue seems not to have a bug report in Debian, however bus errors are mentioned on both Deb: #1008369 and #1003165. Both bugs have extensive discussion, however it's unclear if a fix is in sight; main suggestions appear to be to drop the architecture or skip the test case.
"""
The new version of scikit-learn has a bus error in one of its
autopkgtests on armhf. This was allowed to regress in Debian during a
numpy transition almost a year ago. I'm not sure whether it is worth
the time to try to fix this, or simply skip the failing test.
"""
[Test Log]
> ../../../usr/lib/python3/dist-packages/sklearn/metrics/tests/test_dist_metrics.py::test_cdist[X10-X20-metric_param_grid9] PASSED
> ../../../usr/lib/python3/dist-packages/sklearn/metrics/tests/test_dist_metrics.py::test_cdist[X11-X21-metric_param_grid0] Fatal Python error: Bus error
>
> Current thread 0xf7cda020 (most recent call first):
> File "/usr/lib/python3/dist-packages/sklearn/metrics/tests/test_dist_metrics.py", line 80 in check_cdist
> File "/usr/lib/python3/dist-packages/sklearn/metrics/tests/test_dist_metrics.py", line 99 in test_cdist
> File "/usr/lib/python3/dist-packages/_pytest/python.py", line 192 in pytest_pyfunc_call
> File "/usr/lib/python3/dist-packages/pluggy/_callers.py", line 39 in _multicall
> File "/usr/lib/python3/dist-packages/pluggy/_manager.py", line 80 in _hookexec
> File "/usr/lib/python3/dist-packages/pluggy/_hooks.py", line 265 in __call__
> File "/usr/lib/python3/dist-packages/_pytest/python.py", line 1761 in runtest
> File "/usr/lib/python3/dist-packages/_pytest/runner.py", line 166 in pytest_runtest_call
> File "/usr/lib/python3/dist-packages/pluggy/_callers.py", line 39 in _multicall
> File "/usr/lib/python3/dist-packages/pluggy/_manager.py", line 80 in _hookexec
> File "/usr/lib/python3/dist-packages/pluggy/_hooks.py", line 265 in __call__
> File "/usr/lib/python3/dist-packages/_pytest/runner.py", line 259 in <lambda>
> File "/usr/lib/python3/dist-packages/_pytest/runner.py", line 338 in from_call
> File "/usr/lib/python3/dist-packages/_pytest/runner.py", line 258 in call_runtest_hook
> File "/usr/lib/python3/dist-packages/_pytest/runner.py", line 219 in call_and_report
> File "/usr/lib/python3/dist-packages/_pytest/runner.py", line 130 in runtestprotocol
> File "/usr/lib/python3/dist-packages/_pytest/runner.py", line 111 in pytest_runtest_protocol
> File "/usr/lib/python3/dist-packages/pluggy/_callers.py", line 39 in _multicall
> File "/usr/lib/python3/dist-packages/pluggy/_manager.py", line 80 in _hookexec
> File "/usr/lib/python3/dist-packages/pluggy/_hooks.py", line 265 in __call__
> File "/usr/lib/python3/dist-packages/_pytest/main.py", line 347 in pytest_runtestloop
> File "/usr/lib/python3/dist-packages/pluggy/_callers.py", line 39 in _multicall
> File "/usr/lib/python3/dist-packages/pluggy/_manager.py", line 80 in _hookexec
> File "/usr/lib/python3/dist-packages/pluggy/_hooks.py", line 265 in __call__
> File "/usr/lib/python3/dist-packages/_pytest/main.py", line 322 in _main
> File "/usr/lib/python3/dist-packages/_pytest/main.py", line 268 in wrap_session
> File "/usr/lib/python3/dist-packages/_pytest/main.py", line 315 in pytest_cmdline_main
> File "/usr/lib/python3/dist-packages/pluggy/_callers.py", line 39 in _multicall
> File "/usr/lib/python3/dist-packages/pluggy/_manager.py", line 80 in _hookexec
> File "/usr/lib/python3/dist-packages/pluggy/_hooks.py", line 265 in __call__
> File "/usr/lib/python3/dist-packages/_pytest/config/__init__.py", line 164 in main
> File "/usr/lib/python3/dist-packages/_pytest/config/__init__.py", line 187 in console_main
> File "/usr/lib/python3/dist-packages/pytest/__main__.py", line 5 in <module>
> File "/usr/lib/python3.10/runpy.py", line 86 in _run_code
> File "/usr/lib/python3.10/runpy.py", line 196 in _run_module_as_main
>
> Extension modules: sklearn.__check_build._check_build, numpy.core._multiarray_umath, numpy.core._multiarray_tests, numpy.linalg.lapack_lite, numpy.linalg._umath_linalg, numpy.fft._pocketfft_internal, numpy.random._common, numpy.random.bit_generator, numpy.random._bounded_integers, numpy.random._mt19937, numpy.random.mtrand, numpy.random._philox, numpy.random._pcg64, numpy.random._sfc64, numpy.random._generator, scipy._lib._ccallback_c, scipy.sparse._sparsetools, scipy.sparse._csparsetools, scipy.sparse.csgraph._tools, scipy.sparse.csgraph._shortest_path, scipy.sparse.csgraph._traversal, scipy.sparse.csgraph._min_spanning_tree, scipy.sparse.csgraph._flow, scipy.sparse.csgraph._matching, scipy.sparse.csgraph._reordering, sklearn.utils.murmurhash, lz4._version, lz4.frame._frame, scipy.spatial._ckdtree, scipy._lib.messagestream, scipy.spatial._qhull, scipy.spatial._voronoi, scipy.linalg._fblas, scipy.linalg._flapack, scipy.linalg._cythonized_array_utils, scipy.linalg._flinalg, scipy.linalg._solve_toeplitz, scipy.linalg._matfuncs_sqrtm_triu, scipy.linalg.cython_blas, scipy.linalg.cython_lapack, scipy.linalg._decomp_update, scipy.spatial._distance_wrap, scipy.spatial._hausdorff, scipy.special._ufuncs_cxx, scipy.special._ufuncs, scipy.special._specfun, scipy.special._comb, scipy.special._ellip_harm_2, scipy.spatial.transform._rotation, scipy.ndimage._nd_image, _ni_label, scipy.ndimage._ni_label, scipy.sparse.linalg._isolve._iterative, scipy.sparse.linalg._dsolve._superlu, scipy.sparse.linalg._eigen.arpack._arpack, scipy.optimize._minpack2, scipy.optimize._group_columns, scipy.optimize._trlib._trlib, scipy.optimize._lbfgsb, _moduleTNC, scipy.optimize._moduleTNC, scipy.optimize._cobyla, scipy.optimize._slsqp, scipy.optimize._minpack, scipy.optimize._lsq.givens_elimination, scipy.optimize._zeros, scipy.optimize.__nnls, scipy.optimize._highs.cython.src._highs_wrapper, scipy.optimize._highs._highs_wrapper, scipy.optimize._highs.cython.src._highs_constants, scipy.optimize._highs._highs_constants, scipy.linalg._interpolative, scipy.optimize._bglu_dense, scipy.optimize._lsap_module, scipy.integrate._odepack, scipy.integrate._quadpack, scipy.integrate._vode, scipy.integrate._dop, scipy.integrate._lsoda, scipy.interpolate._fitpack, scipy.interpolate.dfitpack, scipy.interpolate._bspl, scipy.interpolate._ppoly, scipy.interpolate.interpnd, scipy.special.cython_special, scipy.stats._stats, beta_ufunc, scipy.stats._boost.beta_ufunc, binom_ufunc, scipy.stats._boost.binom_ufunc, nbinom_ufunc, scipy.stats._boost.nbinom_ufunc, hypergeom_ufunc, scipy.stats._boost.hypergeom_ufunc, scipy.stats._biasedurn, scipy.stats._statlib, scipy.stats._mvn, scipy.stats._sobol, scipy.stats._qmc_cy, scipy.stats._unuran.unuran_wrapper, sklearn.utils._openmp_helpers, sklearn.utils._logistic_sigmoid, sklearn.utils.sparsefuncs_fast, sklearn.preprocessing._csr_polynomial_expansion, sklearn.utils._vector_sentinel, sklearn.feature_extraction._hashing_fast, sklearn.utils._random, sklearn.datasets._svmlight_format_fast, scipy.io.matlab._mio_utils, scipy.io.matlab._streams, scipy.io.matlab._mio5_utils, matplotlib._c_internal_utils, PIL._imaging, matplotlib._path, kiwisolver, sklearn._loss._loss, sklearn.utils._readonly_array_wrapper, sklearn.utils._typedefs, sklearn.metrics._dist_metrics, sklearn.metrics.cluster._expected_mutual_info_fast, sklearn.utils._cython_blas, sklearn.utils._heap, sklearn.utils._sorting, sklearn.metrics._pairwise_distances_reduction, sklearn.metrics._pairwise_fast, sklearn.neighbors._partition_nodes, sklearn.neighbors._ball_tree, sklearn.neighbors._kd_tree, sklearn.decomposition._cdnmf_fast, sklearn.utils._seq_dataset, sklearn.utils.arrayfuncs, sklearn.linear_model._cd_fast, sklearn.utils._weight_vector, sklearn.linear_model._sgd_fast, sklearn.linear_model._sag_fast, sklearn.svm._libsvm, sklearn.svm._liblinear, sklearn.svm._libsvm_sparse, sklearn.decomposition._online_lda_fast, sklearn._isotonic, sklearn.manifold._utils, sklearn.tree._utils, sklearn.tree._tree, sklearn.tree._splitter, sklearn.tree._criterion, sklearn.neighbors._quad_tree, sklearn.manifold._barnes_hut_tsne, sklearn.cluster._k_means_common, sklearn.cluster._k_means_minibatch, sklearn.cluster._k_means_lloyd, sklearn.cluster._k_means_elkan, sklearn.utils._fast_dict, sklearn.cluster._hierarchical_fast, sklearn.cluster._dbscan_inner, scipy.cluster._vq, scipy.cluster._hierarchy, scipy.cluster._optimal_leaf_ordering, sklearn.ensemble._gradient_boosting, sklearn.ensemble._hist_gradient_boosting.common, sklearn.ensemble._hist_gradient_boosting._gradient_boosting, sklearn.ensemble._hist_gradient_boosting._binning, sklearn.ensemble._hist_gradient_boosting._bitset, sklearn.ensemble._hist_gradient_boosting.splitting, sklearn.ensemble._hist_gradient_boosting.histogram, sklearn.ensemble._hist_gradient_boosting._predictor, sklearn.ensemble._hist_gradient_boosting.utils, scipy._lib._uarray._uarray, sklearn.svm._newrand, matplotlib._image (total: 169)
> Bus error (core dumped)
> autopkgtest [08:04:45]: test python3: -----------------------]
I wonder if this gets better by setting the parameter aligned=True?
def create_
https:/
Maybe just change this *here*; False feels like a *very* silly default. x86 can cope with unaligned by going VERY SLOW. arm64 when emulating armhf tends to just SIGBUS and tell you not to do that. I don't know any other architectures, but unaligned is usually bad news.
Thanks