scikit-learn tests segfault on armel

### Describe the bug

Hi,

scikit-learn version 1.1.1 seems to segfault on armel architecture. Full build log [here](https://buildd.debian.org/status/fetch.php?pkg=scikit-learn&arch=armel&ver=1.1.1-1&stamp=1653343638&raw=0)

### Steps/Code to Reproduce

Normally running testsuite on armel

### Expected Results

No error is shown

### Actual Results


```
sklearn/decomposition/tests/test_sparse_pca.py::test_transform_nan Fatal Python error: Segmentation fault

Thread 0xa52ff3e0 (most recent call first):
  File "/usr/lib/python3.10/threading.py", line 320 in wait
  File "/usr/lib/python3/dist-packages/joblib/externals/loky/backend/queues.py", line 141 in _feed
  File "/usr/lib/python3.10/threading.py", line 946 in run
  File "/usr/lib/python3.10/threading.py", line 1009 in _bootstrap_inner
  File "/usr/lib/python3.10/threading.py", line 966 in _bootstrap

Thread 0xa3eff3e0 (most recent call first):
  File "/usr/lib/python3.10/selectors.py", line 416 in select
  File "/usr/lib/python3.10/multiprocessing/connection.py", line 936 in wait
  File "/usr/lib/python3/dist-packages/joblib/externals/loky/process_executor.py", line 609 in wait_result_broken_or_wakeup
  File "/usr/lib/python3/dist-packages/joblib/externals/loky/process_executor.py", line 555 in run
  File "/usr/lib/python3.10/threading.py", line 1009 in _bootstrap_inner
  File "/usr/lib/python3.10/threading.py", line 966 in _bootstrap

Current thread 0xb6f0a540 (most recent call first):
  File "/usr/lib/python3/dist-packages/scipy/linalg/decomp_svd.py", line 127 in svd
  File "/<<PKGBUILDDIR>>/.pybuild/cpython3_3.10/build/sklearn/decomposition/_dict_learning.py", line 639 in dict_learning
  File "/<<PKGBUILDDIR>>/.pybuild/cpython3_3.10/build/sklearn/decomposition/_sparse_pca.py", line 186 in fit
  File "/<<PKGBUILDDIR>>/.pybuild/cpython3_3.10/build/sklearn/base.py", line 867 in fit_transform
  File "/<<PKGBUILDDIR>>/.pybuild/cpython3_3.10/build/sklearn/decomposition/tests/test_sparse_pca.py", line 95 in test_transform_nan
  File "/usr/lib/python3/dist-packages/_pytest/python.py", line 183 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 1641 in runtest
  File "/usr/lib/python3/dist-packages/_pytest/runner.py", line 162 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 255 in <lambda>
  File "/usr/lib/python3/dist-packages/_pytest/runner.py", line 311 in from_call
  File "/usr/lib/python3/dist-packages/_pytest/runner.py", line 254 in call_runtest_hook
  File "/usr/lib/python3/dist-packages/_pytest/runner.py", line 215 in call_and_report
  File "/usr/lib/python3/dist-packages/_pytest/runner.py", line 126 in runtestprotocol
  File "/usr/lib/python3/dist-packages/_pytest/runner.py", line 109 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 348 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 323 in _main
  File "/usr/lib/python3/dist-packages/_pytest/main.py", line 269 in wrap_session
  File "/usr/lib/python3/dist-packages/_pytest/main.py", line 316 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 162 in main
  File "/usr/lib/python3/dist-packages/_pytest/config/__init__.py", line 185 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._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.optimize.minpack2, scipy.sparse.linalg.isolve._iterative, scipy.sparse.linalg.dsolve._superlu, scipy.sparse.linalg.eigen.arpack._arpack, scipy.optimize._group_columns, scipy.optimize._trlib._trlib, scipy.optimize._lbfgsb, 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, scipy.stats.biasedurn, scipy.stats.statlib, scipy.stats.mvn, scipy.stats._sobol, scipy.stats._qmc_cy, 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._isotonic, sklearn.utils._cython_blas, sklearn.svm._libsvm, sklearn.svm._liblinear, sklearn.svm._libsvm_sparse, sklearn.utils._seq_dataset, sklearn.utils.arrayfuncs, sklearn.utils._typedefs, sklearn.utils._readonly_array_wrapper, sklearn.metrics._dist_metrics, sklearn.metrics.cluster._expected_mutual_info_fast, sklearn.utils._heap, sklearn.utils._sorting, sklearn.metrics._pairwise_distances_reduction, sklearn.metrics._pairwise_fast, sklearn.linear_model._cd_fast, sklearn._loss._loss, sklearn.utils._weight_vector, sklearn.linear_model._sgd_fast, sklearn.linear_model._sag_fast, scipy._lib._uarray._uarray, sklearn.neighbors._partition_nodes, sklearn.neighbors._ball_tree, sklearn.neighbors._kd_tree, sklearn.decomposition._cdnmf_fast, sklearn.decomposition._online_lda_fast, 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, sklearn.svm._newrand, pandas._libs.tslibs.dtypes, pandas._libs.tslibs.base, pandas._libs.tslibs.np_datetime, pandas._libs.tslibs.nattype, pandas._libs.tslibs.timezones, pandas._libs.tslibs.ccalendar, pandas._libs.tslibs.tzconversion, pandas._libs.tslibs.strptime, pandas._libs.tslibs.fields, pandas._libs.tslibs.timedeltas, pandas._libs.tslibs.timestamps, pandas._libs.properties, pandas._libs.tslibs.offsets, pandas._libs.tslibs.parsing, pandas._libs.tslibs.conversion, pandas._libs.tslibs.period, pandas._libs.tslibs.vectorized, pandas._libs.ops_dispatch, pandas._libs.missing, pandas._libs.hashtable, pandas._libs.algos, pandas._libs.interval, pandas._libs.tslib, pandas._libs.lib, pandas._libs.hashing, pandas._libs.ops, pandas._libs.arrays, pandas._libs.index, pandas._libs.join, pandas._libs.sparse, pandas._libs.reduction, pandas._libs.indexing, pandas._libs.internals, pandas._libs.writers, pandas._libs.window.aggregations, pandas._libs.window.indexers, pandas._libs.reshape, pandas._libs.groupby, pandas._libs.parsers, pandas._libs.json, pandas._libs.testing (total: 204)
Segmentation fault
```

### Versions

```shell
1.1.1
```

COMMENT:
Hi @nileshpatra, thanks for reaching out and sorry that this issue did not get the attention it deserved.
Luckily (:innocent:), the update to scikit-learn 1.1.2 made `test_transform_nan` pass on armel (see [build log](https://ci.debian.net/data/autopkgtest/testing/armel/s/scikit-learn/27233877/log.gz)).
I am going to close this one.

Labels: Bug, Build / CI