[Debian-pan-maintainers] Bug#1118519: opentsne: autopkgtest regression on some architectures with scikit 1.7.2

[Timo Röhling]

Source: opentsne
Version: 1.0.2-4
Severity: serious
X-Debbugs-Cc: debian-arm at lists.debian.org, debian-riscv at lists.debian.org, debian-s390 at lists.debian.org
User: debian-arm at lists.debian.org
Usertags: arm64
User: debian-riscv at lists.debian.org
Usertags: riscv64
User: debian-s390 at lists.debian.org
Usertags: s390x
User: debian-science at lists.debian.org
Usertags: scikit-learn-1.7

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Dear maintainer,

your package has an autopkgtest regression with sckit-learn 1.7.2. I'm 
quoting the arm64 [1] error below, but it is the same failing test on 
risc64 [2] and s390x [3] as well:

[1] https://ci.debian.net/packages/o/opentsne/testing/arm64/65339152/
[2] https://ci.debian.net/packages/o/opentsne/testing/riscv64/65333862/
[3] https://ci.debian.net/packages/o/opentsne/testing/s390x/65330911/


220s =================================== FAILURES ===================================
220s _________ TestTSNECorrectnessUsingPrecomputedDistanceMatrix.test_iris __________
220s
220s self = <tests.test_correctness.TestTSNECorrectnessUsingPrecomputedDistanceMatrix testMethod=test_iris>
220s
220s     @unittest.skipIf(('i686' in machine) or machine == 'i386'
220s                        or machine == 'ppc64le',
220s                      reason=f"Skipping test on {machine} architecture")
220s     def test_iris(self):
220s         x = datasets.load_iris().data
220s         print(platform.machine())
220s         x += np.random.normal(0, 1e-3, x.shape)  # iris contains duplicate rows
220s
220s         distances = squareform(pdist(x))
220s         params = dict(initialization="random", random_state=0)
220s         embedding1 = TSNE(metric="precomputed", **params).fit(distances)
220s         embedding2 = TSNE(metric="euclidean", **params).fit(x)
220s
220s >       np.testing.assert_almost_equal(embedding1, embedding2)
220s E       AssertionError:
220s E       Arrays are not almost equal to 7 decimals
220s E
220s E       Mismatched elements: 300 / 300 (100%)
220s E       Max absolute difference among violations: 4.85427071
220s E       Max relative difference among violations: 47.91193852
220s E        ACTUAL: TSNEEmbedding([[ 11.855024 ,  15.4978719],
220s E                      [ 11.7985732,  12.7515209],
220s E                      [ 12.8316039,  13.2288263],...
220s E        DESIRED: TSNEEmbedding([[ 13.8717067,  11.1420085],
220s E                      [ 14.6164783,   8.511387 ],
220s E                      [ 15.4360712,   9.2738073],...
220s
220s tests/test_correctness.py:307: AssertionError


Cheers
Timo

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