Bug#1082695: marked as done (python-hmmlearn: FTBFS: failing tests)

Debian Bug Tracking System Sat, 05 Oct 2024 03:15:37 -0700

Your message dated Sat, 05 Oct 2024 10:14:04 +0000
with message-id <e1sx1ny-00506v...@fasolo.debian.org>
and subject line Bug#1082695: fixed in python-hmmlearn 0.3.2-1
has caused the Debian Bug report #1082695,
regarding python-hmmlearn: FTBFS: failing tests
to be marked as done.


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-- 
1082695: https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=1082695
Debian Bug Tracking System
Contact ow...@bugs.debian.org with problems

--- Begin Message ---

Package: src:python-hmmlearn
Version: 0.3.0-5
Severity: serious
Tags: ftbfs

Dear maintainer:

During a rebuild of all packages in unstable, your package failed to build:

--------------------------------------------------------------------------------
[...]
 debian/rules binary
dh binary --buildsystem=pybuild
   dh_update_autotools_config -O--buildsystem=pybuild
   dh_autoreconf -O--buildsystem=pybuild
   dh_auto_configure -O--buildsystem=pybuild
   dh_auto_build -O--buildsystem=pybuild
I: pybuild plugin_pyproject:129: Building wheel for python3.12 with "build" 
module
I: pybuild base:311: python3.12 -m build --skip-dependency-check --no-isolation --wheel 
--outdir /<<PKGBUILDDIR>>/.pybuild/cpython3_3.12_hmmlearn
* Building wheel...
WARNING setuptools_scm.pyproject_reading toml section missing 'pyproject.toml 
does not contain a tool.setuptools_scm section'
Traceback (most recent call last):
  File 
"/usr/lib/python3/dist-packages/setuptools_scm/_integration/pyproject_reading.py",
 line 36, in read_pyproject
    section = defn.get("tool", {})[tool_name]
              ~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^

[... snipped ...]

       [-1.23521059],
       [ 2.96221347],
       [-2.4055287 ]])

    def _fit_scaling(self, X):
        frameprob = self._compute_subnorm_likelihood(X)

      logprob, fwdlattice, scaling_factors = _hmmc.forward_scaling(

            self.startprob_subnorm_, self.transmat_subnorm_, frameprob)
E       RuntimeError: pybind11::handle::inc_ref() PyGILState_Check() failure.

hmmlearn/base.py:1080: RuntimeError
----------------------------- Captured stderr call -----------------------------
pybind11::handle::inc_ref() is being called while the GIL is either not held or 
invalid. Please see 
https://pybind11.readthedocs.io/en/stable/advanced/misc.html#common-sources-of-global-interpreter-lock-errors
 for debugging advice.
If you are convinced there is no bug in your code, you can #define 
PYBIND11_NO_ASSERT_GIL_HELD_INCREF_DECREF to disable this check. In that case 
you have to ensure this #define is consistently used for all translation units 
linked into a given pybind11 extension, otherwise there will be ODR violations. 
The failing pybind11::handle::inc_ref() call was triggered on a numpy.ndarray 
object.
_________________ TestDiagonal.test_common_initialization[log] _________________

self = <hmmlearn.tests.test_variational_gaussian.TestDiagonal object at 
0x7f77ab8d3980>
implementation = 'log'

    @pytest.mark.parametrize("implementation", ["scaling", "log"])
    def test_common_initialization(self, implementation):
        sequences, lengths = get_sequences(50, 10,
                                           model=get_mcgrory_titterington())

with pytest.raises(ValueError):

            model = vhmm.VariationalGaussianHMM(
                4, n_iter=500, tol=1e-9,
                covariance_type="incorrect",
                implementation=implementation)
            assert_log_likelihood_increasing(model, sequences, lengths, 10)

with pytest.raises(ValueError):

            model = vhmm.VariationalGaussianHMM(
                4, n_iter=500, tol=1e-9,
                covariance_type="incorrect",
                init_params="",
                implementation=implementation)
            model.startprob_= np.asarray([.25, .25, .25, .25])
            model.score(sequences, lengths)

# Manually setup means - should converge

        model = vhmm.VariationalGaussianHMM(
            4, n_iter=500, tol=1e-9, init_params="stc",
            covariance_type=self.covariance_type,
            implementation=implementation)
        model.means_prior_ = [[1], [1], [1], [1]]
        model.means_posterior_ = [[2], [1], [3], [4]]
        model.beta_prior_ = [1, 1, 1, 1]
        model.beta_posterior_ = [1, 1, 1, 1]

      assert_log_likelihood_increasing(model, sequences, lengths, 10)


hmmlearn/tests/test_variational_gaussian.py:123:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
hmmlearn/tests/__init__.py:46: in assert_log_likelihood_increasing
    h.fit(X, lengths=lengths)
hmmlearn/base.py:473: in fit
    stats, curr_logprob = self._do_estep(X, lengths)
hmmlearn/base.py:750: in _do_estep
    lattice, logprob, posteriors, fwdlattice, bwdlattice = impl(sub_X)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = VariationalGaussianHMM(covariance_type='diag', init_params='', 
n_components=4,
                       n_iter=1, tol=1e-09)
X = array([[-1.00900958],
       [ 1.83548612],
       [-1.18687723],
       [ 1.39357219],
       [ 2.31529054],
       [...120186],
       [-0.59813352],
       [ 1.09476375],
       [ 2.7001891 ],
       [ 0.25515909],
       [-1.58409402]])

    def _fit_log(self, X):
        framelogprob = self._compute_subnorm_log_likelihood(X)

      logprob, fwdlattice = _hmmc.forward_log(

            self.startprob_subnorm_, self.transmat_subnorm_, framelogprob)
E       RuntimeError: pybind11::handle::inc_ref() PyGILState_Check() failure.

hmmlearn/base.py:1091: RuntimeError
----------------------------- Captured stderr call -----------------------------
pybind11::handle::inc_ref() is being called while the GIL is either not held or 
invalid. Please see 
https://pybind11.readthedocs.io/en/stable/advanced/misc.html#common-sources-of-global-interpreter-lock-errors
 for debugging advice.
If you are convinced there is no bug in your code, you can #define 
PYBIND11_NO_ASSERT_GIL_HELD_INCREF_DECREF to disable this check. In that case 
you have to ensure this #define is consistently used for all translation units 
linked into a given pybind11 extension, otherwise there will be ODR violations. 
The failing pybind11::handle::inc_ref() call was triggered on a numpy.ndarray 
object.
__________________ TestDiagonal.test_initialization[scaling] ___________________

self = <hmmlearn.tests.test_variational_gaussian.TestDiagonal object at 
0x7f77ab8d22d0>
implementation = 'scaling'

    @pytest.mark.parametrize("implementation", ["scaling", "log"])
    def test_initialization(self, implementation):
        random_state = check_random_state(234234)
        sequences, lengths = get_sequences(
            50, 10, model=get_mcgrory_titterington())

# dof's have wrong shape

        with pytest.raises(ValueError):
            model = self.new_for_init(implementation)
            model.dof_prior_ = [1, 1, 1]
            assert_log_likelihood_increasing(model, sequences, lengths, 10)

with pytest.raises(ValueError):

            model = self.new_for_init(implementation)
            model.dof_posterior_ = [1, 1, 1]
            assert_log_likelihood_increasing(model, sequences, lengths, 10)

# scales's have wrong shape

        with pytest.raises(ValueError):
            model = self.new_for_init(implementation)
            model.scale_prior_ = [[2], [2], [2]]
            assert_log_likelihood_increasing(model, sequences, lengths, 10)

with pytest.raises(ValueError):

            model = vhmm.VariationalGaussianHMM(
                4, n_iter=500, tol=1e-9, init_params="stm",
                covariance_type=self.covariance_type,
                implementation=implementation)
            model.dof_prior_ = [1, 1, 1, 1]
            model.dof_posterior_ = [1, 1, 1, 1]
            model.scale_prior_ = [[2], [2], [2], [2]]
            model.scale_posterior_ = [[2, 2, 2]]  # this is wrong
            assert_log_likelihood_increasing(model, sequences, lengths, 10)

# Set priors correctly via params

        model = vhmm.VariationalGaussianHMM(
            4, n_iter=500, tol=1e-9, random_state=random_state,
            covariance_type=self.covariance_type,
            implementation=implementation,
            means_prior=[[0.], [0.], [0.], [0.]],
            beta_prior=[2., 2., 2., 2.],
            dof_prior=[2., 2., 2., 2.],
            scale_prior=[[2], [2], [2], [2]]
        )

      assert_log_likelihood_increasing(model, sequences, lengths, 10)


hmmlearn/tests/test_variational_gaussian.py:486:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
hmmlearn/tests/__init__.py:46: in assert_log_likelihood_increasing
    h.fit(X, lengths=lengths)
hmmlearn/base.py:473: in fit
    stats, curr_logprob = self._do_estep(X, lengths)
hmmlearn/base.py:750: in _do_estep
    lattice, logprob, posteriors, fwdlattice, bwdlattice = impl(sub_X)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = VariationalGaussianHMM(beta_prior=[2.0, 2.0, 2.0, 2.0], 
covariance_type='diag',
                       dof_prior=[2.0,...andom_state=RandomState(MT19937) at 
0x7F77AB814240,
                       scale_prior=[[2], [2], [2], [2]], tol=1e-09)
X = array([[ 0.37725899],
       [ 3.11738285],
       [-0.09163979],
       [ 1.69939899],
       [ 1.17211122],
       [...975532],
       [-1.29219785],
       [-2.21400016],
       [-0.12401679],
       [ 3.5650227 ],
       [-0.33847644]])

    def _fit_scaling(self, X):
        frameprob = self._compute_subnorm_likelihood(X)

      logprob, fwdlattice, scaling_factors = _hmmc.forward_scaling(

            self.startprob_subnorm_, self.transmat_subnorm_, frameprob)
E       RuntimeError: pybind11::handle::inc_ref() PyGILState_Check() failure.

hmmlearn/base.py:1080: RuntimeError
----------------------------- Captured stderr call -----------------------------
pybind11::handle::inc_ref() is being called while the GIL is either not held or 
invalid. Please see 
https://pybind11.readthedocs.io/en/stable/advanced/misc.html#common-sources-of-global-interpreter-lock-errors
 for debugging advice.
If you are convinced there is no bug in your code, you can #define 
PYBIND11_NO_ASSERT_GIL_HELD_INCREF_DECREF to disable this check. In that case 
you have to ensure this #define is consistently used for all translation units 
linked into a given pybind11 extension, otherwise there will be ODR violations. 
The failing pybind11::handle::inc_ref() call was triggered on a numpy.ndarray 
object.
____________________ TestDiagonal.test_initialization[log] _____________________

self = <hmmlearn.tests.test_variational_gaussian.TestDiagonal object at 
0x7f77ab8d03e0>
implementation = 'log'

    @pytest.mark.parametrize("implementation", ["scaling", "log"])
    def test_initialization(self, implementation):
        random_state = check_random_state(234234)
        sequences, lengths = get_sequences(
            50, 10, model=get_mcgrory_titterington())

# dof's have wrong shape

        with pytest.raises(ValueError):
            model = self.new_for_init(implementation)
            model.dof_prior_ = [1, 1, 1]
            assert_log_likelihood_increasing(model, sequences, lengths, 10)

with pytest.raises(ValueError):

            model = self.new_for_init(implementation)
            model.dof_posterior_ = [1, 1, 1]
            assert_log_likelihood_increasing(model, sequences, lengths, 10)

# scales's have wrong shape

        with pytest.raises(ValueError):
            model = self.new_for_init(implementation)
            model.scale_prior_ = [[2], [2], [2]]
            assert_log_likelihood_increasing(model, sequences, lengths, 10)

with pytest.raises(ValueError):

            model = vhmm.VariationalGaussianHMM(
                4, n_iter=500, tol=1e-9, init_params="stm",
                covariance_type=self.covariance_type,
                implementation=implementation)
            model.dof_prior_ = [1, 1, 1, 1]
            model.dof_posterior_ = [1, 1, 1, 1]
            model.scale_prior_ = [[2], [2], [2], [2]]
            model.scale_posterior_ = [[2, 2, 2]]  # this is wrong
            assert_log_likelihood_increasing(model, sequences, lengths, 10)

# Set priors correctly via params

        model = vhmm.VariationalGaussianHMM(
            4, n_iter=500, tol=1e-9, random_state=random_state,
            covariance_type=self.covariance_type,
            implementation=implementation,
            means_prior=[[0.], [0.], [0.], [0.]],
            beta_prior=[2., 2., 2., 2.],
            dof_prior=[2., 2., 2., 2.],
            scale_prior=[[2], [2], [2], [2]]
        )

      assert_log_likelihood_increasing(model, sequences, lengths, 10)


hmmlearn/tests/test_variational_gaussian.py:486:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
hmmlearn/tests/__init__.py:46: in assert_log_likelihood_increasing
    h.fit(X, lengths=lengths)
hmmlearn/base.py:473: in fit
    stats, curr_logprob = self._do_estep(X, lengths)
hmmlearn/base.py:750: in _do_estep
    lattice, logprob, posteriors, fwdlattice, bwdlattice = impl(sub_X)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = VariationalGaussianHMM(beta_prior=[2.0, 2.0, 2.0, 2.0], 
covariance_type='diag',
                       dof_prior=[2.0,...andom_state=RandomState(MT19937) at 
0x7F77AB881740,
                       scale_prior=[[2], [2], [2], [2]], tol=1e-09)
X = array([[-1.50974603],
       [ 0.66501942],
       [ 1.03376567],
       [-0.33821964],
       [-0.03369866],
       [...945696],
       [ 1.03948035],
       [ 3.29548267],
       [-1.67415189],
       [-0.95330419],
       [ 2.79920426]])

    def _fit_log(self, X):
        framelogprob = self._compute_subnorm_log_likelihood(X)

      logprob, fwdlattice = _hmmc.forward_log(

            self.startprob_subnorm_, self.transmat_subnorm_, framelogprob)
E       RuntimeError: pybind11::handle::inc_ref() PyGILState_Check() failure.

hmmlearn/base.py:1091: RuntimeError
----------------------------- Captured stderr call -----------------------------
pybind11::handle::inc_ref() is being called while the GIL is either not held or 
invalid. Please see 
https://pybind11.readthedocs.io/en/stable/advanced/misc.html#common-sources-of-global-interpreter-lock-errors
 for debugging advice.
If you are convinced there is no bug in your code, you can #define 
PYBIND11_NO_ASSERT_GIL_HELD_INCREF_DECREF to disable this check. In that case 
you have to ensure this #define is consistently used for all translation units 
linked into a given pybind11 extension, otherwise there will be ODR violations. 
The failing pybind11::handle::inc_ref() call was triggered on a numpy.ndarray 
object.
=============================== warnings summary ===============================
.pybuild/cpython3_3.12_hmmlearn/build/hmmlearn/tests/test_variational_categorical.py:
 9 warnings
.pybuild/cpython3_3.12_hmmlearn/build/hmmlearn/tests/test_variational_gaussian.py:
 15 warnings
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.12_hmmlearn/build/hmmlearn/base.py:1192: 
RuntimeWarning: underflow encountered in exp
    self.startprob_subnorm_ = np.exp(startprob_log_subnorm)

.pybuild/cpython3_3.12_hmmlearn/build/hmmlearn/tests/test_variational_categorical.py:
 7 warnings
.pybuild/cpython3_3.12_hmmlearn/build/hmmlearn/tests/test_variational_gaussian.py:
 13 warnings
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.12_hmmlearn/build/hmmlearn/base.py:1197: 
RuntimeWarning: underflow encountered in exp
    self.transmat_subnorm_ = np.exp(transmat_log_subnorm)

.pybuild/cpython3_3.12_hmmlearn/build/hmmlearn/tests/test_variational_categorical.py::TestVariationalCategorical::test_fit_beal[scaling]
  /<<PKGBUILDDIR>>/.pybuild/cpython3_3.12_hmmlearn/build/hmmlearn/base.py:1130: 
RuntimeWarning: underflow encountered in exp
    return np.exp(self._compute_subnorm_log_likelihood(X))

-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
=========================== short test summary info ============================
FAILED 
hmmlearn/tests/test_base.py::TestBaseAgainstWikipedia::test_do_forward_scaling_pass
FAILED 
hmmlearn/tests/test_base.py::TestBaseAgainstWikipedia::test_do_forward_pass
FAILED 
hmmlearn/tests/test_base.py::TestBaseAgainstWikipedia::test_do_backward_scaling_pass
FAILED 
hmmlearn/tests/test_base.py::TestBaseAgainstWikipedia::test_do_viterbi_pass
FAILED hmmlearn/tests/test_base.py::TestBaseAgainstWikipedia::test_score_samples
FAILED 
hmmlearn/tests/test_base.py::TestBaseConsistentWithGMM::test_score_samples
FAILED hmmlearn/tests/test_base.py::TestBaseConsistentWithGMM::test_decode - ...
FAILED 
hmmlearn/tests/test_categorical_hmm.py::TestCategoricalAgainstWikipedia::test_decode_viterbi[scaling]
FAILED 
hmmlearn/tests/test_categorical_hmm.py::TestCategoricalAgainstWikipedia::test_decode_viterbi[log]
FAILED 
hmmlearn/tests/test_categorical_hmm.py::TestCategoricalAgainstWikipedia::test_decode_map[scaling]
FAILED 
hmmlearn/tests/test_categorical_hmm.py::TestCategoricalAgainstWikipedia::test_decode_map[log]
FAILED 
hmmlearn/tests/test_categorical_hmm.py::TestCategoricalAgainstWikipedia::test_predict[scaling]
FAILED 
hmmlearn/tests/test_categorical_hmm.py::TestCategoricalAgainstWikipedia::test_predict[log]
FAILED 
hmmlearn/tests/test_categorical_hmm.py::TestCategoricalHMM::test_n_features[scaling]
FAILED 
hmmlearn/tests/test_categorical_hmm.py::TestCategoricalHMM::test_n_features[log]
FAILED 
hmmlearn/tests/test_categorical_hmm.py::TestCategoricalHMM::test_score_samples[scaling]
FAILED 
hmmlearn/tests/test_categorical_hmm.py::TestCategoricalHMM::test_score_samples[log]
FAILED 
hmmlearn/tests/test_categorical_hmm.py::TestCategoricalHMM::test_fit[scaling]
FAILED hmmlearn/tests/test_categorical_hmm.py::TestCategoricalHMM::test_fit[log]
FAILED 
hmmlearn/tests/test_categorical_hmm.py::TestCategoricalHMM::test_fit_emissionprob[scaling]
FAILED 
hmmlearn/tests/test_categorical_hmm.py::TestCategoricalHMM::test_fit_emissionprob[log]
FAILED 
hmmlearn/tests/test_categorical_hmm.py::TestCategoricalHMM::test_fit_with_init[scaling]
FAILED 
hmmlearn/tests/test_categorical_hmm.py::TestCategoricalHMM::test_fit_with_init[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_score_samples_and_decode[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_score_samples_and_decode[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_fit[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_fit[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_criterion[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_criterion[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_fit_ignored_init_warns[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_fit_ignored_init_warns[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_fit_sequences_of_different_length[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_fit_sequences_of_different_length[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_fit_with_length_one_signal[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_fit_with_length_one_signal[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_fit_zero_variance[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_fit_zero_variance[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_fit_with_priors[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_fit_with_priors[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_fit_startprob_and_transmat[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_fit_startprob_and_transmat[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithSphericalCovars::test_underflow_from_scaling[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithDiagonalCovars::test_score_samples_and_decode[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithDiagonalCovars::test_score_samples_and_decode[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithDiagonalCovars::test_fit[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithDiagonalCovars::test_fit[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithDiagonalCovars::test_criterion[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithDiagonalCovars::test_criterion[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithDiagonalCovars::test_fit_ignored_init_warns[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithDiagonalCovars::test_fit_ignored_init_warns[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithDiagonalCovars::test_fit_sequences_of_different_length[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithDiagonalCovars::test_fit_sequences_of_different_length[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithDiagonalCovars::test_fit_with_length_one_signal[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithDiagonalCovars::test_fit_with_length_one_signal[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithDiagonalCovars::test_fit_zero_variance[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithDiagonalCovars::test_fit_zero_variance[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithDiagonalCovars::test_fit_with_priors[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithDiagonalCovars::test_fit_with_priors[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithDiagonalCovars::test_fit_left_right[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithDiagonalCovars::test_fit_left_right[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithTiedCovars::test_score_samples_and_decode[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithTiedCovars::test_score_samples_and_decode[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithTiedCovars::test_fit[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithTiedCovars::test_fit[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithTiedCovars::test_criterion[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithTiedCovars::test_criterion[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithTiedCovars::test_fit_ignored_init_warns[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithTiedCovars::test_fit_ignored_init_warns[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithTiedCovars::test_fit_sequences_of_different_length[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithTiedCovars::test_fit_sequences_of_different_length[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithTiedCovars::test_fit_with_length_one_signal[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithTiedCovars::test_fit_with_length_one_signal[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithTiedCovars::test_fit_zero_variance[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithTiedCovars::test_fit_zero_variance[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithTiedCovars::test_fit_with_priors[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithTiedCovars::test_fit_with_priors[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithFullCovars::test_score_samples_and_decode[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithFullCovars::test_score_samples_and_decode[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithFullCovars::test_fit[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithFullCovars::test_fit[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithFullCovars::test_criterion[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithFullCovars::test_criterion[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithFullCovars::test_fit_ignored_init_warns[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithFullCovars::test_fit_ignored_init_warns[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithFullCovars::test_fit_sequences_of_different_length[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithFullCovars::test_fit_sequences_of_different_length[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithFullCovars::test_fit_with_length_one_signal[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithFullCovars::test_fit_with_length_one_signal[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithFullCovars::test_fit_zero_variance[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithFullCovars::test_fit_zero_variance[log]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithFullCovars::test_fit_with_priors[scaling]
FAILED 
hmmlearn/tests/test_gaussian_hmm.py::TestGaussianHMMWithFullCovars::test_fit_with_priors[log]
FAILED 
hmmlearn/tests/test_gmm_hmm_multisequence.py::test_gmmhmm_multi_sequence_fit_invariant_to_sequence_ordering[scaling-diag]
FAILED 
hmmlearn/tests/test_gmm_hmm_multisequence.py::test_gmmhmm_multi_sequence_fit_invariant_to_sequence_ordering[scaling-spherical]
FAILED 
hmmlearn/tests/test_gmm_hmm_multisequence.py::test_gmmhmm_multi_sequence_fit_invariant_to_sequence_ordering[scaling-tied]
FAILED 
hmmlearn/tests/test_gmm_hmm_multisequence.py::test_gmmhmm_multi_sequence_fit_invariant_to_sequence_ordering[scaling-full]
FAILED 
hmmlearn/tests/test_gmm_hmm_multisequence.py::test_gmmhmm_multi_sequence_fit_invariant_to_sequence_ordering[log-diag]
FAILED 
hmmlearn/tests/test_gmm_hmm_multisequence.py::test_gmmhmm_multi_sequence_fit_invariant_to_sequence_ordering[log-spherical]
FAILED 
hmmlearn/tests/test_gmm_hmm_multisequence.py::test_gmmhmm_multi_sequence_fit_invariant_to_sequence_ordering[log-tied]
FAILED 
hmmlearn/tests/test_gmm_hmm_multisequence.py::test_gmmhmm_multi_sequence_fit_invariant_to_sequence_ordering[log-full]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithSphericalCovars::test_score_samples_and_decode[scaling]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithSphericalCovars::test_score_samples_and_decode[log]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithSphericalCovars::test_fit[scaling]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithSphericalCovars::test_fit[log]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithSphericalCovars::test_fit_sparse_data[scaling]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithSphericalCovars::test_fit_sparse_data[log]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithSphericalCovars::test_criterion[scaling]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithSphericalCovars::test_criterion[log]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithDiagCovars::test_score_samples_and_decode[scaling]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithDiagCovars::test_score_samples_and_decode[log]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithDiagCovars::test_fit[scaling]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithDiagCovars::test_fit[log]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithDiagCovars::test_fit_sparse_data[scaling]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithDiagCovars::test_fit_sparse_data[log]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithDiagCovars::test_criterion[scaling]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithDiagCovars::test_criterion[log]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithTiedCovars::test_score_samples_and_decode[scaling]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithTiedCovars::test_score_samples_and_decode[log]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithTiedCovars::test_fit[scaling]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithTiedCovars::test_fit[log]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithTiedCovars::test_fit_sparse_data[scaling]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithTiedCovars::test_fit_sparse_data[log]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithTiedCovars::test_criterion[scaling]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithTiedCovars::test_criterion[log]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithFullCovars::test_score_samples_and_decode[scaling]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithFullCovars::test_score_samples_and_decode[log]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithFullCovars::test_fit[scaling]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithFullCovars::test_fit[log]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithFullCovars::test_fit_sparse_data[scaling]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithFullCovars::test_fit_sparse_data[log]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithFullCovars::test_criterion[scaling]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMMWithFullCovars::test_criterion[log]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMM_KmeansInit::test_kmeans[scaling]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMM_KmeansInit::test_kmeans[log]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMM_MultiSequence::test_chunked[diag]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMM_MultiSequence::test_chunked[spherical]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMM_MultiSequence::test_chunked[tied]
FAILED 
hmmlearn/tests/test_gmm_hmm_new.py::TestGMMHMM_MultiSequence::test_chunked[full]
FAILED 
hmmlearn/tests/test_multinomial_hmm.py::TestMultinomialHMM::test_score_samples[scaling]
FAILED 
hmmlearn/tests/test_multinomial_hmm.py::TestMultinomialHMM::test_score_samples[log]
FAILED 
hmmlearn/tests/test_multinomial_hmm.py::TestMultinomialHMM::test_fit[scaling]
FAILED hmmlearn/tests/test_multinomial_hmm.py::TestMultinomialHMM::test_fit[log]
FAILED 
hmmlearn/tests/test_multinomial_hmm.py::TestMultinomialHMM::test_fit_emissionprob[scaling]
FAILED 
hmmlearn/tests/test_multinomial_hmm.py::TestMultinomialHMM::test_fit_emissionprob[log]
FAILED 
hmmlearn/tests/test_multinomial_hmm.py::TestMultinomialHMM::test_fit_with_init[scaling]
FAILED 
hmmlearn/tests/test_multinomial_hmm.py::TestMultinomialHMM::test_fit_with_init[log]
FAILED 
hmmlearn/tests/test_multinomial_hmm.py::TestMultinomialHMM::test_compare_with_categorical_hmm[scaling]
FAILED 
hmmlearn/tests/test_multinomial_hmm.py::TestMultinomialHMM::test_compare_with_categorical_hmm[log]
FAILED 
hmmlearn/tests/test_poisson_hmm.py::TestPoissonHMM::test_score_samples[scaling]
FAILED 
hmmlearn/tests/test_poisson_hmm.py::TestPoissonHMM::test_score_samples[log]
FAILED hmmlearn/tests/test_poisson_hmm.py::TestPoissonHMM::test_fit[scaling]
FAILED hmmlearn/tests/test_poisson_hmm.py::TestPoissonHMM::test_fit[log] - Ru...
FAILED 
hmmlearn/tests/test_poisson_hmm.py::TestPoissonHMM::test_fit_lambdas[scaling]
FAILED hmmlearn/tests/test_poisson_hmm.py::TestPoissonHMM::test_fit_lambdas[log]
FAILED 
hmmlearn/tests/test_poisson_hmm.py::TestPoissonHMM::test_fit_with_init[scaling]
FAILED 
hmmlearn/tests/test_poisson_hmm.py::TestPoissonHMM::test_fit_with_init[log]
FAILED 
hmmlearn/tests/test_poisson_hmm.py::TestPoissonHMM::test_criterion[scaling]
FAILED hmmlearn/tests/test_poisson_hmm.py::TestPoissonHMM::test_criterion[log]
FAILED 
hmmlearn/tests/test_variational_categorical.py::TestVariationalCategorical::test_init_priors[scaling]
FAILED 
hmmlearn/tests/test_variational_categorical.py::TestVariationalCategorical::test_init_priors[log]
FAILED 
hmmlearn/tests/test_variational_categorical.py::TestVariationalCategorical::test_n_features[scaling]
FAILED 
hmmlearn/tests/test_variational_categorical.py::TestVariationalCategorical::test_n_features[log]
FAILED 
hmmlearn/tests/test_variational_categorical.py::TestVariationalCategorical::test_init_incorrect_priors[scaling]
FAILED 
hmmlearn/tests/test_variational_categorical.py::TestVariationalCategorical::test_init_incorrect_priors[log]
FAILED 
hmmlearn/tests/test_variational_categorical.py::TestVariationalCategorical::test_fit_beal[scaling]
FAILED 
hmmlearn/tests/test_variational_categorical.py::TestVariationalCategorical::test_fit_beal[log]
FAILED 
hmmlearn/tests/test_variational_categorical.py::TestVariationalCategorical::test_fit_and_compare_with_em[scaling]
FAILED 
hmmlearn/tests/test_variational_categorical.py::TestVariationalCategorical::test_fit_and_compare_with_em[log]
FAILED 
hmmlearn/tests/test_variational_categorical.py::TestVariationalCategorical::test_fit_length_1_sequences[scaling]
FAILED 
hmmlearn/tests/test_variational_categorical.py::TestVariationalCategorical::test_fit_length_1_sequences[log]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestFull::test_random_fit[scaling]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestFull::test_random_fit[log]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestFull::test_fit_mcgrory_titterington1d[scaling]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestFull::test_fit_mcgrory_titterington1d[log]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestFull::test_common_initialization[scaling]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestFull::test_common_initialization[log]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestFull::test_initialization[scaling]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestFull::test_initialization[log]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestTied::test_random_fit[scaling]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestTied::test_random_fit[log]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestTied::test_fit_mcgrory_titterington1d[scaling]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestTied::test_fit_mcgrory_titterington1d[log]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestTied::test_common_initialization[scaling]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestTied::test_common_initialization[log]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestTied::test_initialization[scaling]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestTied::test_initialization[log]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestSpherical::test_random_fit[scaling]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestSpherical::test_random_fit[log]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestSpherical::test_fit_mcgrory_titterington1d[scaling]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestSpherical::test_fit_mcgrory_titterington1d[log]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestSpherical::test_common_initialization[scaling]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestSpherical::test_common_initialization[log]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestSpherical::test_initialization[scaling]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestSpherical::test_initialization[log]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestDiagonal::test_random_fit[scaling]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestDiagonal::test_random_fit[log]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestDiagonal::test_fit_mcgrory_titterington1d[scaling]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestDiagonal::test_fit_mcgrory_titterington1d[log]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestDiagonal::test_common_initialization[scaling]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestDiagonal::test_common_initialization[log]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestDiagonal::test_initialization[scaling]
FAILED 
hmmlearn/tests/test_variational_gaussian.py::TestDiagonal::test_initialization[log]
=========== 202 failed, 92 passed, 26 xfailed, 45 warnings in 13.37s ===========
E: pybuild pybuild:389: test: plugin pyproject failed with: exit code=1: cd 
/<<PKGBUILDDIR>>/.pybuild/cpython3_3.12_hmmlearn/build; python3.12 -m pytest 
--pyargs hmmlearn
dh_auto_test: error: pybuild --test --test-pytest -i python{version} -p 3.12 
returned exit code 13
make: *** [debian/rules:9: binary] Error 25
dpkg-buildpackage: error: debian/rules binary subprocess returned exit status 2
--------------------------------------------------------------------------------

The above is just how the build ends and not necessarily the most relevant part.
If required, the full build log is available here:

https://people.debian.org/~sanvila/build-logs/202409/

About the archive rebuild: The build was made on virtual machines from AWS,
using sbuild and a reduced chroot with only build-essential packages.

If you could not reproduce the bug please contact me privately, as I
am willing to provide ssh access to a virtual machine where the bug is
fully reproducible.

If this is really a bug in one of the build-depends, please use
reassign and affects, so that this is still visible in the BTS web
page for this package.

Thanks.

--- End Message ---

--- Begin Message ---

Source: python-hmmlearn
Source-Version: 0.3.2-1
Done: Michael R. Crusoe <cru...@debian.org>

We believe that the bug you reported is fixed in the latest version of
python-hmmlearn, which is due to be installed in the Debian FTP archive.

A summary of the changes between this version and the previous one is
attached.

Thank you for reporting the bug, which will now be closed.  If you
have further comments please address them to 1082...@bugs.debian.org,
and the maintainer will reopen the bug report if appropriate.

Debian distribution maintenance software
pp.
Michael R. Crusoe <cru...@debian.org> (supplier of updated python-hmmlearn 
package)

(This message was generated automatically at their request; if you
believe that there is a problem with it please contact the archive
administrators by mailing ftpmas...@ftp-master.debian.org)


-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA512

Format: 1.8
Date: Fri, 04 Oct 2024 18:11:45 +0200
Source: python-hmmlearn
Architecture: source
Version: 0.3.2-1
Distribution: unstable
Urgency: medium
Maintainer: Debian Med Packaging Team 
<debian-med-packag...@lists.alioth.debian.org>
Changed-By: Michael R. Crusoe <cru...@debian.org>
Closes: 1081690 1082695
Changes:
 python-hmmlearn (0.3.2-1) unstable; urgency=medium
 .
   * Team upload.
   * New upstream version
   * Remove all patches, they are in the new upstream release.
   * Added patch to hack around GIL error. Closes: #1082695, #1081690
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Files:
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python-hmmlearn_0.3.2-1.dsc
 3f2121da97e876844f68a24778e89844 75203 science optional 
python-hmmlearn_0.3.2.orig.tar.gz
 24a5d79b65731a1ed934cb14d21fcdf7 3928 science optional 
python-hmmlearn_0.3.2-1.debian.tar.xz
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python-hmmlearn_0.3.2-1_source.buildinfo

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--- End Message ---

Bug#1082695: marked as done (python-hmmlearn: FTBFS: failing tests)

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