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FIX np.divide undefined behaviour with where in gaussian processes #24245

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merged 2 commits into from
Sep 5, 2022
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FIX np.divide undefined behaviour with where in gaussian processes #24245

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e82eb17
[pypy] FIX np.divide undefined behaviour with where
lesteve Aug 24, 2022
d2cae35
Tweak + whats_new entry
lesteve Aug 24, 2022
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7 changes: 7 additions & 0 deletions doc/whats_new/v1.2.rst
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Expand Up @@ -198,6 +198,13 @@ Changelog
:mod:`sklearn.feature_selection`
................................

:mod:`sklearn.gaussian_process`
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This section seems to be out of place in the whats new.

...............................

- |Fix| Fix :class:`gaussian_process.kernels.Matern` gradient computation with
`nu=0.5` for PyPy (and possibly other non CPython interpreters). :pr:`24245`
by :user:`Loïc Estève <lesteve>`.

:mod:`sklearn.linear_model`
...........................

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9 changes: 7 additions & 2 deletions sklearn/gaussian_process/kernels.py
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Expand Up @@ -1733,9 +1733,14 @@ def __call__(self, X, Y=None, eval_gradient=False):

if self.nu == 0.5:
denominator = np.sqrt(D.sum(axis=2))[:, :, np.newaxis]
K_gradient = K[..., np.newaxis] * np.divide(
D, denominator, where=denominator != 0
divide_result = np.zeros_like(D)
np.divide(
D,
denominator,
out=divide_result,
where=denominator != 0,
)
K_gradient = K[..., np.newaxis] * divide_result
elif self.nu == 1.5:
K_gradient = 3 * D * np.exp(-np.sqrt(3 * D.sum(-1)))[..., np.newaxis]
elif self.nu == 2.5:
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3 changes: 0 additions & 3 deletions sklearn/gaussian_process/tests/test_kernels.py
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Expand Up @@ -34,7 +34,6 @@
assert_array_equal,
assert_array_almost_equal,
assert_allclose,
fails_if_pypy,
)


Expand Down Expand Up @@ -70,8 +69,6 @@
kernels.append(PairwiseKernel(gamma=1.0, metric=metric))


# Numerical precisions errors in PyPy
@fails_if_pypy
@pytest.mark.parametrize("kernel", kernels)
def test_kernel_gradient(kernel):
# Compare analytic and numeric gradient of kernels.
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