10000 FIX Fixes check_array nonfinite checks with ArrayAPI specification (#… · scikit-learn/scikit-learn@c069158 · GitHub
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FIX Fixes check_array nonfinite checks with ArrayAPI specification (#25619)
* FIX Fixes check_array nonfinite checks with ArrayAPI specification * DOC Adds PR number * FIX Test on both cupy and numpy
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‎doc/whats_new/v1.2.rst

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@@ -65,6 +65,13 @@ Changelog
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when the global configuration sets `transform_output="pandas"`.
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:pr:`25500` by :user:`Guillaume Lemaitre <glemaitre>`.
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:mod:`sklearn.utils`
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....................
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- |Fix| Fixes a bug in :func:`utils.check_array` which now correctly performs
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non-finite validation with the Array API specification. :pr:`25619` by
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`Thomas Fan`_.
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.. _changes_1_2_1:
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Version 1.2.1

‎sklearn/utils/tests/test_validation.py

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@@ -13,6 +13,7 @@
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import numpy as np
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import scipy.sparse as sp
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from sklearn._config import config_context
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from sklearn.utils._testing import assert_no_warnings
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from sklearn.utils._testing import ignore_warnings
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from sklearn.utils._testing import SkipTest
@@ -1759,3 +1760,19 @@ def test_boolean_series_remains_boolean():
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assert res.dtype == expected.dtype
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assert_array_equal(res, expected)
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@pytest.mark.parametrize("array_namespace", ["numpy.array_api", "cupy.array_api"])
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def test_check_array_array_api_has_non_finite(array_namespace):
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"""Checks that Array API arrays checks non-finite correctly."""
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xp = pytest.importorskip(array_namespace)
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X_nan = xp.asarray([[xp.nan, 1, 0], [0, xp.nan, 3]], dtype=xp.float32)
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with config_context(array_api_dispatch=True):
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with pytest.raises(ValueError, match="Input contains NaN."):
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check_array(X_nan)
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X_inf = xp.asarray([[xp.inf, 1, 0], [0, xp.inf, 3]], dtype=xp.float32)
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with config_context(array_api_dispatch=True):
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with pytest.raises(ValueError, match="infinity or a value too large"):
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check_array(X_inf)

‎sklearn/utils/validation.py

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@@ -131,8 +131,8 @@ def _assert_all_finite(
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has_nan_error = False if allow_nan else out == FiniteStatus.has_nan
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has_inf = out == FiniteStatus.has_infinite
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else:
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has_inf = np.isinf(X).any()
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has_nan_error = False if allow_nan else xp.isnan(X).any()
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has_inf = xp.any(xp.isinf(X))
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has_nan_error = False if allow_nan else xp.any(xp.isnan(X))
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if has_inf or has_nan_error:
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if has_nan_error:
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type_err = "NaN"

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