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🔒 🤖 CI Update lock files for main CI build(s) 🔒 🤖#29276

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🔒 🤖 CI Update lock files for main CI build(s) 🔒 🤖#29276
scikit-learn-bot wants to merge 1 commit intoscikit-learn:mainfrom
scikit-learn-bot:auto-update-lock-files-main

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@scikit-learn-bot scikit-learn-bot commented Jun 17, 2024

Update lock files.

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If the CI tasks fail, create a new branch based on this PR and add the required fixes to that branch.

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github-actions bot commented Jun 17, 2024 •
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✔️ Linting Passed

All linting checks passed. Your pull request is in excellent shape! ☀️

Generated for commit: 8efbaeb. Link to the linter CI: here

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lesteve commented Jun 17, 2024 •
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The CI issue comes from pyamg uses np.deprecate which is deprecated in Numpy 2: pyamg/pyamg#406

The short-term fix is to ignore the warning similarly to pyamg warnings which are already ignored.

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ogrisel commented Jun 17, 2024

The short-term fix is to ignore the warning similarly to pyamg warnings which are already ignored.

+1

@scikit-learn-bot scikit-learn-bot force-pushed the auto-update-lock-files-main branch from 99b3de3 to 180e9fa Compare June 24, 2024 05:08
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lesteve commented Jun 27, 2024 •
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pyamg 5.2 has been released without the DeprecationWarning due to Numpy 2, so I guess the best thing to do is to wait until next Monday and see what happens on the next bot schedule run.

See pyamg/pyamg#406.

@scikit-learn-bot scikit-learn-bot force-pushed the auto-update-lock-files-main branch from 180e9fa to 130ce2e Compare July 1, 2024 05:07
@lesteve lesteve mentioned this pull request Jul 1, 2024
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lesteve commented Jul 1, 2024 •
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27 failures from one Azure build log. Here is a quick summary looking at the different errors.

doctests differences likely due to scipy 1.13 -> 1.14?

Probably a work-around is to skip doctests in some settings, there is already some logic to do this.

Details 
_________________ [doctest] sklearn.utils.validation.indexable _________________
[gw1] linux -- Python 3.11.9 /usr/share/miniconda/envs/testvenv/bin/python
494 
495     Examples
496     --------
497     >>> from sklearn.utils import indexable
498     >>> from scipy.sparse import csr_matrix
499     >>> import numpy as np
500     >>> iterables = [
501     ...     [1, 2, 3], np.array([2, 3, 4]), None, csr_matrix([[5], [6], [7]])
502     ... ]
503     >>> indexable(*iterables)
Expected:
    [[1, 2, 3], array([2, 3, 4]), None, <3x1 sparse matrix ...>]
Got:
    [[1, 2, 3], array([2, 3, 4]), None, <Compressed Sparse Row sparse matrix of dtype 'int64'
    	with 3 stored elements and shape (3, 1)>]

array API issues

likely due to array-api-strict 1.1 -> 2.0 update?

TypeError: array iteration is not allowed in array-api-strict
Details 
__________ test_isin[uint8-14-False-False-array_api_strict-None-None] __________
[gw1] linux -- Python 3.11.9 /usr/share/miniconda/envs/testvenv/bin/python

array_namespace = 'array_api_strict', device = None, _ = None, invert = False
assume_unique = False, element_size = 14, int_dtype = 'uint8'

    @pytest.mark.parametrize(
        "array_namespace, device, _", yield_namespace_device_dtype_combinations()
    )
    @pytest.mark.parametrize("invert", [True, False])
    @pytest.mark.parametrize("assume_unique", [True, False])
    @pytest.mark.parametrize("element_size", [6, 10, 14])
    @pytest.mark.parametrize("int_dtype", ["int16", "int32", "int64", "uint8"])
    def test_isin(
        array_namespace, device, _, invert, assume_unique, element_size, int_dtype
    ):
        xp = _array_api_for_tests(array_namespace, device)
        r = element_size // 2
        element = 2 * numpy.arange(element_size).reshape((r, 2)).astype(int_dtype)
        test_elements = numpy.array(numpy.arange(14), dtype=int_dtype)
        element_xp = xp.asarray(element, device=device)
        test_elements_xp = xp.asarray(test_elements, device=device)
        expected = numpy.isin(
            element=element,
            test_elements=test_elements,
            assume_unique=assume_unique,
            invert=invert,
        )
        with config_context(array_api_dispatch=True):
>           result = _isin(
                element=element_xp,
                test_elements=test_elements_xp,
E       TypeError: array iteration is not allowed in array-api-strict

self       = Array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,
        9, 10, 11, 12, 13], dtype=array_api_strict.uint8)

Cryptic CircleCI failure (segmentation fault?)

build log

generating gallery for auto_examples/gaussian_process... [ 10%] plot_gpr_noisy.py
generating gallery for auto_examples/gaussian_process... [ 20%] plot_compare_gpr_krr.py
generating gallery for auto_examples/gaussian_process... [ 30%] plot_gpr_co2.py
make: *** [Makefile:73: html] Segmentation fault (core dumped)
/home/circleci/miniforge3/envs/testenv/lib/python3.9/site-packages/joblib/externals/loky/backend/resource_tracker.py:314: UserWarning: resource_tracker: There appear to be 8 leaked semlock objects to clean up at shutdown
  warnings.warn(
/home/circleci/miniforge3/envs/testenv/lib/python3.9/site-packages/joblib/externals/loky/backend/resource_tracker.py:314: UserWarning: resource_tracker: There appear to be 1328 leaked folder objects to clean up at shutdown
  warnings.warn(

Exited with code exit status 2

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lesteve commented Jul 2, 2024 •
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Scipy bumped into array-api-strict 2 issues: scipy/scipy#21074, some were fixed in 2.0.1 released yesterday but locally I still get some issue about searchsorted and The function searchsorted requires API version 2023.12 or later, but the current API version for array-api-strict is 2022.12, see below. Edit this would actually be fixed by #29387

_________________________________________________________________________________________________________________________ test_label_encoder_array_api_compliance[y2-array_api_strict-None-None] __________________________________________________________________________________________________________________________
[gw1] linux -- Python 3.11.9 /home/lesteve/micromamba/envs/scikit-learn-conda-forge-mkl/bin/python

y = array([3, 5, 9, 5, 9, 3]), array_namespace = 'array_api_strict', device = None, dtype = None

    @pytest.mark.parametrize(
        "array_namespace, device, dtype", yield_namespace_device_dtype_combinations()
    )
    @pytest.mark.parametrize(
        "y",
        [
            np.array([2, 1, 3, 1, 3]),
            np.array([1, 1, 4, 5, -1, 0]),
            np.array([3, 5, 9, 5, 9, 3]),
        ],
    )
    def test_label_encoder_array_api_compliance(y, array_namespace, device, dtype):
        xp = _array_api_for_tests(array_namespace, device)
        xp_y = xp.asarray(y, device=device)
        with config_context(array_api_dispatch=True):
            xp_label = LabelEncoder()
            np_label = LabelEncoder()
            xp_label = xp_label.fit(xp_y)
>           xp_transformed = xp_label.transform(xp_y)

sklearn/preprocessing/tests/test_label.py:729: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
sklearn/preprocessing/_label.py:134: in transform
    return _encode(y, uniques=self.classes_)
sklearn/utils/_encode.py:240: in _encode
    return _searchsorted(xp, uniques, values)
sklearn/utils/_array_api.py:860: in _searchsorted
    return xp.searchsorted(a, v, side=side, sorter=sorter)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

args = (Array([3, 5, 9], dtype=array_api_strict.int64), Array([3, 5, 9, 5, 9, 3], dtype=array_api_strict.int64)), kwargs = {'side': 'left', 'sorter': None}

    @functools.wraps(func)
    def wrapper(*args, **kwargs):
        if version > API_VERSION:
>           raise RuntimeError(
                f"The function {func.__name__} requires API version {version} or later, "
                f"but the current API version for array-api-strict is {API_VERSION}"
            )
E           RuntimeError: The function searchsorted requires API version 2023.12 or later, but the current API version for array-api-strict is 2022.12

../../micromamba/envs/scikit-learn-conda-forge-mkl/lib/python3.11/site-packages/array_api_strict/_flags.py:355: RuntimeError
================================================================================================================================================= short test summary info =================================================================================================================================================
FAILED sklearn/preprocessing/tests/test_label.py::test_label_encoder_array_api_compliance[y0-array_api_strict-None-None] - RuntimeError: The function searchsorted requires API version 2023.12 or later, but the current API version for array-api-strict is 2022.12
FAILED sklearn/preprocessing/tests/test_label.py::test_label_encoder_array_api_compliance[y1-array_api_strict-None-None] - RuntimeError: The function searchsorted requires API version 2023.12 or later, but the current API version for array-api-strict is 2022.12
FAILED sklearn/preprocessing/tests/test_label.py::test_label_encoder_array_api_compliance[y2-array_api_strict-None-None] - RuntimeError: The function searchsorted requires API version 2023.12 or later, but the current API version for array-api-strict is 2022.12
================================================================================================================================= 3 failed, 149 passed, 1 skipped, 417 warnings in 11.14s =================================================================================================================================

@lesteve lesteve mentioned this pull request Jul 2, 2024
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lesteve commented Jul 2, 2024

I have opened #29385 to fix the doctests to be compatible for scipy>=1.14.

This was referenced Jul 2, 2024
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lesteve commented Jul 5, 2024 •
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This is taken over by #29388 since this requires quite a few changes.

I let this open otherwise the bot will open a separate PR on Monday and we want to have all the info in the same PR.

@scikit-learn-bot scikit-learn-bot force-pushed the auto-update-lock-files-main branch from 76940df to 8efbaeb Compare July 8, 2024 05:08
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