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Commit d7d3da8

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thomasjpfanvenkyyuvy
authored andcommitted
CI Fixes wheel building (scikit-learn#22051)
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‎.github/workflows/wheels.yml

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@@ -80,22 +80,22 @@ jobs:
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bitness: 32
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platform_id: win32
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# Linux 64 bit manylinux1
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# Linux 64 bit manylinux2014
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- os: ubuntu-latest
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python: 37
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bitness: 64
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platform_id: manylinux_x86_64
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manylinux_image: manylinux1
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manylinux_image: manylinux2014
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- os: ubuntu-latest
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python: 38
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bitness: 64
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platform_id: manylinux_x86_64
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manylinux_image: manylinux1
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manylinux_image: manylinux2014
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- os: ubuntu-latest
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python: 39
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bitness: 64
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platform_id: manylinux_x86_64
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manylinux_image: manylinux1
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manylinux_image: manylinux2014
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# Linux 64 bit manylinux2010
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- os: ubuntu-latest
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bitness: 64
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platform_id: manylinux_x86_64
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manylinux_image: manylinux2010
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# NumPy on Python 3.10 only supports 64bit and is only available with manylinux2014
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- os: ubuntu-latest
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python: 310
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bitness: 64
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platform_id: manylinux_x86_64
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manylinux_image: manylinux2014
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# Linux 32 bit manylinux1
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# Linux 32 bit manylinux2014
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- os: ubuntu-latest
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python: 37
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bitness: 32
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platform_id: manylinux_i686
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manylinux_image: manylinux1
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manylinux_image: manylinux2014
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- os: ubuntu-latest
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python: 38
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bitness: 32
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platform_id: manylinux_i686
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manylinux_image: manylinux1
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manylinux_image: manylinux2014
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- os: ubuntu-latest
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python: 39
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bitness: 32
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platform_id: manylinux_i686
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manylinux_image: manylinux1
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manylinux_image: manylinux2014
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# Linux 32 bit manylinux2010
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- os: ubuntu-latest

‎pyproject.toml

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[build-system]
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# Minimum requirements for the build system to execute.
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requires = [
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"setuptools",
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"setuptools<60.0",
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"wheel",
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"Cython>=0.28.5",
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‎sklearn/linear_model/tests/test_quantile.py

Copy file name to clipboardExpand all lines: sklearn/linear_model/tests/test_quantile.py
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from sklearn.linear_model import HuberRegressor, QuantileRegressor
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from sklearn.metrics import mean_pinball_loss
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from sklearn.utils._testing import assert_allclose
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from sklearn.utils._testing import skip_if_32bit
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from sklearn.utils.fixes import parse_version, sp_version
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reg.fit(X, y)
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@skip_if_32bit
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@pytest.mark.skipif(
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sp_version <= parse_version("1.6.0"),
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reason="Solvers are available as of scipy 1.6.0",

‎sklearn/svm/tests/test_sparse.py

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assert_array_equal(clf_lin.predict(X_sp), clf_mylin.predict(X_sp))
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@skip_if_32bit
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def test_svc_iris():
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# Test the sparse SVC with the iris dataset
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for k in ("linear", "poly", "rbf"):

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