8000 array API support for mean_poisson_deviance (#29227) · scikit-learn/scikit-learn@68b71b5 · GitHub
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EmilyXinyiogriselOmarManzoorlesteve
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array API support for mean_poisson_deviance (#29227)
Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> Co-authored-by: Omar Salman <omar.salman@arbisoft.com> Co-authored-by: Loïc Estève <loic.esteve@ymail.com>
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‎.github/workflows/cuda-ci.yml

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@@ -42,4 +42,4 @@ jobs:
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run: |
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source "${HOME}/conda/etc/profile.d/conda.sh"
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conda activate sklearn
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pytest -k 'array_api'
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SCIPY_ARRAY_API=1 pytest -k 'array_api'

‎azure-pipelines.yml

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@@ -138,6 +138,7 @@ jobs:
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# Here we make sure, that they are still run on a regular basis.
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${{ if eq(variables['Build.Reason'], 'Schedule') }}:
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SKLEARN_SKIP_NETWORK_TESTS: '0'
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SCIPY_ARRAY_API: '1'
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# Check compilation with Ubuntu 22.04 LTS (Jammy Jellyfish) and scipy from conda-forge
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# By default the CI is sequential, where `Ubuntu_Jammy_Jellyfish` runs first and
@@ -221,6 +222,7 @@ jobs:
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# makes sure that they are single threaded in each xdist subprocess.
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PYTEST_XDIST_VERSION: 'none'
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PIP_BUILD_ISOLATION: 'true'
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SCIPY_ARRAY_API: '1'
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- template: build_tools/azure/posix-docker.yml
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parameters:
@@ -259,6 +261,7 @@ jobs:
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DISTRIB: 'conda'
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LOCK_FILE: './build_tools/azure/pylatest_conda_forge_mkl_osx-64_conda.lock'
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SKLEARN_TESTS_GLOBAL_RANDOM_SEED: '5' # non-default seed
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SCIPY_ARRAY_API: '1'
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pylatest_conda_mkl_no_openmp:
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DISTRIB: 'conda'
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LOCK_FILE: './build_tools/azure/pylatest_conda_mkl_no_openmp_osx-64_conda.lock'

‎doc/modules/array_api.rst

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@@ -119,6 +119,7 @@ Metrics
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- :func:`sklearn.metrics.mean_absolute_error`
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- :func:`sklearn.metrics.mean_absolute_percentage_error`
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- :func:`sklearn.metrics.mean_gamma_deviance`
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- :func:`sklearn.metrics.mean_poisson_deviance` (requires `enabling array API support for SciPy <https://docs.scipy.org/doc/scipy/dev/api-dev/array_api.html#using-array-api-standard-support>`_)
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- :func:`sklearn.metrics.mean_squared_error`
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- :func:`sklearn.metrics.mean_tweedie_deviance`
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- :func:`sklearn.metrics.pairwise.additive_chi2_kernel`

‎doc/whats_new/v1.6.rst

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@@ -39,6 +39,7 @@ See :ref:`array_api` for more details.
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and :pr:`29143` by :user:`Tialo <Tialo>` and :user:`Loïc Estève <lesteve>`;
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- :func:`sklearn.metrics.mean_absolute_percentage_error` :pr:`29300` by :user:`Emily Chen <EmilyXinyi>`;
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- :func:`sklearn.metrics.mean_gamma_deviance` :pr:`29239` by :user:`Emily Chen <EmilyXinyi>`;
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- :func:`sklearn.metrics.mean_poisson_deviance` :pr:`29227` by :user:`Emily Chen <EmilyXinyi>`;
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- :func:`sklearn.metrics.mean_squared_error` :pr:`29142` by :user:`Yaroslav Korobko <Tialo>`;
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- :func:`sklearn.metrics.mean_tweedie_deviance` :pr:`28106` by :user:`Thomas Li <lithomas1>`;
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- :func:`sklearn.metrics.pairwise.additive_chi2_kernel` :pr:`29144` by :user:`Yaroslav Korobko <Tialo>`;

‎sklearn/metrics/tests/test_common.py

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@@ -76,7 +76,7 @@
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assert_array_less,
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ignore_warnings,
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)
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from sklearn.utils.fixes import COO_CONTAINERS
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from sklearn.utils.fixes import COO_CONTAINERS, parse_version, sp_version
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from sklearn.utils.multiclass import type_of_target
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from sklearn.utils.validation import _num_samples, check_random_state
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@@ -1867,6 +1867,12 @@ def check_array_api_multilabel_classification_metric(
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def check_array_api_regression_metric(metric, array_namespace, device, dtype_name):
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func_name = metric.func.__name__ if isinstance(metric, partial) else metric.__name__
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if func_name == "mean_poisson_deviance" and sp_version < parse_version("1.14.0"):
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pytest.skip(
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"mean_poisson_deviance's dependency `xlogy` is available as of scipy 1.14.0"
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)
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y_true_np = np.array([2.0, 0.1, 1.0, 4.0], dtype=dtype_name)
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y_pred_np = np.array([0.5, 0.5, 2, 2], dtype=dtype_name)
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@@ -2012,6 +2018,7 @@ def check_array_api_metric_pairwise(metric, array_namespace, device, dtype_name)
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check_array_api_regression_metric,
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],
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paired_cosine_distances: [check_array_api_metric_pairwise],
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mean_poisson_deviance: [check_array_api_regression_metric],
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additive_chi2_kernel: [check_array_api_metric_pairwise],
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mean_gamma_deviance: [check_array_api_regression_metric],
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max_error: [check_array_api_regression_metric],

‎sklearn/utils/_array_api.py

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@@ -5,6 +5,8 @@
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import itertools
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import math
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import os
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import warnings
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from functools import wraps
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import numpy
@@ -106,6 +108,17 @@ def _check_array_api_dispatch(array_api_dispatch):
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f"NumPy must be {min_numpy_version} or newer to dispatch array using"
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" the API specification"
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)
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if os.environ.get("SCIPY_ARRAY_API") != "1":
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warnings.warn(
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(
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"Some scikit-learn array API features might rely on enabling "
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"SciPy's own support for array API to function properly. "
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"Please set the SCIPY_ARRAY_API=1 environment variable "
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"before importing sklearn or scipy. More details at: "
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"https://docs.scipy.org/doc/scipy/dev/api-dev/array_api.html"
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),
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UserWarning,
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)
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def _single_array_device(array):

‎sklearn/utils/tests/test_array_api.py

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@@ -1,3 +1,4 @@
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import os
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import re
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from functools import partial
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@@ -77,7 +78,7 @@ def test_get_namespace_ndarray_with_dispatch():
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@skip_if_array_api_compat_not_configured
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def test_get_namespace_array_api():
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def test_get_namespace_array_api(monkeypatch):
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"""Test get_namespace for ArrayAPI arrays."""
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xp = pytest.importorskip("array_api_strict")
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@@ -90,6 +91,18 @@ def test_get_namespace_array_api():
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with pytest.raises(TypeError):
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xp_out, is_array_api_compliant = get_namespace(X_xp, X_np)
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def mock_getenv(key):
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if key == "SCIPY_ARRAY_API":
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return "0"
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monkeypatch.setattr("os.environ.get", mock_getenv)
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assert os.environ.get("SCIPY_ARRAY_API") != "1"
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with pytest.warns(
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UserWarning,
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match="enabling SciPy's own support for array API to function properly. ",
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):
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xp_out, is_array_api_compliant = get_namespace(X_xp)
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class _AdjustableNameAPITestWrapper(_ArrayAPIWrapper):
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"""API wrapper that has an adjustable name. Used for testing."""

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