10000 [CI] Add circleci build and test for arm64. (#20460) · rth/scikit-learn@7366abd · GitHub
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[CI] Add circleci build and test for arm64. (scikit-learn#20460)
 Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>
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‎.circleci/config.yml

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version: 2
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version: 2.1
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jobs:
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doc-min-dependencies:
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- ~/.ccache
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- ~/.cache/pip
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linux-arm64:
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machine:
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image: ubuntu-2004:202101-01
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resource_class: arm.medium
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environment:
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- OMP_NUM_THREADS: 2
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- OPENBLAS_NUM_THREADS: 2
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- CYTHON_VERSION: 'latest'
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- JOBLIB_VERSION: 'latest'
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- THREADPOOLCTL_VERSION: 'latest'
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- PYTEST_VERSION: 'latest'
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- PYTEST_XDIST_VERSION: 'latest'
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- TEST_DOCSTRINGS: 'true'
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steps:
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- checkout
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- run: ./build_tools/circle/checkout_merge_commit.sh
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- restore_cache:
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key: v1-datasets-{{ .Branch }}
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- run: ./build_tools/circle/build_test_arm.sh
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- save_cache:
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key: doc-ccache-{{ .Branch }}-{{ .BuildNum }}
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paths:
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- ~/.ccache
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- ~/.cache/pip
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- save_cache:
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key: v1-datasets-{{ .Branch }}
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paths:
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- ~/scikit_learn_data
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deploy:
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docker:
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- image: circleci/python:3.7
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- main
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jobs:
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- pypy3
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linux-arm64:
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jobs:
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- linux-arm64

‎.travis.yml

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jobs:
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include:
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# Manual trigger of linux/arm64 tests in PR without triggering the full
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# wheel building process for all the Python versions.
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- python: 3.9
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os: linux
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arch: arm64
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if: commit_message =~ /\[arm64\]/
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env:
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- CPU_COUNT=4
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# Linux environments to build the scikit-learn wheels for the ARM64
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# architecture and Python 3.7 and newer. This is used both at release time
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# with the manual trigger in the commit message in the release branch and as

‎build_tools/circle/build_test_arm.sh

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#!/bin/bash
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set -e
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set -x
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UNAMESTR=`uname`
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setup_ccache() {
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echo "Setting up ccache"
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mkdir /tmp/ccache/
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which ccache
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for name in gcc g++ cc c++ x86_64-linux-gnu-gcc x86_64-linux-gnu-c++; do
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ln -s $(which ccache) "/tmp/ccache/${name}"
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done
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export PATH="/tmp/ccache/:${PATH}"
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ccache -M 256M
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}
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# imports get_dep
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source build_tools/shared.sh
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sudo add-apt-repository --remove ppa:ubuntu-toolchain-r/test
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sudo apt-get update
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sudo apt-get install python3-virtualenv ccache
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python3 -m virtualenv --system-site-packages --python=python3 testenv
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source testenv/bin/activate
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pip install --upgrade pip
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setup_ccache
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python -m pip install $(get_dep cython $CYTHON_VERSION) \
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$(get_dep joblib $JOBLIB_VERSION)
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python -m pip install $(get_dep threadpoolctl $THREADPOOLCTL_VERSION) \
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$(get_dep pytest $PYTEST_VERSION) \
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$(get_dep pytest-xdist $PYTEST_XDIST_VERSION)
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if [[ "$COVERAGE" == "true" ]]; then
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python -m pip install codecov pytest-cov
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fi
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if [[ "$PYTEST_XDIST_VERSION" != "none" ]]; then
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python -m pip install pytest-xdist
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fi
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if [[ "$TEST_DOCSTRINGS" == "true" ]]; then
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# numpydoc requires sphinx
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python -m pip install sphinx
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python -m pip install numpydoc
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fi
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python --version
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# Set parallelism to 3 to overlap IO bound tasks with CPU bound tasks on CI
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# workers with 2 cores when building the compiled extensions of scikit-learn.
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export SKLEARN_BUILD_PARALLEL=3
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python -m pip list
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pip install --verbose --editable .
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ccache -s
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python -c "import sklearn; sklearn.show_versions()"
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python -m threadpoolctl --import sklearn
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python -m pytest sklearn

‎doc/developers/contributing.rst

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@@ -547,7 +547,7 @@ Continuous Integration (CI)
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* Azure pipelines are used for testing scikit-learn on Linux, Mac and Windows,
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with different dependencies and settings.
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* CircleCI is used to build the docs for viewing, for linting with flake8, and
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for testing with PyPy on Linux
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for testing with PyPy and ARM64 / aarch64 on Linux
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Please note that if one of the following markers appear in the latest commit
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message, the following actions are taken.
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[lint skip] Azure pipeline skips linting
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[scipy-dev] Add a Travis build with our dependencies (numpy, scipy, etc ...) development builds
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[icc-build] Add a Travis build with the Intel C compiler (ICC)
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[arm64] Add a Travis build for the ARM64 / aarch64 little endian architecture
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[doc skip] Docs are not built
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[doc quick] Docs built, but excludes example gallery plots
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[doc build] Docs built including example gallery plots (very long)

‎sklearn/manifold/tests/test_locally_linear.py

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def test_lle_simple_grid():
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# note: ARPACK is numerically unstable, so this test will fail for
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# some random seeds. We choose 2 because the tests pass.
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rng = np.random.RandomState(2)
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# some random seeds. We choose 42 because the tests pass.
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# for arm64 platforms 2 makes the test fail.
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# TODO: rewrite this test to make less sensitive to the random seed,
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# irrespective of the platform.
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rng = np.random.RandomState(42)
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# grid of equidistant points in 2D, n_components = n_dim
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X = np.array(list(product(range(5), repeat=2)))

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