scikit-learn · ogrisel · Dec 15, 2020 · Nov 7, 2020 · Nov 7, 2020 · Nov 7, 2020
diff --git a/.travis.yml b/.travis.yml
@@ -1,58 +1,101 @@
-# make it explicit that we favor the new container-based travis workers
+# Make it explicit that we favor the
+# new container-based Travis workers
 language: python
+dist: xenial
 
 cache:
   apt: true
   directories:
-  - $HOME/.cache/pip
-  - $HOME/.ccache
-
-dist: xenial
+    - $HOME/.cache/pip
+    - $HOME/.ccache
 
 env:
   global:
-    # Directory where tests are run from
-    - TEST_DIR=/tmp/sklearn
+    - CPU_COUNT=3
+    - TEST_DIR=/tmp/sklearn  # Test directory for continuous integration jobs
+    - PYTEST_VERSION=latest
     - OMP_NUM_THREADS=2
     - OPENBLAS_NUM_THREADS=2
-    - PYTEST_VERSION=latest
+    - SKLEARN_BUILD_PARALLEL=3
+    - SKLEARN_SKIP_NETWORK_TESTS=1
+    # Custom environment variables for the ARM wheel builder
+    - CIBW_BUILD_VERBOSITY=1
+    - CIBW_TEST_REQUIRES="pytest pytest-xdist threadpoolctl"
+    - CIBW_TEST_COMMAND="bash {project}/build_tools/travis/test_wheels.sh"
+    - CIBW_ENVIRONMENT="CPU_COUNT=8
+                        OMP_NUM_THREADS=2
+                        OPENBLAS_NUM_THREADS=2
+                        SKLEARN_BUILD_PARALLEL=8
+                        SKLEARN_SKIP_NETWORK_TESTS=1"
+    # Nightly upload token and staging upload token are set in Travis settings
+    - SCIKIT_LEARN_NIGHTLY_UPLOAD_TOKEN=__token__
+    - SCIKIT_LEARN_STAGING_UPLOAD_TOKEN=__token__
 
-matrix:
+jobs:
   include:
-    # Linux environment to test scikit-learn against numpy and scipy master
-    # installed from their CI wheels in a virtualenv with the Python
-    # interpreter provided by travis.
+    # Linux environment to test scikit-learn against NumPy and SciPy
+    # master installed from their continuous integration wheels in a
+    # virtual environment with Python interpreter provided by Travis.
     - python: 3.7
       env:
-        - CHECK_WARNINGS="true"
-        - CI_CPU_COUNT="3"
+        - CHECK_WARNINGS=true
       if: type = cron OR commit_message =~ /\[scipy-dev\]/
 
-    # As above but build scikit-learn with Intel C compiler (ICC).
     - python: 3.7
       env:
-        - CHECK_WARNING="true"
-        - BUILD_WITH_ICC="true"
-        - CI_CPU_COUNT="3"
+        - CHECK_WARNING=true
+        - BUILD_WITH_ICC=true
       if: type = cron OR commit_message =~ /\[icc-build\]/
 
     - python: 3.7
-      env:
-        - CI_CPU_COUNT="8"
       os: linux
       arch: arm64
       if: type = cron OR commit_message =~ /\[arm64\]/
+      env:
+        - CPU_COUNT=8
+
+    # Linux environments to build the scikit-learn wheels
+    # for the ARM64 arquitecture and Python 3.6 and newer
+    - python: 3.6
+      os: linux
+      arch: arm64
+      if: type = cron or commit_message =~ /\[cd build\]/
+      env:
+        - BUILD_WHEEL=true
+        - CIBW_BUILD=cp36-manylinux_aarch64
+
+    - python: 3.7
+      os: linux
+      arch: arm64
+      if: type = cron or commit_message =~ /\[cd build\]/
+      env:
+        - BUILD_WHEEL=true
+        - CIBW_BUILD=cp37-manylinux_aarch64
+
+    - python: 3.8
+      os: linux
+      arch: arm64
+      if: type = cron or commit_message =~ /\[cd build\]/
+      env:
+        - BUILD_WHEEL=true
+        - CIBW_BUILD=cp38-manylinux_aarch64
+
+    - python: 3.9
+      os: linux
+      arch: arm64
+      if: type = cron or commit_message =~ /\[cd build\]/
+      env:
+        - BUILD_WHEEL=true
+        - CIBW_BUILD=cp39-manylinux_aarch64
 
 install: source build_tools/travis/install.sh
-script:
-  - bash build_tools/travis/test_script.sh || travis_terminate 1
-  - bash build_tools/travis/test_docs.sh || travis_terminate 1
-  - bash build_tools/travis/test_pytest_soft_dependency.sh || travis_terminate 1
+script: source build_tools/travis/script.sh
 after_success: source build_tools/travis/after_success.sh
+
 notifications:
   webhooks:
     urls:
       - https://webhooks.gitter.im/e/4ffabb4df010b70cd624
-    on_success: change  # options: [always|never|change] default: always
-    on_failure: always  # options: [always|never|change] default: always
-    on_start: never     # options: [always|never|change] default: always
+    on_success: change
+    on_failure: always
+    on_start: never
diff --git a/build_tools/travis/after_success.sh b/build_tools/travis/after_success.sh
@@ -1,19 +1,24 @@
 #!/bin/bash
-# This script is meant to be called by the "after_success" step defined in
-# .travis.yml. See https://docs.travis-ci.com/ for more details.
    
-# License: 3-clause BSD
+# This script is meant to be called by the "after_success" step
+# defined in ".travis.yml". In particular, we upload the wheels
+# of the ARM64 architecture for the continuous deployment jobs.
 
 set -e
 
-if [[ "$COVERAGE" == "true" ]]; then
-    # Need to run codecov from a git checkout, so we copy .coverage
-    # from TEST_DIR where pytest has been run
-    cp $TEST_DIR/.coverage $TRAVIS_BUILD_DIR
+# The wheels cannot be uploaded on PRs
+if [[ $BUILD_WHEEL == true && $TRAVIS_EVENT_TYPE != pull_request ]]; then
+    if [ $TRAVIS_EVENT_TYPE == cron ]; then
+        ANACONDA_ORG="scipy-wheels-nightly"
+        ANACONDA_TOKEN="$SCIKIT_LEARN_NIGHTLY_UPLOAD_TOKEN"
+    else
+        ANACONDA_ORG="scikit-learn-wheels-staging"
+        ANACONDA_TOKEN="$SCIKIT_LEARN_STAGING_UPLOAD_TOKEN"
+    fi
 
-    # Ignore codecov failures as the codecov server is not
-    # very reliable but we don't want travis to report a failure
-    # in the github UI just because the coverage report failed to
-    # be published.
-    codecov --root $TRAVIS_BUILD_DIR || echo "codecov upload failed"
+    pip install git+https://github.com/Anaconda-Server/anaconda-client
+
+    # Force a replacement if the remote file already exists
+    anaconda -t $ANACONDA_TOKEN upload --force -u $ANACONDA_ORG wheelhouse/*.whl
+    echo "Index: https://pypi.anaconda.org/$ANACONDA_ORG/simple"
 fi
diff --git a/build_tools/travis/install.sh b/build_tools/travis/install.sh
@@ -1,111 +1,13 @@
 #!/bin/bash
-# This script is meant to be called by the "install" step defined in
-# .travis.yml. See https://docs.travis-ci.com/ for more details.
-    # The behavior of the script is controlled by environment variabled defined
-# in the .travis.yml in the top level folder of the project.
 
-# License: 3-clause BSD
-
-# Travis clone scikit-learn/scikit-learn repository in to a local repository.
-# We use a cached directory with three scikit-learn repositories (one for each
-# matrix entry) from which we pull from local Travis repository. This allows
-# us to keep build artefact for gcc + cython, and gain time
+# This script is meant to be called by the "install" step
+# defined in the ".travis.yml" file. In particular, it is
+# important that we call to the right installation script.
 
 set -e
 
-# Fail fast
-echo "CPU Arch: ${TRAVIS_CPU_ARCH}"
-
-# jq is used in travis_fastfail.sh, it's already pre-installed in non arm64
-# environments
-sudo apt-get install jq
-
-build_tools/travis/travis_fastfail.sh
-
-# Imports get_dep
-source build_tools/shared.sh
-
-echo "List files from cached directories"
-echo "pip:"
-ls $HOME/.cache/pip
-
-export CC=/usr/lib/ccache/gcc
-export CXX=/usr/lib/ccache/g++
-# Useful for debugging how ccache is used
-# export CCACHE_LOGFILE=/tmp/ccache.log
-# ~60M is used by .ccache when compiling from scratch at the time of writing
-ccache --max-size 100M --show-stats
-
-# Deactivate the travis-provided virtual environment and setup a
-# conda-based environment instead
-# If Travvis has language=generic, deactivate does not exist. `|| :` will pass.
-deactivate || :
-
-
-# Install miniconda
-if [[ "$TRAVIS_CPU_ARCH" == "arm64" ]]; then
-    wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-aarch64.sh -O miniconda.sh
+if [[ $BUILD_WHEEL == true ]]; then
+    source build_tools/travis/install_wheels.sh
 else
-    fname=Miniconda3-latest-Linux-x86_64.sh
-    wget https://repo.continuum.io/miniconda/$fname -O miniconda.sh
+    source build_tools/travis/install_master.sh
 fi
-MINICONDA_PATH=$HOME/miniconda
-chmod +x miniconda.sh && ./miniconda.sh -b -p $MINICONDA_PATH
-export PATH=$MINICONDA_PATH/bin:$PATH
-conda update --yes conda
-
-# Create environment and install dependencies
-conda create -n testenv --yes python=3.7
-
-source activate testenv
-
-if [[ "$TRAVIS_CPU_ARCH" == "amd64" ]]; then
-    pip install --upgrade pip setuptools
-    echo "Installing numpy and scipy master wheels"
-    dev_anaconda_url=https://pypi.anaconda.org/scipy-wheels-nightly/simple
-    pip install --pre --upgrade --timeout=60 --extra-index $dev_anaconda_url numpy scipy pandas
-    pip install --pre cython
-    echo "Installing joblib master"
-    pip install https://github.com/joblib/joblib/archive/master.zip
-    echo "Installing pillow master"
-    pip install https://github.com/python-pillow/Pillow/archive/master.zip
-else
-    conda install -y scipy numpy pandas cython
-    pip install joblib threadpoolctl
-fi
-
-pip install $(get_dep pytest $PYTEST_VERSION) pytest-cov pytest-xdist
-
-# Build scikit-learn in the install.sh script to collapse the verbose
-# build output in the travis output when it succeeds.
-python --version
-python -c "import numpy; print('numpy %s' % numpy.__version__)"
-python -c "import scipy; print('scipy %s' % scipy.__version__)"
-
-if [[ "$BUILD_WITH_ICC" == "true" ]]; then
-    wget https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS-2023.PUB
-    sudo apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS-2023.PUB
-    rm GPG-PUB-KEY-INTEL-SW-PRODUCTS-2023.PUB
-    sudo add-apt-repository "deb https://apt.repos.intel.com/oneapi all main"
-    sudo apt-get update
-    sudo apt-get install intel-oneapi-icc
-    source /opt/intel/oneapi/setvars.sh
-
-    # The build_clib command is implicitly used to build libsvm-skl. To compile
-    # with a different compiler we also need to specify the compiler for this
-    # command.
-    python setup.py build_ext --compiler=intelem -i -j "${CI_CPU_COUNT}" build_clib --compiler=intelem
-else
-    # Use setup.py instead of `pip install -e .` to be able to pass the -j flag
-    # to speed-up the building multicore CI machines.
-    python setup.py build_ext --inplace -j "${CI_CPU_COUNT}"
-fi
-
-python setup.py develop
-
-ccache --show-stats
-# Useful for debugging how ccache is used
-# cat $CCACHE_LOGFILE
-
-# fast fail
-build_tools/travis/travis_fastfail.sh
diff --git a/build_tools/travis/install_master.sh b/build_tools/travis/install_master.sh
@@ -0,0 +1,102 @@
+#!/bin/bash
+
+# Travis clone "scikit-learn/scikit-learn" repository into
+# a local repository. We use a cached directory with three
+# scikit-learn repositories (one for each matrix entry for
+# non continuous deployment jobs) from which we pull local
+# Travis repository. This allows us to keep build artifact
+# for GCC + Cython, and gain time.
+
+set -e
+
+echo "CPU Arch: $TRAVIS_CPU_ARCH."
+
+# Import "get_dep"
+source build_tools/shared.sh
+
+echo "List files from cached directories."
+echo "pip:"
+ls $HOME/.cache/pip
+
+export CC=/usr/lib/ccache/gcc
+export CXX=/usr/lib/ccache/g++
+
+# Useful for debugging how ccache is used
+# export CCACHE_LOGFILE=/tmp/ccache.log
+
+# 60MB are (more or less) used by .ccache, when
+# compiling from scratch at the time of writing
+ccache --max-size 100M --show-stats
+
+# Deactivate the default virtual environment
+# to setup a conda-based environment instead
+deactivate
+
+if [[ $TRAVIS_CPU_ARCH == arm64 ]]; then
+    # Different Miniconda URL for ARM64 architectures
+    MINICONDA_URL="https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-aarch64.sh"
+else
+    MINICONDA_URL="https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh"
+fi
+
+# Install Miniconda
+wget $MINICONDA_URL -O miniconda.sh
+MINICONDA_PATH=$HOME/miniconda
+chmod +x miniconda.sh && ./miniconda.sh -b -p $MINICONDA_PATH
+export PATH=$MINICONDA_PATH/bin:$PATH
+conda update --yes conda
+
+# Create environment and install dependencies
+conda create -n testenv --yes python=3.7
+
+source activate testenv
+
+if [[ $TRAVIS_CPU_ARCH == amd64 ]]; then
+    echo "Upgrading pip and setuptools."
+    pip install --upgrade pip setuptools
+    echo "Installing numpy, scipy and pandas master wheels."
+    dev_anaconda_url=https://pypi.anaconda.org/scipy-wheels-nightly/simple
+    pip install --pre --upgrade --timeout=60 --extra-index $dev_anaconda_url numpy scipy pandas
+    echo "Installing cython pre-release wheels."
+    pip install --pre cython
+    echo "Installing joblib master."
+    pip install https://github.com/joblib/joblib/archive/master.zip
+    echo "Installing pillow master."
+    pip install https://github.com/python-pillow/Pillow/archive/master.zip
+else
+    conda install -y scipy numpy pandas cython
+    pip install joblib threadpoolctl
+fi
+
+pip install $(get_dep pytest $PYTEST_VERSION) pytest-xdist
+
+# Build scikit-learn in this script to collapse the 
+# verbose build output in the Travis output when it
+# succeeds
+python --version
+python -c "import numpy; print(f'numpy {numpy.__version__}')"
+python -c "import scipy; print(f'scipy {scipy.__version__}')"
+
+if [[ $BUILD_WITH_ICC == true ]]; then
+    wget https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS-2023.PUB
+    sudo apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS-2023.PUB
+    rm GPG-PUB-KEY-INTEL-SW-PRODUCTS-2023.PUB
+    sudo add-apt-repository "deb https://apt.repos.intel.com/oneapi all main"
+    sudo apt-get update
+    sudo apt-get install intel-oneapi-icc
+    source /opt/intel/oneapi/setvars.sh
+
+    # The "build_clib" command is implicitly used to build "libsvm-skl".
+    # To compile with a different compiler, we also need to specify the
+    # compiler for this command
+    python setup.py build_ext --compiler=intelem -i build_clib --compiler=intelem
+else
+    pip install -e .
+fi
+
+python setup.py develop
+
+ccache --show-stats
+
+# Useful for debugging how ccache is used
+# cat $CCACHE_LOGFILE
diff --git a/build_tools/travis/install_wheels.sh b/build_tools/travis/install_wheels.sh
@@ -0,0 +1,6 @@
+#!/bin/bash
+
+set -e
+
+python -m pip install cibuildwheel
+python -m cibuildwheel --output-dir wheelhouse