scikit-learn · jjerphan · Nov 3, 2022 · Oct 2, 2022 · Oct 2, 2022 · Oct 2, 2022
diff --git a/MANIFEST.in b/MANIFEST.in
@@ -1,7 +1,7 @@
 include *.rst
 recursive-include doc *
 recursive-include examples *
-recursive-include sklearn *.c *.h *.pyx *.pxd *.pxi *.tp
+recursive-include sklearn *.c *.cpp *.h *.pyx *.pxd *.pxi *.tp
 recursive-include sklearn/datasets *.csv *.csv.gz *.rst *.jpg *.txt *.arff.gz *.json.gz
 include COPYING
 include README.rst

diff --git a/azure-pipelines.yml b/azure-pipelines.yml
@@ -106,27 +106,6 @@ jobs:
         LOCK_FILE: './build_tools/azure/python_nogil_lock.txt'
         COVERAGE: 'false'
 
-# Check compilation with intel C++ compiler (ICC)
-- template: build_tools/azure/posix.yml
-  parameters:
-    name: Linux_Nightly_ICC
-    vmImage: ubuntu-20.04
-    dependsOn: [git_commit, linting]
-    condition: |
-      and(
-        succeeded(),
-        not(contains(dependencies['git_commit']['outputs']['commit.message'], '[ci skip]')),
-        or(eq(variables['Build.Reason'], 'Schedule'),
-           contains(dependencies['git_commit']['outputs']['commit.message'], '[icc-build]')
-        )
-      )
-    matrix:
-      pylatest_conda_forge_mkl:
-        DISTRIB: 'conda'
-        LOCK_FILE: 'build_tools/azure/pylatest_conda_forge_mkl_no_coverage_linux-64_conda.lock'
-        COVERAGE: 'false'
-        BUILD_WITH_ICC: 'true'
-
 [icc-build]            Build & test with the Intel C compiler (ICC) 
 if sys.platform == "win32" and ("icc" in compiler or "icl" in compiler): 
     return ["/Qopenmp"] 
 elif sys.platform == "win32": 
     return ["/openmp"] 
 elif sys.platform in ("darwin", "linux") and "icc" in compiler: 
 [icc-build]            Build & test with the Intel C compiler (ICC) 
 if sys.platform == "win32" and ("icc" in compiler or "icl" in compiler): 
     return ["/Qopenmp"] 
 elif sys.platform == "win32": 
     return ["/openmp"] 
 elif sys.platform in ("darwin", "linux") and "icc" in compiler: 
 - template: build_tools/azure/posix-docker.yml
   parameters:
     name: Linux_Nightly_PyPy
@@ -182,7 +161,6 @@ jobs:
         DISTRIB: 'conda'
         LOCK_FILE: './build_tools/azure/py38_conda_forge_openblas_ubuntu_2204_linux-64_conda.lock'
         COVERAGE: 'false'
-        BUILD_WITH_ICC: 'false'
         SKLEARN_TESTS_GLOBAL_RANDOM_SEED: '0'  # non-default seed
 
 - template: build_tools/azure/posix.yml

diff --git a/build_tools/azure/install.sh b/build_tools/azure/install.sh
@@ -59,15 +59,6 @@ pre_python_environment_install() {
         export PYTHON_NOGIL_PATH="${PYTHON_NOGIL_CLONE_PATH}/python"
         cd $OLDPWD
 
-    elif [[ "$BUILD_WITH_ICC" == "true" ]]; then
-        wget https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
-        sudo apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
-        rm GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
-        sudo add-apt-repository "deb https://apt.repos.intel.com/oneapi all main"
-        sudo apt-get update
-        sudo apt-get install intel-oneapi-compiler-dpcpp-cpp-and-cpp-classic
-        source /opt/intel/oneapi/setvars.sh
-
     fi
 }
 
@@ -122,13 +113,6 @@ scikit_learn_install() {
         export LDFLAGS="$LDFLAGS -Wl,--sysroot=/"
     fi
 
-    if [[ "$BUILD_WITH_ICC" == "true" ]]; then
-        # The "build_clib" command is implicitly used to build "libsvm-skl".
-        # To compile with a different compiler, we also need to specify the
-        # compiler for this command
-        python setup.py build_ext --compiler=intelem -i build_clib --compiler=intelem
-    fi
-
     # TODO use a specific variable for this rather than using a particular build ...
     if [[ "$DISTRIB" == "conda-pip-latest" ]]; then
         # Check that pip can automatically build scikit-learn with the build

diff --git a/build_tools/azure/test_docs.sh b/build_tools/azure/test_docs.sh
@@ -8,8 +8,4 @@ elif [[ "$DISTRIB" == "ubuntu" || "$DISTRIB" == "pip-nogil" ]]; then
     source $VIRTUALENV/bin/activate
 fi
 

10000
-if [[ "$BUILD_WITH_ICC" == "true" ]]; then
-    source /opt/intel/oneapi/setvars.sh
-fi
-
 make test-doc
diff --git a/build_tools/azure/test_script.sh b/build_tools/azure/test_script.sh
@@ -11,10 +11,6 @@ elif [[ "$DISTRIB" == "ubuntu" || "$DISTRIB" == "debian-32" || "$DISTRIB" == "pi
     source $VIRTUALENV/bin/activate
 fi
 
-if [[ "$BUILD_WITH_ICC" == "true" ]]; then
-    source /opt/intel/oneapi/setvars.sh
-fi
-
 if [[ "$BUILD_REASON" == "Schedule" ]]; then
     # Enable global random seed randomization to discover seed-sensitive tests
     # only on nightly builds.
@@ -62,9 +58,6 @@ if [[ -n "$CHECK_WARNINGS" ]]; then
     # removes its usage
     TEST_CMD="$TEST_CMD -Wignore:tostring:DeprecationWarning"
 
-    # Python 3.10 deprecates distutils, which is imported by numpy internally
-    TEST_CMD="$TEST_CMD -Wignore:The\ distutils:DeprecationWarning"
-
     # Ignore distutils deprecation warning, used by joblib internally
     TEST_CMD="$TEST_CMD -Wignore:distutils\ Version\ classes\ are\ deprecated:DeprecationWarning"
 

diff --git a/build_tools/circle/list_versions.py b/build_tools/circle/list_versions.py
@@ -5,7 +5,7 @@
 import re
 import sys
 
-from distutils.version import LooseVersion
+from sklearn.utils.fixes import parse_version
 from urllib.request import urlopen
 
 
@@ -37,8 +37,8 @@ def get_file_extension(version):
         # The 'dev' branch should be explicitly handled
         return "zip"
 
-    current_version = LooseVersion(version)
-    min_zip_version = LooseVersion("0.24")
+    current_version = parse_version(version)
+    min_zip_version = parse_version("0.24")
 
     return "zip" if current_version >= min_zip_version else "pdf"
 
@@ -94,7 +94,7 @@ def get_file_size(version):
 # Output in order: dev, stable, decreasing other version
 seen = set()
 for name in NAMED_DIRS + sorted(
-    (k for k in dirs if k[:1].isdigit()), key=LooseVersion, reverse=True
+    (k for k in dirs if k[:1].isdigit()), key=parse_version, reverse=True
 ):
     version_num, file_size = dirs[name]
     if version_num in seen:

diff --git a/build_tools/github/build_wheels.sh b/build_tools/github/build_wheels.sh
@@ -31,11 +31,6 @@ if [[ "$RUNNER_OS" == "macOS" ]]; then
     export CFLAGS="$CFLAGS -I$PREFIX/include"
     export CXXFLAGS="$CXXFLAGS -I$PREFIX/include"
     export LDFLAGS="$LDFLAGS -Wl,-rpath,$PREFIX/lib -L$PREFIX/lib -lomp"
-    # Disable the use of setuptools's vendored copy distutils when invoking setuptools
-    # See: https://setuptools.pypa.io/en/latest/deprecated/distutils-legacy.html
-    # TODO: remove the definition of this environment variable when no
-    # reference to distutils exist in the code-base for building scikit-learn.
-    export SETUPTOOLS_USE_DISTUTILS=stdlib
 fi
 
 # The version of the built dependencies are specified

diff --git a/doc/computing/computational_performance.rst b/doc/computing/computational_performance.rst
@@ -278,10 +278,9 @@ BLAS implementation and lead to orders of magnitude speedup over a
 non-optimized BLAS.
 
 You can display the BLAS / LAPACK implementation used by your NumPy / SciPy /
-scikit-learn install with the following commands::
+scikit-learn install with the following command::
 
-    from numpy import show_config
-    show_config()
+    python -c "import sklearn; sklearn.show_versions()"
 
 Optimized BLAS / LAPACK implementations include:
  - Atlas (need hardware specific tuning by rebuilding on the target machine)

diff --git a/doc/developers/advanced_installation.rst b/doc/developers/advanced_installation.rst
@@ -461,75 +461,6 @@ the base system and these steps will not be necessary.
 .. _conda environment: https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html
 .. _Miniforge3: https://github.com/conda-forge/miniforge#miniforge3
 
-Alternative compilers
-=====================
-
-The command:
-
-.. prompt:: bash $
-
-    pip install --verbose --editable .
-
-will build scikit-learn using your default C/C++ compiler. If you want to build
-scikit-learn with another compiler handled by ``distutils`` or by
-``numpy.distutils``, use the following command:
-
-.. prompt:: bash $
-
-    python setup.py build_ext --compiler=<compiler> -i build_clib --compiler=<compiler>
-
-To see the list of available compilers run:
-
-.. prompt:: bash $
-
-    python setup.py build_ext --help-compiler
-
-If your compiler is not listed here, you can specify it via the ``CC`` and
-``LDSHARED`` environment variables (does not work on windows):
-
-.. prompt:: bash $
-
-    CC=<compiler> LDSHARED="<compiler> -shared" python setup.py build_ext -i
-
-Building with Intel C Compiler (ICC) using oneAPI on Linux
-----------------------------------------------------------
-
-Intel provides access to all of its oneAPI toolkits and packages through a
-public APT repository. First you need to get and install the public key of this
-repository:
-
-.. prompt:: bash $
-
-    wget https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
-    sudo apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
-    rm GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
-
-Then, add the oneAPI repository to your APT repositories:
-
-.. prompt:: bash $
-
-    sudo add-apt-repository "deb https://apt.repos.intel.com/oneapi all main"
-    sudo apt-get update
-
-Install ICC, packaged under the name
-``intel-oneapi-compiler-dpcpp-cpp-and-cpp-classic``:
-
-.. prompt:: bash $
-
-    sudo apt-get install intel-oneapi-compiler-dpcpp-cpp-and-cpp-classic
-
-Before using ICC, you need to set up environment variables:
-
-.. prompt:: bash $
-
-    source /opt/intel/oneapi/setvars.sh
-
-Finally, you can build scikit-learn. For example on Linux x86_64:
-
-.. prompt:: bash $
-
-    python setup.py build_ext --compiler=intelem -i build_clib --compiler=intelem
-
 Parallel builds
 ===============
 

diff --git a/doc/developers/contributing.rst b/doc/developers/contributing.rst
@@ -549,7 +549,6 @@ message, the following actions are taken.
     [lint skip]            Azure pipeline skips linting
     [scipy-dev]            Build & test with our dependencies (numpy, scipy, etc ...) development builds
     [nogil]                Build & test with the nogil experimental branches of CPython, Cython, NumPy, SciPy...
-    [icc-build]            Build & test with the Intel C compiler (ICC)
     [pypy]                 Build & test with PyPy
     [float32]              Run float32 tests by setting `SKLEARN_RUN_FLOAT32_TESTS=1`. See :ref:`environment_variable` for more details
     [doc skip]             Docs are not built

diff --git a/maint_tools/check_pxd_in_installation.py b/maint_tools/check_pxd_in_installation.py
@@ -40,8 +40,7 @@
         f.write(
             textwrap.dedent(
                 """
-            from distutils.core import setup
-            from distutils.extension import Extension
+            from setuptools import setup, Extension
             from Cython.Build import cythonize
             import numpy
 

diff --git a/setup.cfg b/setup.cfg
@@ -1,3 +1,9 @@
+[options]
+packages = find_namespace:
+
+[options.packages.find]
+include = sklearn*
+
 [aliases]
 test = pytest