simplify mkl_umath conda-forge build scripts

also use gnu_thread on Windows

Author: ndgrigorian

conda-recipe-cf/bld.bat

@@ -5,21 +5,5 @@ set "INCLUDE=%BUILD_PREFIX%\include;%INCLUDE%"
 set "CC=icx"
 set "CXX=icx"
 
-%PYTHON% -m build -w -n -x
-if %ERRORLEVEL% neq 0 exit 1
-
-for /f %%f in ('dir /b /S .\dist') do (
-    %PYTHON% -m pip install %%f ^
-        --no-build-isolation ^
-        --no-deps ^
-        --only-binary :all: ^
-        --no-index ^
-        --prefix %PREFIX% ^
-        -vv
-    if %ERRORLEVEL% neq 0 exit 1
-)
-
-if NOT "%WHEELS_OUTPUT_FOLDER%"=="" (
-    copy dist\mkl_umath*.whl %WHEELS_OUTPUT_FOLDER%
-    if %ERRORLEVEL% neq 0 exit 1
-)
+%PYTHON% -m pip install --no-build-isolation --no-deps --config-settings=setup-args="-Dmkl_threading=gnu_thread" .
+if errorlevel 1 exit 1

conda-recipe-cf/build.sh

@@ -1,26 +1,3 @@
-#!/bin/bash
-set -e
+#!/bin/bash -x
 
-# This is necessary to help DPC++ find Intel libraries such as SVML, IRNG, etc in build prefix
-export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:${BUILD_PREFIX}/lib"
-
-# Intel LLVM must cooperate with compiler and sysroot from conda
-echo "--gcc-toolchain=${BUILD_PREFIX} --sysroot=${BUILD_PREFIX}/${HOST}/sysroot -target ${HOST}" > icx_for_conda.cfg
-ICXCFG="$(pwd)/icx_for_conda.cfg"
-export ICXCFG
-
-read -r GLIBC_MAJOR GLIBC_MINOR <<< "$(conda list '^sysroot_linux-64$' \
-    | tail -n 1 | awk '{print $2}' | grep -oP '\d+' | head -n 2 | tr '\n' ' ')"
-
-export CMAKE_GENERATOR="Ninja"
-SKBUILD_ARGS=(
-    "--"
-    "-DCMAKE_C_COMPILER:PATH=icx"
-    "-DCMAKE_VERBOSE_MAKEFILE:BOOL=ON"
-    "-DMKL_THREADING=gnu_thread"
-)
-
-if [ -n "${WHEELS_OUTPUT_FOLDER}" ]; then
-    mkdir -p "${WHEELS_OUTPUT_FOLDER}"
-    cp dist/mkl_umath*.whl "${WHEELS_OUTPUT_FOLDER}"
-fi
+CC=icx CXX=icpx $PYTHON -m pip install --no-build-isolation --no-deps -Csetup-args="-Dmkl_threading=gnu_thread" .

conda-recipe-cf/meta.yaml

@@ -28,13 +28,11 @@ requirements:
       - cython
       - python
       - python-gil     # [py>=314]
-      - python-build
       - mkl-devel
       - numpy  # [not win]
       - numpy <2.4  # [win]
       # TODO: remove win numpy pin when numpy 2.5 is released, see https://github.com/numpy/numpy/issues/31337
       - llvm-openmp
-      - wheel  >=0.41.3
       - pip
     run:
       - python