130 lines
3.9 KiB
Nix
130 lines
3.9 KiB
Nix
{ lib
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, stdenv
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, pythonAtLeast
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, pythonOlder
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, fetchFromGitHub
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, python
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, buildPythonPackage
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, setuptools
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, numpy
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, llvmlite
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, libcxx
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, importlib-metadata
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, substituteAll
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, runCommand
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, config
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# CUDA-only dependencies:
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, addOpenGLRunpath ? null
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, cudaPackages ? {}
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# CUDA flags:
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, cudaSupport ? config.cudaSupport
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}:
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let
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inherit (cudaPackages) cudatoolkit;
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in buildPythonPackage rec {
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# Using an untagged version, with numpy 1.25 support, when it's released
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# also drop the versioneer patch in postPatch
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version = "0.59.0";
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pname = "numba";
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pyproject = true;
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disabled = pythonOlder "3.8" || pythonAtLeast "3.13";
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src = fetchFromGitHub {
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owner = "numba";
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repo = "numba";
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rev = "refs/tags/${version}";
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# Upstream uses .gitattributes to inject information about the revision
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# hash and the refname into `numba/_version.py`, see:
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#
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# - https://git-scm.com/docs/gitattributes#_export_subst and
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# - https://github.com/numba/numba/blame/5ef7c86f76a6e8cc90e9486487294e0c34024797/numba/_version.py#L25-L31
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#
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# Hence this hash may change if GitHub / Git will change it's behavior.
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# Hopefully this will not happen until the next release. We are fairly sure
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# that upstream relies on those strings to be valid, that's why we don't
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# use `forceFetchGit = true;`.` If in the future we'll observe the hash
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# changes too often, we can always use forceFetchGit, and inject the
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# relevant strings ourselves, using `sed` commands, in extraPostFetch.
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hash = "sha256-wd4TujPhV2Jy/HUUXLHAlcbVFm4gfQNWxWFXD+jeZC4=";
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};
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env.NIX_CFLAGS_COMPILE = lib.optionalString stdenv.isDarwin "-I${lib.getDev libcxx}/include/c++/v1";
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nativeBuildInputs = [
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numpy
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] ++ lib.optionals cudaSupport [
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addOpenGLRunpath
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];
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propagatedBuildInputs = [
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numpy
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llvmlite
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setuptools
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] ++ lib.optionals (pythonOlder "3.9") [
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importlib-metadata
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] ++ lib.optionals cudaSupport [
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cudatoolkit
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cudatoolkit.lib
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];
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patches = lib.optionals cudaSupport [
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(substituteAll {
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src = ./cuda_path.patch;
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cuda_toolkit_path = cudatoolkit;
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cuda_toolkit_lib_path = cudatoolkit.lib;
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})
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];
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postFixup = lib.optionalString cudaSupport ''
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find $out -type f \( -name '*.so' -or -name '*.so.*' \) | while read lib; do
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addOpenGLRunpath "$lib"
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patchelf --set-rpath "${cudatoolkit}/lib:${cudatoolkit.lib}/lib:$(patchelf --print-rpath "$lib")" "$lib"
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done
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'';
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# run a smoke test in a temporary directory so that
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# a) Python picks up the installed library in $out instead of the build files
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# b) we have somewhere to put $HOME so some caching tests work
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# c) it doesn't take 6 CPU hours for the full suite
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checkPhase = ''
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runHook preCheck
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pushd $(mktemp -d)
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HOME=. ${python.interpreter} -m numba.runtests -m $NIX_BUILD_CORES numba.tests.test_usecases
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popd
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runHook postCheck
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'';
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pythonImportsCheck = [
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"numba"
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];
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passthru.tests = {
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# CONTRIBUTOR NOTE: numba also contains CUDA tests, though these cannot be run in
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# this sandbox environment. Consider running similar commands to those below outside the
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# sandbox manually if you have the appropriate hardware; support will be detected
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# and the corresponding tests enabled automatically.
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# Also, the full suite currently does not complete on anything but x86_64-linux.
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fullSuite = runCommand "${pname}-test" {} ''
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pushd $(mktemp -d)
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# pip and python in $PATH is needed for the test suite to pass fully
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PATH=${python.withPackages (p: [ p.numba p.pip ])}/bin:$PATH
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HOME=$PWD python -m numba.runtests -m $NIX_BUILD_CORES
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popd
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touch $out # stop Nix from complaining no output was generated and failing the build
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'';
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};
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meta = with lib; {
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description = "Compiling Python code using LLVM";
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homepage = "https://numba.pydata.org/";
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license = licenses.bsd2;
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mainProgram = "numba";
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maintainers = with maintainers; [ fridh ];
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};
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}
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