nixpkgs/pkgs/development/libraries/science/math/tiny-cuda-nn/default.nix

159 lines
4.2 KiB
Nix

{
cmake,
cudaPackages,
fetchFromGitHub,
lib,
ninja,
python3Packages ? {},
pythonSupport ? false,
stdenv,
symlinkJoin,
which,
}: let
inherit (lib) lists strings;
inherit (cudaPackages) backendStdenv cudaFlags;
cuda-common-redist = with cudaPackages; [
cuda_cudart # cuda_runtime.h
libcublas # cublas_v2.h
libcusolver # cusolverDn.h
libcusparse # cusparse.h
];
cuda-native-redist = symlinkJoin {
name = "cuda-redist";
paths = with cudaPackages;
[cuda_nvcc]
++ cuda-common-redist;
};
cuda-redist = symlinkJoin {
name = "cuda-redist";
paths = cuda-common-redist;
};
in
stdenv.mkDerivation (finalAttrs: {
pname = "tiny-cuda-nn";
version = "1.6";
strictDeps = true;
format = strings.optionalString pythonSupport "setuptools";
src = fetchFromGitHub {
owner = "NVlabs";
repo = finalAttrs.pname;
rev = "v${finalAttrs.version}";
fetchSubmodules = true;
hash = "sha256-qW6Fk2GB71fvZSsfu+mykabSxEKvaikZ/pQQZUycOy0=";
};
nativeBuildInputs =
[
cmake
cuda-native-redist
ninja
which
]
++ lists.optionals pythonSupport (with python3Packages; [
pip
setuptools
wheel
]);
buildInputs =
[
cuda-redist
]
++ lib.optionals pythonSupport (
with python3Packages; [
pybind11
python
]
);
propagatedBuildInputs = lib.optionals pythonSupport (
with python3Packages; [
torch
]
);
# NOTE: We cannot use pythonImportsCheck for this module because it uses torch to immediately
# initailize CUDA and GPU access is not allowed in the nix build environment.
# NOTE: There are no tests for the C++ library or the python bindings, so we just skip the check
# phase -- we're not missing anything.
doCheck = false;
preConfigure = ''
export TCNN_CUDA_ARCHITECTURES="${
strings.concatStringsSep ";" (lists.map cudaFlags.dropDot cudaFlags.cudaCapabilities)
}"
export CUDA_HOME="${cuda-native-redist}"
export LIBRARY_PATH="${cuda-native-redist}/lib/stubs:$LIBRARY_PATH"
export CC="${backendStdenv.cc}/bin/cc"
export CXX="${backendStdenv.cc}/bin/c++"
'';
# When building the python bindings, we cannot re-use the artifacts from the C++ build so we
# skip the CMake confurePhase and the buildPhase.
dontUseCmakeConfigure = pythonSupport;
# The configurePhase usually puts you in the build directory, so for the python bindings we
# need to change directories to the source directory.
configurePhase = strings.optionalString pythonSupport ''
runHook preConfigure
mkdir -p "$NIX_BUILD_TOP/build"
cd "$NIX_BUILD_TOP/build"
runHook postConfigure
'';
buildPhase = strings.optionalString pythonSupport ''
runHook preBuild
python -m pip wheel \
--no-build-isolation \
--no-clean \
--no-deps \
--no-index \
--verbose \
--wheel-dir "$NIX_BUILD_TOP/build" \
"$NIX_BUILD_TOP/source/bindings/torch"
runHook postBuild
'';
installPhase =
''
runHook preInstall
mkdir -p "$out/lib"
''
# Installing the C++ library just requires copying the static library to the output directory
+ strings.optionalString (!pythonSupport) ''
cp libtiny-cuda-nn.a "$out/lib/"
''
# Installing the python bindings requires building the wheel and installing it
+ strings.optionalString pythonSupport ''
python -m pip install \
--no-build-isolation \
--no-cache-dir \
--no-deps \
--no-index \
--no-warn-script-location \
--prefix="$out" \
--verbose \
./*.whl
''
+ ''
runHook postInstall
'';
passthru = {
inherit cudaPackages;
};
meta = with lib; {
description = "Lightning fast C++/CUDA neural network framework";
homepage = "https://github.com/NVlabs/tiny-cuda-nn";
license = licenses.bsd3;
maintainers = with maintainers; [connorbaker];
platforms = platforms.linux;
};
})