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# Copyright 2022-2023 Gentoo Authors
# Distributed under the terms of the GNU General Public License v2
EAPI=8
PYTHON_COMPAT=( python3_{9..11} )
inherit python-single-r1 cmake cuda flag-o-matic prefix
MYPN=pytorch
MYP=${MYPN}-${PV}
DESCRIPTION="A deep learning framework"
HOMEPAGE="https://pytorch.org/"
SRC_URI="https://github.com/pytorch/${MYPN}/archive/refs/tags/v${PV}.tar.gz
-> ${MYP}.tar.gz"
LICENSE="BSD"
SLOT="0"
KEYWORDS="~amd64"
IUSE="cuda distributed fbgemm ffmpeg gloo mpi nnpack +numpy opencl opencv openmp qnnpack tensorpipe xnnpack"
RESTRICT="test"
REQUIRED_USE="
${PYTHON_REQUIRED_USE}
ffmpeg? ( opencv )
mpi? ( distributed )
tensorpipe? ( distributed )
distributed? ( tensorpipe )
gloo? ( distributed )
" # ?? ( cuda rocm )
# CUDA 12 not supported yet: https://github.com/pytorch/pytorch/issues/91122
RDEPEND="
${PYTHON_DEPS}
dev-cpp/gflags:=
>=dev-cpp/glog-0.5.0
dev-libs/cpuinfo
dev-libs/libfmt
dev-libs/protobuf:=
dev-libs/pthreadpool
dev-libs/sleef
sci-libs/lapack
>=sci-libs/onnx-1.12.0
<sci-libs/onnx-1.15.0
sci-libs/foxi
cuda? (
=dev-libs/cudnn-8*
dev-libs/cudnn-frontend:0/8
<dev-util/nvidia-cuda-toolkit-12:=[profiler]
)
fbgemm? ( dev-libs/FBGEMM )
ffmpeg? ( media-video/ffmpeg:= )
gloo? ( sci-libs/gloo[cuda?] )
mpi? ( virtual/mpi )
nnpack? ( sci-libs/NNPACK )
numpy? ( $(python_gen_cond_dep '
dev-python/numpy[${PYTHON_USEDEP}]
') )
opencl? ( virtual/opencl )
opencv? ( media-libs/opencv:= )
qnnpack? ( sci-libs/QNNPACK )
tensorpipe? ( sci-libs/tensorpipe[cuda?] )
xnnpack? ( >=sci-libs/XNNPACK-2022.12.22 )
"
DEPEND="
${RDEPEND}
dev-cpp/eigen
cuda? ( dev-libs/cutlass )
dev-libs/psimd
dev-libs/FP16
dev-libs/FXdiv
dev-libs/pocketfft
dev-libs/flatbuffers
sci-libs/kineto
$(python_gen_cond_dep '
dev-python/pyyaml[${PYTHON_USEDEP}]
dev-python/pybind11[${PYTHON_USEDEP}]
')
"
S="${WORKDIR}"/${MYP}
PATCHES=(
"${FILESDIR}"/${PN}-2.0.0-gentoo.patch
"${FILESDIR}"/${PN}-1.13.0-install-dirs.patch
"${FILESDIR}"/${PN}-1.12.0-glog-0.6.0.patch
"${FILESDIR}"/${PN}-1.13.1-tensorpipe.patch
"${FILESDIR}"/${PN}-2.0.0-gcc13.patch
"${FILESDIR}"/${PN}-2.0.0-cudnn_include_fix.patch
"${FILESDIR}"/${P}-cudaExtra.patch
)
src_prepare() {
filter-lto #bug 862672
sed -i \
-e "/third_party\/gloo/d" \
cmake/Dependencies.cmake \
|| die
cmake_src_prepare
pushd torch/csrc/jit/serialization || die
flatc --cpp --gen-mutable --scoped-enums mobile_bytecode.fbs || die
popd
# prefixify the hardcoded paths, after all patches are applied
hprefixify \
aten/CMakeLists.txt \
caffe2/CMakeLists.txt \
cmake/Metal.cmake \
cmake/Modules/*.cmake \
cmake/Modules_CUDA_fix/FindCUDNN.cmake \
cmake/Modules_CUDA_fix/upstream/FindCUDA/make2cmake.cmake \
cmake/Modules_CUDA_fix/upstream/FindPackageHandleStandardArgs.cmake \
cmake/public/LoadHIP.cmake \
cmake/public/cuda.cmake \
cmake/Dependencies.cmake \
torch/CMakeLists.txt \
CMakeLists.txt
}
src_configure() {
if use cuda && [[ -z ${TORCH_CUDA_ARCH_LIST} ]]; then
ewarn "WARNING: caffe2 is being built with its default CUDA compute capabilities: 3.5 and 7.0."
ewarn "These may not be optimal for your GPU."
ewarn ""
ewarn "To configure caffe2 with the CUDA compute capability that is optimal for your GPU,"
ewarn "set TORCH_CUDA_ARCH_LIST in your make.conf, and re-emerge caffe2."
ewarn "For example, to use CUDA capability 7.5 & 3.5, add: TORCH_CUDA_ARCH_LIST=7.5 3.5"
ewarn "For a Maxwell model GPU, an example value would be: TORCH_CUDA_ARCH_LIST=Maxwell"
ewarn ""
ewarn "You can look up your GPU's CUDA compute capability at https://developer.nvidia.com/cuda-gpus"
ewarn "or by running /opt/cuda/extras/demo_suite/deviceQuery | grep 'CUDA Capability'"
fi
local mycmakeargs=(
-DBUILD_CUSTOM_PROTOBUF=OFF
-DBUILD_SHARED_LIBS=ON
-DUSE_CCACHE=OFF
-DUSE_CUDA=$(usex cuda)
-DUSE_CUDNN=$(usex cuda)
-DUSE_FAST_NVCC=$(usex cuda)
-DTORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST:-3.5 7.0}"
-DBUILD_NVFUSER=$(usex cuda)
-DUSE_DISTRIBUTED=$(usex distributed)
-DUSE_MPI=$(usex mpi)
-DUSE_FAKELOWP=OFF
-DUSE_FBGEMM=$(usex fbgemm)
-DUSE_FFMPEG=$(usex ffmpeg)
-DUSE_GFLAGS=ON
-DUSE_GLOG=ON
-DUSE_GLOO=$(usex gloo)
-DUSE_KINETO=OFF # TODO
-DUSE_LEVELDB=OFF
-DUSE_MAGMA=OFF # TODO: In GURU as sci-libs/magma
-DUSE_MKLDNN=OFF
-DUSE_NCCL=OFF # TODO: NVIDIA Collective Communication Library
-DUSE_NNPACK=$(usex nnpack)
-DUSE_QNNPACK=$(usex qnnpack)
-DUSE_XNNPACK=$(usex xnnpack)
-DUSE_SYSTEM_XNNPACK=$(usex xnnpack)
-DUSE_TENSORPIPE=$(usex tensorpipe)
-DUSE_PYTORCH_QNNPACK=OFF
-DUSE_NUMPY=$(usex numpy)
-DUSE_OPENCL=$(usex opencl)
-DUSE_OPENCV=$(usex opencv)
-DUSE_OPENMP=$(usex openmp)
-DUSE_ROCM=OFF # TODO
-DUSE_SYSTEM_CPUINFO=ON
-DUSE_SYSTEM_PYBIND11=ON
-DUSE_UCC=OFF
-DUSE_VALGRIND=OFF
-DPYBIND11_PYTHON_VERSION="${EPYTHON#python}"
-DPYTHON_EXECUTABLE="${PYTHON}"
-DUSE_ITT=OFF
-DBLAS=Eigen # avoid the use of MKL, if found on the system
-DUSE_SYSTEM_EIGEN_INSTALL=ON
-DUSE_SYSTEM_PTHREADPOOL=ON
-DUSE_SYSTEM_FXDIV=ON
-DUSE_SYSTEM_FP16=ON
-DUSE_SYSTEM_GLOO=ON
-DUSE_SYSTEM_ONNX=ON
-DUSE_SYSTEM_SLEEF=ON
-Wno-dev
-DTORCH_INSTALL_LIB_DIR="${EPREFIX}"/usr/$(get_libdir)
-DLIBSHM_INSTALL_LIB_SUBDIR="${EPREFIX}"/usr/$(get_libdir)
)
if use cuda; then
addpredict "/dev/nvidiactl" # bug 867706
addpredict "/dev/char"
mycmakeargs+=(
-DCMAKE_CUDA_FLAGS="$(cuda_gccdir -f | tr -d \")"
)
fi
cmake_src_configure
}
src_install() {
cmake_src_install
insinto "/var/lib/${PN}"
doins "${BUILD_DIR}"/CMakeCache.txt
rm -rf python
mkdir -p python/torch/include || die
mv "${ED}"/usr/lib/python*/site-packages/caffe2 python/ || die
mv "${ED}"/usr/include/torch python/torch/include || die
cp torch/version.py python/torch/ || die
python_domodule python/caffe2
python_domodule python/torch
}
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