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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..10} )
inherit python-single-r1 cmake flag-o-matic
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 ffmpeg nnpack +numpy opencl opencv openmp qnnpack xnnpack"
RESTRICT="test"
REQUIRED_USE="
${PYTHON_REQUIRED_USE}
ffmpeg? ( opencv )
" # ?? ( cuda rocm )
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/foxi
cuda? (
=dev-libs/cudnn-8*
dev-libs/cudnn-frontend:0/8
dev-util/nvidia-cuda-toolkit:=[profiler]
)
ffmpeg? ( media-video/ffmpeg:= )
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 )
xnnpack? ( sci-libs/XNNPACK )
"
DEPEND="
${RDEPEND}
dev-cpp/eigen
dev-libs/psimd
dev-libs/FP16
dev-libs/FXdiv
dev-libs/pocketfft
dev-libs/flatbuffers
$(python_gen_cond_dep '
dev-python/pyyaml[${PYTHON_USEDEP}]
dev-python/pybind11[${PYTHON_USEDEP}]
')
"
S="${WORKDIR}"/${MYP}
PATCHES=(
"${FILESDIR}"/${P}-gentoo.patch
"${FILESDIR}"/${P}-install-dirs.patch
"${FILESDIR}"/${PN}-1.12.0-glog-0.6.0.patch
"${FILESDIR}"/${PN}-1.12.0-clang.patch
)
src_prepare() {
filter-lto #bug 862672
cmake_src_prepare
pushd torch/csrc/jit/serialization || die
flatc --cpp --gen-mutable --scoped-enums mobile_bytecode.fbs || die
popd
}
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="${TORCH_CUDA_ARCH_LIST:-3.5 7.0}"
-DUSE_DISTRIBUTED=OFF
-DUSE_FAKELOWP=OFF
-DUSE_FBGEMM=OFF # TODO
-DUSE_FFMPEG=$(usex ffmpeg)
-DUSE_GFLAGS=ON
-DUSE_GLOG=ON
-DUSE_GLOO=OFF
-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_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_VALGRIND=OFF
-DPYBIND11_PYTHON_VERSION="${EPYTHON#python}"
-DPYTHON_EXECUTABLE="${PYTHON}"
-DUSE_ITT=OFF
-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
-DUSE_TENSORPIPE=OFF
-Wno-dev
-DTORCH_INSTALL_LIB_DIR="${EPREFIX}"/usr/$(get_libdir)
-DLIBSHM_INSTALL_LIB_SUBDIR="${EPREFIX}"/usr/$(get_libdir)
)
use cuda && addpredict "/dev/nvidiactl" # bug 867706
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
rm -r "${ED}"/var/tmp || die
python_domodule python/caffe2
python_domodule python/torch
}
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