sci-libs/caffe2: add 2.3.1

Signed-off-by: Alfredo Tupone <tupone@gentoo.org>

2 files changed, 275 insertions, 0 deletions

diff --git a/sci-libs/caffe2/Manifest b/sci-libs/caffe2/Manifest
index d70fba8fc67b..246ab4d21a1a 100644
--- a/sci-libs/caffe2/Manifest
+++ b/sci-libs/caffe2/Manifest
@@ -1,2 +1,3 @@
 DIST pytorch-2.2.2.tar.gz 116367503 BLAKE2B 0be22f2ec4b9aac6f5e976664cae01facf07929a32565cd57d7cc5b2d9888e9ae71ca301853752fe8f31d174d04c9974eb9ed2f3d452360a50ccf024f200726a SHA512 7990e0f9484038c3458c0bda2c863bf2b19e56edab81fc5938c6e0f08b17558287f853bb67350e8cca8f42bec0f1d4ba0e94e50a145db8da44bdd4bd703d91d0
 DIST pytorch-2.3.0.tar.gz 117029829 BLAKE2B 8f9c0d71ee0a9219b495eddccdcc65107f7ad537c43c68100b229f3d27b0e6c01ccb1659c7fffc356a48d80f2adc0a10361305dc8f1df20446de837d380f89f6 SHA512 67f7e9a096c3ffb952206ebf9105bedebb68c24ad82456083adf1d1d210437fcaa9dd52b68484cfc97d408c9eebc9541c76868c34a7c9982494dc3f424cfb07c
+DIST pytorch-2.3.1.tar.gz 117035696 BLAKE2B d419d7fa1342f1fb317ffce09ec9dc1447414627cc83d36578fe60f68c283c620b2b4d49f414cd206d537b90b16432a06cd1941662720db05d5e2b6c493325f5 SHA512 e1bcae44f9939fc7ccb1360a9b1970d92426f25e5de73e36964df3dd15ad5d8d9f5bd2f9a7dda6b8f64e2bba3674005bd869f542489cc442ad0125a02676f587
diff --git a/sci-libs/caffe2/caffe2-2.3.1.ebuild b/sci-libs/caffe2/caffe2-2.3.1.ebuild
new file mode 100644
index 000000000000..c01e904d8eb0
--- /dev/null
+++ b/sci-libs/caffe2/caffe2-2.3.1.ebuild
@@ -0,0 +1,274 @@
+# Copyright 2022-2024 Gentoo Authors
+# Distributed under the terms of the GNU General Public License v2
+
+EAPI=8
+
+PYTHON_COMPAT=( python3_{10..12} )
+ROCM_VERSION=5.7
+inherit python-single-r1 cmake cuda flag-o-matic prefix rocm
+
+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
+	-> ${MYP}.tar.gz"
+
+S="${WORKDIR}"/${MYP}
+
+LICENSE="BSD"
+SLOT="0"
+KEYWORDS="~amd64"
+IUSE="cuda distributed fbgemm ffmpeg flash gloo mkl mpi nnpack +numpy onednn openblas opencl opencv openmp qnnpack rocm xnnpack"
+RESTRICT="test"
+REQUIRED_USE="
+	${PYTHON_REQUIRED_USE}
+	ffmpeg? ( opencv )
+	mpi? ( distributed )
+	gloo? ( distributed )
+	?? ( cuda rocm )
+	rocm? (
+		|| ( ${ROCM_REQUIRED_USE} )
+		!flash
+	)
+"
+
+# 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
+	virtual/lapack
+	sci-libs/onnx
+	sci-libs/foxi
+	cuda? (
+		dev-libs/cudnn
+		>=dev-libs/cudnn-frontend-1.0.3:0/8
+		<dev-util/nvidia-cuda-toolkit-12.4.0:=[profiler]
+	)
+	fbgemm? ( >=dev-libs/FBGEMM-2023.12.01 )
+	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}]
+		') )
+	onednn? ( dev-libs/oneDNN )
+	opencl? ( virtual/opencl )
+	opencv? ( media-libs/opencv:= )
+	qnnpack? ( sci-libs/QNNPACK )
+	rocm? (
+		>=dev-util/hip-5.7
+		>=dev-libs/rccl-5.7[${ROCM_USEDEP}]
+		>=sci-libs/rocThrust-5.7[${ROCM_USEDEP}]
+		>=sci-libs/rocPRIM-5.7[${ROCM_USEDEP}]
+		>=sci-libs/hipBLAS-5.7[${ROCM_USEDEP}]
+		>=sci-libs/hipFFT-5.7[${ROCM_USEDEP}]
+		>=sci-libs/hipSPARSE-5.7[${ROCM_USEDEP}]
+		>=sci-libs/hipRAND-5.7[${ROCM_USEDEP}]
+		>=sci-libs/hipCUB-5.7[${ROCM_USEDEP}]
+		>=sci-libs/hipSOLVER-5.7[${ROCM_USEDEP}]
+		>=sci-libs/miopen-5.7[${ROCM_USEDEP}]
+		>=dev-util/roctracer-5.7[${ROCM_USEDEP}]
+	)
+	distributed? ( sci-libs/tensorpipe[cuda?] )
+	xnnpack? ( >=sci-libs/XNNPACK-2022.12.22 )
+	mkl? ( sci-libs/mkl )
+	openblas? ( sci-libs/openblas )
+"
+DEPEND="
+	${RDEPEND}
+	cuda? ( >=dev-libs/cutlass-3.4.1 )
+	onednn? ( sci-libs/ideep )
+	dev-libs/psimd
+	dev-libs/FP16
+	dev-libs/FXdiv
+	dev-libs/pocketfft
+	dev-libs/flatbuffers
+	>=sci-libs/kineto-0.4.0_p20231031
+	$(python_gen_cond_dep '
+		dev-python/pyyaml[${PYTHON_USEDEP}]
+		dev-python/pybind11[${PYTHON_USEDEP}]
+		dev-python/typing-extensions[${PYTHON_USEDEP}]
+	')
+"
+
+PATCHES=(
+	"${FILESDIR}"/${PN}-2.2.1-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
+	"${FILESDIR}"/${P}-cudnn_include_fix.patch
+	"${FILESDIR}"/${PN}-2.1.2-fix-rpath.patch
+	"${FILESDIR}"/${PN}-2.1.2-fix-openmp-link.patch
+	"${FILESDIR}"/${P}-rocm-fix-std-cpp17.patch
+	"${FILESDIR}"/${PN}-2.2.2-musl.patch
+	"${FILESDIR}"/${P}-CMakeFix.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
+
+	if use rocm; then
+		sed -e "s:/opt/rocm:/usr:" \
+			-e "s:lib/cmake:$(get_libdir)/cmake:g" \
+			-e "s/HIP 1.0/HIP 1.0 REQUIRED/" \
+			-i cmake/public/LoadHIP.cmake || die
+
+		ebegin "HIPifying cuda sources"
+		${EPYTHON} tools/amd_build/build_amd.py || die
+		eend $?
+	fi
+}
+
+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_DISTRIBUTED=$(usex distributed)
+		-DUSE_MPI=$(usex mpi)
+		-DUSE_FAKELOWP=OFF
+		-DUSE_FBGEMM=$(usex fbgemm)
+		-DUSE_FFMPEG=$(usex ffmpeg)
+		-DUSE_FLASH_ATTENTION=$(usex flash)
+		-DUSE_GFLAGS=ON
+		-DUSE_GLOG=ON
+		-DUSE_GLOO=$(usex gloo)
+		-DUSE_KINETO=OFF # TODO
+		-DUSE_LEVELDB=OFF
+		-DUSE_MAGMA=OFF # TODO: In GURU as sci-libs/magma
+		-DUSE_MKLDNN=$(usex onednn)
+		-DUSE_NNPACK=$(usex nnpack)
+		-DUSE_QNNPACK=$(usex qnnpack)
+		-DUSE_XNNPACK=$(usex xnnpack)
+		-DUSE_SYSTEM_XNNPACK=$(usex xnnpack)
+		-DUSE_TENSORPIPE=$(usex distributed)
+		-DUSE_PYTORCH_QNNPACK=OFF
+		-DUSE_NUMPY=$(usex numpy)
+		-DUSE_OPENCL=$(usex opencl)
+		-DUSE_OPENCV=$(usex opencv)
+		-DUSE_OPENMP=$(usex openmp)
+		-DUSE_ROCM=$(usex rocm)
+		-DUSE_SYSTEM_CPUINFO=ON
+		-DUSE_SYSTEM_PYBIND11=ON
+		-DUSE_UCC=OFF
+		-DUSE_VALGRIND=OFF
+		-DPYBIND11_PYTHON_VERSION="${EPYTHON#python}"
+		-DPYTHON_EXECUTABLE="${PYTHON}"
+		-DUSE_ITT=OFF
+		-DUSE_SYSTEM_PTHREADPOOL=ON
+		-DUSE_SYSTEM_FXDIV=ON
+		-DUSE_SYSTEM_FP16=ON
+		-DUSE_SYSTEM_GLOO=ON
+		-DUSE_SYSTEM_ONNX=ON
+		-DUSE_SYSTEM_SLEEF=ON
+		-DUSE_METAL=OFF
+
+		-Wno-dev
+		-DTORCH_INSTALL_LIB_DIR="${EPREFIX}"/usr/$(get_libdir)
+		-DLIBSHM_INSTALL_LIB_SUBDIR="${EPREFIX}"/usr/$(get_libdir)
+	)
+
+	if use mkl; then
+		mycmakeargs+=(-DBLAS=MKL)
+	elif use openblas; then
+		mycmakeargs+=(-DBLAS=OpenBLAS)
+	else
+		mycmakeargs+=(-DBLAS=Generic -DBLAS_LIBRARIES=)
+	fi
+
+	if use cuda; then
+		addpredict "/dev/nvidiactl" # bug 867706
+		addpredict "/dev/char"
+		addpredict "/proc/self/task" # bug 926116
+
+		mycmakeargs+=(
+			-DUSE_CUDNN=ON
+			-DTORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST:-3.5 7.0}"
+			-DUSE_NCCL=OFF # TODO: NVIDIA Collective Communication Library
+			-DCMAKE_CUDA_FLAGS="$(cuda_gccdir -f | tr -d \")"
+		)
+	elif use rocm; then
+		export PYTORCH_ROCM_ARCH="$(get_amdgpu_flags)"
+
+		mycmakeargs+=(
+			-DUSE_NCCL=ON
+			-DUSE_SYSTEM_NCCL=ON
+		)
+	fi
+
+	if use onednn; then
+		mycmakeargs+=(
+			-DUSE_MKLDNN=ON
+			-DMKLDNN_FOUND=ON
+			-DMKLDNN_LIBRARIES=dnnl
+			-DMKLDNN_INCLUDE_DIR="${ESYSROOT}/usr/include/oneapi/dnnl"
+		)
+	fi
+
+	cmake_src_configure
+
+	# do not rerun cmake and the build process in src_install
+	sed '/RERUN/,+1d' -i "${BUILD_DIR}"/build.ninja || die
+}
+
+src_install() {
+	cmake_src_install
+
+	insinto "/var/lib/${PN}"
+	doins "${BUILD_DIR}"/CMakeCache.txt
+
+	rm -rf python
+	mkdir -p python/torch/include || die
+	mv "${ED}"/usr/lib/python*/site-packages/caffe2 python/ || die
+	cp torch/version.py python/torch/ || die
+	python_domodule python/caffe2
+	python_domodule python/torch
+	ln -s ../../../../../include/torch \
+		"${D}$(python_get_sitedir)"/torch/include/torch || die # bug 923269
+}