path: root/sci-libs/caffe2/caffe2-2.5.1.ebuild

# 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=6.1
inherit python-single-r1 cmake cuda flag-o-matic prefix rocm toolchain-funcs

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 flash gloo mkl mpi nnpack +numpy onednn openblas opencl openmp qnnpack rocm xnnpack"
RESTRICT="test"
REQUIRED_USE="
	${PYTHON_REQUIRED_USE}
	mpi? ( distributed )
	gloo? ( distributed )
	?? ( cuda rocm )
	rocm? (
		|| ( ${ROCM_REQUIRED_USE} )
		!flash
	)
"

RDEPEND="
	${PYTHON_DEPS}
	dev-cpp/abseil-cpp:=
	dev-cpp/gflags:=
	>=dev-cpp/glog-0.5.0
	dev-libs/cpuinfo
	dev-libs/libfmt
	dev-cpp/opentelemetry-cpp
	dev-libs/protobuf:=
	dev-libs/pthreadpool
	dev-libs/sleef[cpu_flags_x86_avx512f(+),cpu_flags_x86_avx(+)]
	dev-libs/sleef[cpu_flags_x86_sse3(+),cpu_flags_x86_ssse3(+)]
	dev-libs/sleef[cpu_flags_x86_sse4_1(+),cpu_flags_x86_sse4_2(+)]
	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-12.5:=[profiler]
	)
	fbgemm? ( >=dev-libs/FBGEMM-2023.12.01 )
	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 )
	qnnpack? (
		!sci-libs/QNNPACK
		dev-cpp/gemmlowp
	)
	rocm? (
		=dev-util/hip-6.1*
		=dev-libs/rccl-6.1*[${ROCM_USEDEP}]
		=sci-libs/rocThrust-6.1*[${ROCM_USEDEP}]
		=sci-libs/rocPRIM-6.1*[${ROCM_USEDEP}]
		=sci-libs/hipBLAS-6.1*[${ROCM_USEDEP}]
		=sci-libs/hipFFT-6.1*[${ROCM_USEDEP}]
		=sci-libs/hipSPARSE-6.1*[${ROCM_USEDEP}]
		=sci-libs/hipRAND-6.1*[${ROCM_USEDEP}]
		=sci-libs/hipCUB-6.1*[${ROCM_USEDEP}]
		=sci-libs/hipSOLVER-6.1*[${ROCM_USEDEP}]
		=sci-libs/miopen-6.1*[${ROCM_USEDEP}]
		=dev-util/roctracer-6.1*[${ROCM_USEDEP}]

		=sci-libs/hipBLASLt-6.1*
		amdgpu_targets_gfx90a? ( =sci-libs/hipBLASLt-6.1*[amdgpu_targets_gfx90a] )
		amdgpu_targets_gfx940? ( =sci-libs/hipBLASLt-6.1*[amdgpu_targets_gfx940] )
		amdgpu_targets_gfx941? ( =sci-libs/hipBLASLt-6.1*[amdgpu_targets_gfx941] )
		amdgpu_targets_gfx942? ( =sci-libs/hipBLASLt-6.1*[amdgpu_targets_gfx942] )
	)
	distributed? (
		sci-libs/tensorpipe[cuda?]
		dev-cpp/cpp-httplib
	)
	xnnpack? ( >=sci-libs/XNNPACK-2024.02.29 )
	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_p20240525
	$(python_gen_cond_dep '
		dev-python/pyyaml[${PYTHON_USEDEP}]
		dev-python/pybind11[${PYTHON_USEDEP}]
		dev-python/typing-extensions[${PYTHON_USEDEP}]
	')
"

PATCHES=(
	"${FILESDIR}"/${P}-unbundle_fmt.patch
	"${FILESDIR}"/${P}-unbundle_kineto.patch
	"${FILESDIR}"/${P}-fix-functorch-install.patch
	"${FILESDIR}"/${P}-cudnn_include_fix.patch
	"${FILESDIR}"/${P}-gentoo.patch
	"${FILESDIR}"/${P}-cpp-httplib.patch
	"${FILESDIR}"/${P}-glog-0.6.0.patch
)

src_prepare() {
	filter-lto #bug 862672

	# Unbundle fmt
	sed -i \
		-e 's|::fmt-header-only||' \
		c10/CMakeLists.txt \
		cmake/Dependencies.cmake \
		torch/CMakeLists.txt \
		|| die
	# Drop third_party from CMake tree
	sed -i \
		-e '/add_subdirectory.*third_party/d' \
		CMakeLists.txt \
		cmake/Dependencies.cmake \
		cmake/ProtoBuf.cmake \
		aten/src/ATen/CMakeLists.txt \
		|| 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=(
		-DLIBSHM_INSTALL_LIB_SUBDIR="${EPREFIX}"/usr/$(get_libdir)
		-DPython_EXECUTABLE="${PYTHON}"
		-DTORCH_INSTALL_LIB_DIR="${EPREFIX}"/usr/$(get_libdir)
		-DUSE_CCACHE=OFF
		-DUSE_CUDA=$(usex cuda)
		-DUSE_DISTRIBUTED=$(usex distributed)
		-DUSE_FAKELOWP=OFF
		-DUSE_FBGEMM=$(usex fbgemm)
		-DUSE_FLASH_ATTENTION=$(usex flash)
		-DUSE_GFLAGS=ON
		-DUSE_GLOG=ON
		-DUSE_GLOO=$(usex gloo)
		-DUSE_ITT=OFF
		-DUSE_KINETO=OFF # TODO
		-DUSE_MAGMA=OFF # TODO: In GURU as sci-libs/magma
		-DUSE_MEM_EFF_ATTENTION=OFF
		-DUSE_MKLDNN=$(usex onednn)
		-DUSE_MPI=$(usex mpi)
		-DUSE_NCCL=OFF
		-DUSE_NNPACK=$(usex nnpack)
		-DUSE_NUMA=OFF
		-DUSE_NUMPY=$(usex numpy)
		-DUSE_OPENCL=$(usex opencl)
		-DUSE_OPENMP=$(usex openmp)
		-DUSE_PYTORCH_QNNPACK=$(usex qnnpack)
		-DUSE_PYTORCH_METAL=OFF
		-DUSE_ROCM=$(usex rocm)
		-DUSE_SYSTEM_LIBS=ON
		-DUSE_TENSORPIPE=$(usex distributed)
		-DUSE_UCC=OFF
		-DUSE_VALGRIND=OFF
		-DUSE_XNNPACK=$(usex xnnpack)
		-DUSE_XPU=OFF
		-Wno-dev
	)

	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
		)

		# ROCm libraries produce too much warnings
		append-cxxflags -Wno-deprecated-declarations -Wno-unused-result

		if tc-is-clang; then
			# fix mangling in LLVM: https://github.com/llvm/llvm-project/issues/85656
			append-cxxflags -fclang-abi-compat=17
		fi
	fi

	if use onednn; then
		mycmakeargs+=(
			-DMKLDNN_FOUND=ON
			-DMKLDNN_LIBRARIES=dnnl
			-DMKLDNN_INCLUDE_DIR="${ESYSROOT}/usr/include/oneapi/dnnl"
		)
	fi

	cmake_src_configure
}

src_compile() {
	PYTORCH_BUILD_VERSION=${PV} \
	PYTORCH_BUILD_NUMBER=0 \
	cmake_src_compile
}

src_install() {
	cmake_src_install

	insinto "/var/lib/${PN}"
	doins "${BUILD_DIR}"/CMakeCache.txt

	rm -rf python
	mkdir -p python/torch || die
	cp torch/version.py python/torch/ || die
	python_domodule python/torch

	dodir $(python_get_sitedir)/torch/bin
	dodir $(python_get_sitedir)/torch/lib
	dodir $(python_get_sitedir)/torch/include

	ln -s ../../../../../include/torch \
		"${D}$(python_get_sitedir)"/torch/include/torch || die # bug 923269


	mv "${ED}"/usr/bin/torch_shm_manager \
		"${ED}"/$(python_get_sitedir)/torch/bin/ || die

	mv "${ED}"/usr/$(get_libdir)/libtorch_global_deps.so \
		"${ED}"/$(python_get_sitedir)/torch/lib/ || die

	mv "${ED}"/usr/lib/libc10*.so \
		"${ED}"/usr/$(get_libdir)/ || die
}