Install this version:
emerge -a =sci-ml/caffe2-cuda-2.12.0
If this version is masked, you can unmask it using the autounmask tool or standard emerge options:
autounmask =sci-ml/caffe2-cuda-2.12.0
Or alternatively:
emerge --autounmask-write -a =sci-ml/caffe2-cuda-2.12.0
| Version | EAPI | Keywords | Slot |
|---|---|---|---|
| 2.12.0 | 8 | ~amd64 | 0 |
# Copyright 2022-2026 Gentoo Authors
# Distributed under the terms of the GNU General Public License v2
# CUDA implementation of caffe2/PyTorch backend
EAPI=8
PYTHON_COMPAT=( python3_{11..14} )
inherit python-single-r1 cmake cuda flag-o-matic prefix
MY_PN=caffe2
MYPN=pytorch
MYP=${MYPN}-${PV}
FLASH_PV=2.7.4
FLASH_PN=flash-attention
FLASH_P=${FLASH_PN}-${FLASH_PV}
FLASH_ATT_URI="https://github.com/Dao-AILab/${FLASH_PN}/archive/refs/tags/v${FLASH_PV}.tar.gz -> ${FLASH_P}.gh.tar.gz"
DESCRIPTION="A deep learning framework (CUDA backend)"
HOMEPAGE="https://pytorch.org/"
SRC_URI="
https://github.com/pytorch/${MYPN}/archive/refs/tags/v${PV}.tar.gz -> ${MYP}.tar.gz
flash? ( ${FLASH_ATT_URI} )
memefficient? ( ${FLASH_ATT_URI} )
"
S="${WORKDIR}"/${MYP}
LICENSE="BSD"
SLOT="0"
KEYWORDS="~amd64"
IUSE="cusparselt distributed fbgemm flash gloo kineto memefficient
mimalloc mkl mpi nnpack +numpy onednn openblas opencl openmp qnnpack
xnnpack"
RESTRICT="test"
REQUIRED_USE="
${PYTHON_REQUIRED_USE}
mpi? ( distributed )
gloo? ( distributed )
"
RDEPEND="
${PYTHON_DEPS}
app-eselect/eselect-caffe2
dev-cpp/abseil-cpp:=
dev-cpp/gflags:=
>=dev-cpp/glog-0.5.0:=
>=dev-libs/cpuinfo-2025.11.14
dev-libs/libfmt:=
dev-libs/protobuf:=
dev-libs/sleef
sci-ml/onnx
virtual/lapack
dev-libs/cudnn
>=sci-ml/cudnn-frontend-1.12.0:=
>=dev-util/nvidia-cuda-toolkit-12.9:=[profiler]
cusparselt? ( dev-libs/cusparselt )
fbgemm? ( >=sci-ml/FBGEMM-1.4 )
gloo? ( >=sci-ml/gloo-2025.06.04[cuda] )
kineto? ( ~sci-ml/kineto-0.4.0_p20260323 )
mimalloc? ( dev-libs/mimalloc )
mpi? ( virtual/mpi )
nnpack? ( sci-ml/NNPACK dev-libs/pthreadpool )
numpy? ( $(python_gen_cond_dep 'dev-python/numpy[${PYTHON_USEDEP}]') )
onednn? ( sci-ml/oneDNN )
opencl? ( virtual/opencl )
qnnpack? ( !sci-libs/QNNPACK sci-ml/gemmlowp dev-libs/pthreadpool )
distributed? ( sci-ml/tensorpipe[cuda] dev-cpp/cpp-httplib:= )
xnnpack? ( >=sci-ml/XNNPACK-2024.11 dev-libs/pthreadpool )
mkl? ( sci-libs/mkl )
openblas? ( sci-libs/openblas )
"
DEPEND="
${RDEPEND}
dev-cpp/nlohmann_json
dev-libs/flatbuffers
dev-libs/FXdiv
dev-libs/pocketfft
dev-libs/psimd
sci-ml/FP16
$(python_gen_cond_dep '
<dev-python/pybind11-3.0.5[${PYTHON_USEDEP}]
dev-python/pyyaml[${PYTHON_USEDEP}]
dev-python/typing-extensions[${PYTHON_USEDEP}]
')
>=dev-libs/cutlass-3.9.2[tools(+)]
onednn? ( sci-ml/ideep )
qnnpack? ( dev-libs/clog )
"
PATCHES=(
"${FILESDIR}"/${MY_PN}-2.5.1-unbundle_fmt.patch
"${FILESDIR}"/${MY_PN}-2.5.1-unbundle_kineto.patch
"${FILESDIR}"/${MY_PN}-2.8.0-unbundle_pocketfft.patch
"${FILESDIR}"/${MY_PN}-2.5.1-cudnn_include_fix.patch
"${FILESDIR}"/${MY_PN}-2.4.0-cpp-httplib.patch
"${FILESDIR}"/${MY_PN}-2.5.1-glog-0.6.0.patch
"${FILESDIR}"/${MY_PN}-2.7.0-glog-0.7.1.patch
"${FILESDIR}"/${MY_PN}-2.9.1-torch_cpu.patch
"${FILESDIR}"/${MY_PN}-2.10.0-gentoo.patch
"${FILESDIR}"/${MY_PN}-2.11.0-mimalloc.patch
"${FILESDIR}"/${MY_PN}-2.12.0-removekineto-pr178960.patch
)
CAFFE2_PREFIX="/usr/lib/caffe2/cuda"
PYTORCH_PREFIX="/usr/lib/pytorch/cuda"
src_prepare() {
if use flash || use memefficient; then
mv "${WORKDIR}"/${FLASH_P}/* third_party/${FLASH_PN}/ || die
fi
filter-lto
sed -i \
-e 's|::fmt-header-only||' \
c10/CMakeLists.txt cmake/Dependencies.cmake torch/CMakeLists.txt || die
sed -e '/target_compile_options_if_supported(tensorpipe/d' -i cmake/Dependencies.cmake || die
sed -i \
-e '/add_subdirectory.*third_party/d' \
CMakeLists.txt cmake/Dependencies.cmake cmake/ProtoBuf.cmake \
aten/src/ATen/CMakeLists.txt || die
sed -i \
-e "/EXPORT/s|DESTINATION lib)|DESTINATION $(get_libdir))|" \
c10/cuda/CMakeLists.txt c10/CMakeLists.txt || die
sed -i 's/-Wextra-semi//' cmake/public/utils.cmake || die
cmake_src_prepare
pushd torch/csrc/jit/serialization > /dev/null || die
flatc --cpp --gen-mutable --scoped-enums mobile_bytecode.fbs || die
popd > /dev/null || die
hprefixify \
aten/CMakeLists.txt caffe2/CMakeLists.txt cmake/Metal.cmake \
cmake/Modules/*.cmake cmake/Modules_CUDA_fix/FindCUDNN.cmake \
cmake/Modules_CUDA_fix/upstream/FindCUDA/make2cmake.cmake \
cmake/Modules_CUDA_fix/upstream/FindPackageHandleStandardArgs.cmake \
cmake/public/cuda.cmake cmake/Dependencies.cmake \
torch/CMakeLists.txt CMakeLists.txt
}
src_configure() {
local mycmakeargs=(
-DCMAKE_INSTALL_PREFIX="${EPREFIX}${CAFFE2_PREFIX}"
-DCMAKE_INSTALL_RPATH="${EPREFIX}${CAFFE2_PREFIX}/$(get_libdir)"
-DCMAKE_BUILD_WITH_INSTALL_RPATH=ON
-DBUILD_CUSTOM_PROTOBUF=OFF
-DBUILD_TEST=OFF
-DLIBSHM_INSTALL_LIB_SUBDIR="${EPREFIX}${CAFFE2_PREFIX}/$(get_libdir)"
-DPython_EXECUTABLE="${PYTHON}"
-DTORCH_INSTALL_LIB_DIR="${EPREFIX}${CAFFE2_PREFIX}/$(get_libdir)"
-DUSE_CCACHE=OFF
-DUSE_CUDA=ON
-DUSE_ROCM=OFF
-DUSE_DISTRIBUTED=$(usex distributed)
-DUSE_FBGEMM=$(usex fbgemm)
-DUSE_FLASH_ATTENTION=$(usex flash)
-DUSE_GFLAGS=ON
-DUSE_GLOG=ON
-DUSE_GLOO=$(usex gloo)
-DUSE_ITT=OFF
-DUSE_KINETO=$(usex kineto)
-DUSE_KLEIDIAI=OFF
-DUSE_MAGMA=OFF
-DUSE_MEM_EFF_ATTENTION=$(usex memefficient)
-DUSE_MIMALLOC=$(usex mimalloc)
-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=$(usex qnnpack)
-DUSE_PYTORCH_METAL=OFF
-DUSE_SYSTEM_CPUINFO=ON
-DUSE_SYSTEM_EIGEN_INSTALL=ON
-DUSE_SYSTEM_FP16=ON
-DUSE_SYSTEM_FXDIV=ON
-DUSE_SYSTEM_GLOO=ON
-DUSE_SYSTEM_NVTX=ON
-DUSE_SYSTEM_ONNX=ON
-DUSE_SYSTEM_PSIMD=ON
-DUSE_SYSTEM_PTHREADPOOL=ON
-DUSE_SYSTEM_PYBIND11=ON
-DUSE_SYSTEM_SLEEF=ON
-DUSE_SYSTEM_XNNPACK=$(usex xnnpack)
-DUSE_TENSORPIPE=$(usex distributed)
-DUSE_UCC=OFF
-DUSE_VALGRIND=OFF
-DUSE_XNNPACK=$(usex xnnpack)
-DUSE_XPU=OFF
-DUSE_CUDNN=ON
-DTORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST:-6.1 7.5}"
-DUSE_CUSPARSELT=$(usex cusparselt)
-Wno-dev
)
if use mkl; then
mycmakeargs+=(-DBLAS=MKL)
elif use openblas; then
mycmakeargs+=(-DBLAS=OpenBLAS)
else
mycmakeargs+=(-DBLAS=Generic -DBLAS_LIBRARIES=)
fi
cuda_add_sandbox
addpredict "/dev/char/"
mycmakeargs+=( -DCMAKE_CUDA_FLAGS="$(cuda_gccdir -f | tr -d \")" )
[[ -v CUDACXX ]] && export PYTORCH_NVCC="${CUDACXX}"
if use flash; then
export FLASH_ATTENTION_FORCE_BUILD="TRUE"
export FLASH_ATTN_CUDA_ARCHS="${CUDAARCHS:-${TORCH_CUDA_ARCH_LIST:-6.1 7.5}}"
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/caffe2-cuda"
doins "${BUILD_DIR}"/CMakeCache.txt
rm -rf python
mkdir -p python/torch || die
cp torch/version.py python/torch/ || die
insinto "${PYTORCH_PREFIX}"
doins -r python/torch
dodir "${PYTORCH_PREFIX}/torch/bin"
dodir "${PYTORCH_PREFIX}/torch/lib"
dodir "${PYTORCH_PREFIX}/torch/include"
dosym "${CAFFE2_PREFIX}/include/torch" "${PYTORCH_PREFIX}/torch/include/torch"
dosym "${CAFFE2_PREFIX}/bin/torch_shm_manager" "${PYTORCH_PREFIX}/torch/bin/torch_shm_manager"
dosym "${CAFFE2_PREFIX}/$(get_libdir)/libtorch_global_deps.so" "${PYTORCH_PREFIX}/torch/lib/libtorch_global_deps.so"
}
pkg_postinst() {
local active
active=$(eselect caffe2 show 2>/dev/null)
if [[ "${active}" == "(unset)" || -z "${active}" ]]; then
eselect caffe2 set cuda
elog "caffe2 backend set to: cuda"
fi
}
Manage flags for this package:
euse -i <flag> -p sci-ml/caffe2-cuda |
euse -E <flag> -p sci-ml/caffe2-cuda |
euse -D <flag> -p sci-ml/caffe2-cuda
${RDEPEND}
dev-cpp/nlohmann_json
dev-libs/flatbuffers
dev-libs/FXdiv
dev-libs/pocketfft
dev-libs/psimd
sci-ml/FP16
$(python_gen_cond_dep '
<dev-python/pybind11-3.0.5[${PYTHON_USEDEP}]
dev-python/pyyaml[${PYTHON_USEDEP}]
dev-python/typing-extensions[${PYTHON_USEDEP}]
')
>=dev-libs/cutlass-3.9.2[tools(+)]
onednn? ( sci-ml/ideep )
qnnpack? ( dev-libs/clog )
${PYTHON_DEPS}
app-eselect/eselect-caffe2
dev-cpp/abseil-cpp:=
dev-cpp/gflags:=
>=dev-cpp/glog-0.5.0:=
>=dev-libs/cpuinfo-2025.11.14
dev-libs/libfmt:=
dev-libs/protobuf:=
dev-libs/sleef
sci-ml/onnx
virtual/lapack
dev-libs/cudnn
>=sci-ml/cudnn-frontend-1.12.0:=
>=dev-util/nvidia-cuda-toolkit-12.9:=[profiler]
cusparselt? ( dev-libs/cusparselt )
fbgemm? ( >=sci-ml/FBGEMM-1.4 )
gloo? ( >=sci-ml/gloo-2025.06.04[cuda] )
kineto? ( ~sci-ml/kineto-0.4.0_p20260323 )
mimalloc? ( dev-libs/mimalloc )
mpi? ( virtual/mpi )
nnpack? ( sci-ml/NNPACK dev-libs/pthreadpool )
numpy? ( $(python_gen_cond_dep 'dev-python/numpy[${PYTHON_USEDEP}]') )
onednn? ( sci-ml/oneDNN )
opencl? ( virtual/opencl )
qnnpack? ( !sci-libs/QNNPACK sci-ml/gemmlowp dev-libs/pthreadpool )
distributed? ( sci-ml/tensorpipe[cuda] dev-cpp/cpp-httplib:= )
xnnpack? ( >=sci-ml/XNNPACK-2024.11 dev-libs/pthreadpool )
mkl? ( sci-libs/mkl )
openblas? ( sci-libs/openblas )
| Type | File | Size | Source URLs |
|---|---|---|---|
| DIST | pytorch-2.12.0.tar.gz | 64740318 bytes | https://github.com/pytorch/pytorch/archive/refs/tags/v2.12.0.tar.gz |