# 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-cpp/nlohmann_json dev-cpp/opentelemetry-cpp 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-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 "${FILESDIR}"/${PN}-2.4.0-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 ${TORCH_CUDA_ARCH_LIST} ]]; then ewarn "WARNING: caffe2 is being built with its default CUDA compute capabilities: 3.5 and 7.0." ewarn "These may not be optimal for your GPU." ewarn "" ewarn "To configure caffe2 with the CUDA compute capability that is optimal for your GPU," ewarn "set TORCH_CUDA_ARCH_LIST in your make.conf, and re-emerge caffe2." ewarn "For example, to use CUDA capability 7.5 & 3.5, add: TORCH_CUDA_ARCH_LIST=7.5 3.5" ewarn "For a Maxwell model GPU, an example value would be: TORCH_CUDA_ARCH_LIST=Maxwell" ewarn "" ewarn "You can look up your GPU's CUDA compute capability at https://developer.nvidia.com/cuda-gpus" ewarn "or by running /opt/cuda/extras/demo_suite/deviceQuery | grep 'CUDA Capability'" fi local mycmakeargs=( -DBUILD_CUSTOM_PROTOBUF=OFF -DLIBSHM_INSTALL_LIB_SUBDIR="${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=$(usex rocm) -DUSE_SYSTEM_CPUINFO=ON -DUSE_SYSTEM_EIGEN_INSTALL=ON -DUSE_SYSTEM_FP16=ON -DUSE_SYSTEM_FXDIV=ON -DUSE_SYSTEM_GLOO=ON -DUSE_SYSTEM_ONNX=ON -DUSE_SYSTEM_PSIMD=ON -DUSE_SYSTEM_PSIMD=ON -DUSE_SYSTEM_PTHREADPOOL=ON -DUSE_SYSTEM_PYBIND11=ON -DUSE_SYSTEM_SLEEF=ON -DUSE_SYSTEM_XNNPACK=$(usex xnnpack) -DUSE_TENSORPIPE=$(usex distributed) -DUSE_UCC=OFF -DUSE_VALGRIND=OFF -DUSE_XNNPACK=$(usex xnnpack) -DUSE_XPU=OFF -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 "${BUILD_DIR}"/CMakeCache.txt rm -rf python mkdir -p python/torch || die cp torch/version.py python/torch/ || die python_domodule python/torch mkdir "${D}"$(python_get_sitedir)/torch/bin || die mkdir "${D}"$(python_get_sitedir)/torch/lib || die mkdir "${D}"$(python_get_sitedir)/torch/include || die ln -s ../../../../../include/torch \ "${D}$(python_get_sitedir)"/torch/include/torch || die # bug 923269 mv "${D}"/usr/bin/torch_shm_manager \ "${D}"/$(python_get_sitedir)/torch/bin/ || die mv "${D}"/usr/$(get_libdir)/libtorch_global_deps.so \ "${D}"/$(python_get_sitedir)/torch/lib/ || die mv "${D}"/usr/lib/libc10*.so \ "${D}"/usr/$(get_libdir)/ || die }