From d858e58e5b139576c3be9ff35ea7583fc30d7dc7 Mon Sep 17 00:00:00 2001 From: Alfredo Tupone Date: Wed, 24 Dec 2025 14:12:47 +0100 Subject: [PATCH] sci-ml/caffe2: drop 2.9.0-r3 Signed-off-by: Alfredo Tupone --- sci-ml/caffe2/Manifest | 1 - sci-ml/caffe2/caffe2-2.9.0-r3.ebuild | 411 --------------------------- 2 files changed, 412 deletions(-) delete mode 100644 sci-ml/caffe2/caffe2-2.9.0-r3.ebuild diff --git a/sci-ml/caffe2/Manifest b/sci-ml/caffe2/Manifest index 17496b0e1fa20..71de6ac421f8d 100644 --- a/sci-ml/caffe2/Manifest +++ b/sci-ml/caffe2/Manifest @@ -2,5 +2,4 @@ DIST composable_kernel-7fe50dc3.tar.gz 5380728 BLAKE2B c89c346d8e2d7a93a9cf26409 DIST composable_kernel-8086bbe3.tar.gz 4418862 BLAKE2B b710e3d4586899443ec01044dad19fd2f992c351e2f65ba526dfcc47cc65c095beaf8ac21a8f71c02a0eb524d364e817b27241a9198884f2bdae9924b51e24e4 SHA512 8410b5a1c864d71f3034ef0d9d1245078856d09cc191faec59856c229bf11d89ae291036d735cb5cec4f1d72e6e9e8f6921833147f9619d30cfab8722d3a9f63 DIST flash-attention-2.7.4.gh.tar.gz 5841323 BLAKE2B 432999d763f2b3d732580ddfea5d3e01370351db0656546259a5e500a07516dd03c98828bfb55855dabe4adc651033b5d97ea4725ca46158b9970f0fbc662710 SHA512 05a4afb09e666f7404d6a3f8b5256e7bed6eba60a6f1bde2b7dbb96d318975f0b458c2521c7a38d88e97b6e4c27f29077cf787849daf82586e33f43a3d9a84b3 DIST pytorch-2.8.0.tar.gz 56565754 BLAKE2B a8f07513b92f9293f8322508f9fc73a462f89fe51cb1f280af371cee19cbe7e2bf900ba2b3c43fd08ea415566db441a6d6310d77f18477e957641be311a361a5 SHA512 448e9dad4aa10f1793d35e6ffe9f0f69b7719d41e6eccceb687a8d0c148e22d03e4f76170a05308ef9323a7aea41aa74605077ae1d68c6d949f13b3340ebf310 -DIST pytorch-2.9.0.tar.gz 55750268 BLAKE2B 943459ec60a4e1f5e36766defc7018fbf9722fb1564b723c2a7ebcb2a5d8b1735f0b1542dc67a77f788af3e2454ea6261dbdee5beb2bcfa4af2e58ca566edc93 SHA512 2ecdc0eac39ecee68b0f4c98e498424cde00c45bbeeff576c8778046f97119cd02885498b072352dd3cdd9aecd02baf61cdc5554bce8d757b30c673053a0cc80 DIST pytorch-2.9.1.tar.gz 55764697 BLAKE2B b22e154034f8a25aa3ef949eb6b0456777e11fe5f97de56c6112d93a2e154db425e97848911af458d179f03d7154956f53b715c7b9d7e7f074e0baceac35dad8 SHA512 d7098408d44e0fee9ded4afd6622df6f08757bf02eee878ae25b62a275f82eb16f96a07027c670c6ffdd431c8714c569249bd8518ac8828a504e99908b8c38b1 diff --git a/sci-ml/caffe2/caffe2-2.9.0-r3.ebuild b/sci-ml/caffe2/caffe2-2.9.0-r3.ebuild deleted file mode 100644 index c4e8ce27429e7..0000000000000 --- a/sci-ml/caffe2/caffe2-2.9.0-r3.ebuild +++ /dev/null @@ -1,411 +0,0 @@ -# Copyright 2022-2025 Gentoo Authors -# Distributed under the terms of the GNU General Public License v2 - -EAPI=8 - -PYTHON_COMPAT=( python3_{11..14} ) -ROCM_VERSION=6.1 -inherit python-single-r1 cmake cuda flag-o-matic prefix rocm toolchain-funcs - -MYPN=pytorch -MYP=${MYPN}-${PV} - -# caffe2-2.9.0 depends on future version of composable kernel -# TODO: replace it with DEPEND in the future -CK_COMMIT=7fe50dc3da2069d6645d9deb8c017a876472a977 -CK_P=composable_kernel-${CK_COMMIT:0:8} - -FLASH_PV=2.7.4 -FLASH_PN=flash-attention -FLASH_P=${FLASH_PN}-${FLASH_PV} -FLASH_ATT_URI="https://github.com/Dao-AILab/${FLASH_PN}/archive/refs/tags/v${FLASH_PV}.tar.gz -> ${FLASH_P}.gh.tar.gz" - -AOTRITON_PV=0.9.2b -AOTRITON_PN=aotriton -AOTRITON_P=${AOTRITON_PN}-${AOTRITON_PV} -AOTRITON_tar=${AOTRITON_P}-manylinux_2_28_x86_64-rocm6.3-shared.tar.gz - -DESCRIPTION="A deep learning framework" -HOMEPAGE="https://pytorch.org/" -SRC_URI=" - https://github.com/pytorch/${MYPN}/archive/refs/tags/v${PV}.tar.gz -> ${MYP}.tar.gz - rocm? ( - https://github.com/ROCm/composable_kernel/archive/${CK_COMMIT}.tar.gz - -> ${CK_P}.tar.gz - ) - cuda? ( - flash? ( ${FLASH_ATT_URI} ) - memefficient? ( ${FLASH_ATT_URI} ) - ) -" - -S="${WORKDIR}"/${MYP} - -LICENSE="BSD" -SLOT="0" -KEYWORDS="~amd64 ~arm64" -IUSE="cuda cusparselt distributed fbgemm flash gloo memefficient mkl mpi nccl 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? ( || ( cuda rocm ) ) - memefficient? ( || ( cuda rocm ) ) - nccl? ( rocm ) -" - -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/sleef - ~sci-ml/kineto-0.4.0_p20250617 - sci-ml/onnx - virtual/lapack - cuda? ( - 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 ) - gloo? ( >=sci-ml/gloo-2025.06.04[cuda?,rocm?] ) - mpi? ( virtual/mpi ) - nnpack? ( - sci-ml/NNPACK - dev-libs/pthreadpool - ) - numpy? ( $(python_gen_cond_dep ' - dev-python/numpy[${PYTHON_USEDEP}] - ') ) - onednn? ( =sci-ml/oneDNN-3.5* ) - opencl? ( virtual/opencl ) - qnnpack? ( - !sci-libs/QNNPACK - sci-ml/gemmlowp - dev-libs/pthreadpool - ) - rocm? ( - nccl? ( >=dev-libs/rccl-6.3:= =dev-util/hip-6.3:= =dev-util/roctracer-6.3:= =sci-libs/hipBLAS-6.3:= =sci-libs/hipBLASLt-6.3:= =sci-libs/hipFFT-6.3:= =sci-libs/hipRAND-6.3:= =sci-libs/hipSOLVER-6.3:= =sci-libs/hipSPARSE-6.3:= =sci-libs/miopen-6.3:= =sci-libs/rocBLAS-6.3:= =sci-libs/rocRAND-6.3:= =sci-libs/rocSOLVER-6.3:= =dev-util/rocm-smi-6.3:= =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 - $(python_gen_cond_dep ' - dev-python/pybind11[${PYTHON_USEDEP}] - dev-python/pyyaml[${PYTHON_USEDEP}] - dev-python/typing-extensions[${PYTHON_USEDEP}] - ') - cuda? ( >=dev-libs/cutlass-3.9.2[tools(+)] ) - onednn? ( sci-ml/ideep ) - rocm? ( - >=sci-libs/hipCUB-6.3:= =sci-libs/rocPRIM-6.3:= =sci-libs/rocThrust-6.3:= /dev/null || die - flatc --cpp --gen-mutable --scoped-enums mobile_bytecode.fbs || die - popd > /dev/null || die - - # 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:$(get_libdir)/cmake:g" \ - -i cmake/public/LoadHIP.cmake || die - - # TODO: delete, when caffe2 depends on systemwide composable_kernel - sed -e "s:third_party/composable_kernel:../composable_kernel-${CK_COMMIT}:g" \ - -i aten/src/ATen/CMakeLists.txt || die - - # Bug 959808: fix for gfx101x targets - pushd "${WORKDIR}/composable_kernel-${CK_COMMIT}" > /dev/null || die - eapply "${FILESDIR}"/composable-kernel-7fe50dc-expand-isa.patch - popd > /dev/null || die - - if tc-is-clang; then - # Systemwide gcc (for absl and at::TensorBase) + hipcc (llvm>=18) need abi-compat=17. - # But systemwide clang>=18 + hipcc (>=llvm-18) need opposite! - # See also: https://github.com/llvm/llvm-project/issues/102443#issuecomment-2329726287 - sed -e '/-fclang-abi-compat=17/d' -i cmake/Dependencies.cmake || die - fi - - # Workaround for libc++ issue https://github.com/llvm/llvm-project/issues/100802 - sed -e 's/std::memcpy/memcpy/g' -i torch/headeronly/util/Half.h || die - - # Typo: https://github.com/pytorch/pytorch/pull/166502 - sed -e 's/gloo_hiop/gloo_hip/' -i cmake/Modules/FindGloo.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_FBGEMM=$(usex fbgemm) - -DUSE_FLASH_ATTENTION=$(usex flash) - -DUSE_GFLAGS=ON - -DUSE_GLOG=ON - -DUSE_GLOO=$(usex gloo) - -DUSE_ITT=OFF - -DUSE_KINETO=ON - -DUSE_KLEIDIAI=OFF # TODO - -DUSE_MAGMA=OFF # TODO: In GURU as sci-libs/magma - -DUSE_MEM_EFF_ATTENTION=$(usex memefficient) - -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_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=$(usex xnnpack) - -DUSE_TENSORPIPE=$(use distributed && use !rocm && echo ON || echo OFF) - -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="$(cuda_gccdir -f | tr -d \")" - -DUSE_CUSPARSELT=$(usex cusparselt) - ) - elif use rocm; then - export PYTORCH_ROCM_ARCH="$(get_amdgpu_flags)" - - if use memefficient; then - export AOTRITON_INSTALLED_PREFIX="${ESYSROOT}/usr" - fi - - mycmakeargs+=( - -DUSE_NCCL=$(usex nccl) - -DUSE_SYSTEM_NCCL=ON - -DCMAKE_REQUIRE_FIND_PACKAGE_HIP=ON - -DUSE_ROCM_CK_SDPA=OFF # requires flash + aiter, works only on gfx90a/gfx942/gfx950 - ) - - # ROCm libraries produce too much warnings - append-cxxflags -Wno-deprecated-declarations -Wno-unused-result -Wno-unused-value - fi - - if use onednn; then - mycmakeargs+=( - -DMKLDNN_FOUND=ON - -DMKLDNN_LIBRARIES=dnnl - -DMKLDNN_INCLUDE_DIR="${ESYSROOT}/usr/include/oneapi/dnnl" - ) - fi - - cmake_src_configure -} - -src_compile() { - PYTORCH_BUILD_VERSION=${PV} \ - PYTORCH_BUILD_NUMBER=0 \ - cmake_src_compile -} - -python_install() { - python_domodule python/torch - mkdir "${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}$(python_get_sitedir)"/torch/include/torch || die # bug 923269 - ln -s ../../../../../bin/torch_shm_manager \ - "${D}"/$(python_get_sitedir)/torch/bin/torch_shm_manager || die - ln -s ../../../../../$(get_libdir)/libtorch_global_deps.so \ - "${D}"/$(python_get_sitedir)/torch/lib/libtorch_global_deps.so || die -} - -src_install() { - cmake_src_install - - # Used by pytorch ebuild - insinto "/var/lib/${PN}" - doins "${BUILD_DIR}"/CMakeCache.txt - dostrip -x /var/lib/${PN}/functorch.so - - rm -rf python - mkdir -p python/torch || die - cp torch/version.py python/torch/ || die - python_install -}