From 78fce155315439a69aa67573fd4696b735649431 Mon Sep 17 00:00:00 2001 From: V3n3RiX Date: Sat, 17 Feb 2024 23:37:36 +0000 Subject: gentoo auto-resync : 17:02:2024 - 23:37:36 --- sci-libs/caffe2/Manifest | 4 +- sci-libs/caffe2/caffe2-2.1.2-r3.ebuild | 239 -------------------------------- sci-libs/caffe2/caffe2-2.1.2-r4.ebuild | 242 +++++++++++++++++++++++++++++++++ sci-libs/caffe2/metadata.xml | 3 +- 4 files changed, 246 insertions(+), 242 deletions(-) delete mode 100644 sci-libs/caffe2/caffe2-2.1.2-r3.ebuild create mode 100644 sci-libs/caffe2/caffe2-2.1.2-r4.ebuild (limited to 'sci-libs/caffe2') diff --git a/sci-libs/caffe2/Manifest b/sci-libs/caffe2/Manifest index c2c10b6baed9..1f1dc1a1ba3f 100644 --- a/sci-libs/caffe2/Manifest +++ b/sci-libs/caffe2/Manifest @@ -17,5 +17,5 @@ DIST pytorch-2.0.1.tar.gz 111335778 BLAKE2B 7a10cc2b2d5e2422aef7e060a0c3a62ca5c7 DIST pytorch-2.1.2.tar.gz 116316469 BLAKE2B c5a55ee264bc3477d3556ba6376b5591117e992e56e0dd0c9ba93d12526e2727f7840f6f1e0730a38223b6492c9556840c4ebf22ffd220e97225c2abff303747 SHA512 a8961d78ad785b13c959a0612563a60e0de17a7c8bb9822ddea9a24072796354d07e81c47b6cc8761b21a6448845b088cf80e1661d9e889b0ed5474d3dc76756 EBUILD caffe2-1.13.1-r6.ebuild 5244 BLAKE2B d7f5f16e1f1122604a6df64f16c62552fb8b4b0de67bd231036b4835a5a71c58da02f0e1df64f3bd22c2a282a150d7f5a803c87cdf792e3e97ec8f518e055191 SHA512 58b1a09e5e3814d9475d4fe0e46aa837477843e09ed1b0c803c2ac3190e5c819d4216e33e3003652194e90a9f3f35146657eb25f30a4419bf16b2067e5a4b027 EBUILD caffe2-2.0.1-r5.ebuild 5868 BLAKE2B c17450d01ff68d42188c9da9e9c7a6d6469fe5c8b72c91e4ea4456eb4fe9d08cf30619fbb06f3dae21add641329f3ce8ced24bca93eb05900340639c042a1cdb SHA512 d32fa4c194c51efb76b143f22f783efa7a1415902b03ddea1d3f145d632455ebfe672a1b05b1203f2ba752f3331831455ae631a66bb409f45d6c695c68f39c3b -EBUILD caffe2-2.1.2-r3.ebuild 6727 BLAKE2B af5a9ce6ce416e3f3d2ece307f82b4a20e4904e5b21edb18a51a06f3cbb0bbbb19c58ee0729d219c8a62fa985b7911bf6cc03ffc179502aae7fabf52edc2d72a SHA512 54b726d75830ca48394d7ed062b4c32fa1a0514ebfc6a81553b6007044851e584911a509546f585b8a2443b27f1a8c2a8ea209f346d06b2715c82b5e5269f609 -MISC metadata.xml 1079 BLAKE2B 3ee99cd8aaef9260f6fe00f0a0fdd51b425e7386b8df8fee73c11c0a181ab24042057b3dfe35ba460865b81b30159a43db995fa6ec01d71e73088d7b4d0331d5 SHA512 f44df070ad8940a9ed423c9d2ea63ceeea9420e587efc8d4aed3a6ddaaf186edd86eefef421d71a8cd4c5ffce4e23351fd161de894016d1a660c9fa85ff84468 +EBUILD caffe2-2.1.2-r4.ebuild 6827 BLAKE2B 0d6bbb0a8c2f7831b8d20c8a04c35e07fd7a1fb3d09eef27088975765154b56f25ad3169f51aa1768ada5312a7d4a92749d263c56fc216fa5bf14dcecf7909fb SHA512 6ab281adc7181991c9f51fb02b8e49d03eca5ac41d687afeca66da02182f5e66cdcf35cc7d5f8ef64c564b0f362bbfcedad211da63d754474fc5a83fcda25569 +MISC metadata.xml 1161 BLAKE2B 77145d6b17a38da3fc791b85ec6d1d8a4faa5f08485f7b8d7918f301342c9d95b9b9db9147334788ffa5137526365d0161a5e1420eabafb2058e1d85a5fa52bb SHA512 44fa18ac5e1abcfb021e8fc48db1bb9c0f61bc115484ae6f293f38c48d1f42704524490c8e3977eec8dccb728837e1fcb3ce2e892986e55044af3a15e82a61e9 diff --git a/sci-libs/caffe2/caffe2-2.1.2-r3.ebuild b/sci-libs/caffe2/caffe2-2.1.2-r3.ebuild deleted file mode 100644 index 9b7554309dbc..000000000000 --- a/sci-libs/caffe2/caffe2-2.1.2-r3.ebuild +++ /dev/null @@ -1,239 +0,0 @@ -# Copyright 2022-2024 Gentoo Authors -# Distributed under the terms of the GNU General Public License v2 - -EAPI=8 - -PYTHON_COMPAT=( python3_{9..12} ) -inherit python-single-r1 cmake cuda flag-o-matic prefix - -MYPN=pytorch -MYP=${MYPN}-${PV} -IDEEP_VERSION="6f4d653802bd43bc4eda515460df9f90353dbebe" - -DESCRIPTION="A deep learning framework" -HOMEPAGE="https://pytorch.org/" -SRC_URI="https://github.com/pytorch/${MYPN}/archive/refs/tags/v${PV}.tar.gz -> ${MYP}.tar.gz -onednn? ( https://github.com/intel/ideep/archive/${IDEEP_VERSION}.tar.gz -> ideep-${IDEEP_VERSION}.tar.gz ) -" - -LICENSE="BSD" -SLOT="0" -KEYWORDS="~amd64" -IUSE="cuda distributed fbgemm ffmpeg gloo mkl mpi nnpack +numpy onednn opencl opencv openmp qnnpack tensorpipe xnnpack" -RESTRICT="test" -REQUIRED_USE=" - ${PYTHON_REQUIRED_USE} - ffmpeg? ( opencv ) - mpi? ( distributed ) - tensorpipe? ( distributed ) - distributed? ( tensorpipe ) - gloo? ( distributed ) -" # ?? ( cuda rocm ) - -# 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-1.12.0 - =dev-libs/cudnn-frontend-0.9.2:0/8 - dev-util/nvidia-cuda-toolkit:=[profiler] - ) - fbgemm? ( >=dev-libs/FBGEMM-2023.11.02 ) - 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 ) - tensorpipe? ( sci-libs/tensorpipe[cuda?] ) - xnnpack? ( >=sci-libs/XNNPACK-2022.12.22 ) - mkl? ( sci-libs/mkl ) -" -DEPEND=" - ${RDEPEND} - cuda? ( >=dev-libs/cutlass-3.1.0 ) - 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[${PYTHON_USEDEP}] - ') -" - -S="${WORKDIR}"/${MYP} - -PATCHES=( - "${FILESDIR}"/${PN}-2.1.1-gentoo.patch - "${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}"/${PN}-2.0.0-gcc13.patch - "${FILESDIR}"/${PN}-2.0.0-cudnn_include_fix.patch - "${FILESDIR}"/${PN}-2.1.1-cudaExtra.patch - "${FILESDIR}"/${PN}-2.1.2-fix-rpath.patch - "${FILESDIR}"/${PN}-2.1.2-fix-openmp-link.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 -} - -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_CUDNN=$(usex cuda) - -DTORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST:-3.5 7.0}" - -DBUILD_NVFUSER=$(usex cuda) - -DUSE_DISTRIBUTED=$(usex distributed) - -DUSE_MPI=$(usex mpi) - -DUSE_FAKELOWP=OFF - -DUSE_FBGEMM=$(usex fbgemm) - -DUSE_FFMPEG=$(usex ffmpeg) - -DUSE_GFLAGS=ON - -DUSE_GLOG=ON - -DUSE_GLOO=$(usex gloo) - -DUSE_KINETO=OFF # TODO - -DUSE_LEVELDB=OFF - -DUSE_MAGMA=OFF # TODO: In GURU as sci-libs/magma - -DUSE_MKLDNN=$(usex onednn) - -DUSE_NCCL=OFF # TODO: NVIDIA Collective Communication Library - -DUSE_NNPACK=$(usex nnpack) - -DUSE_QNNPACK=$(usex qnnpack) - -DUSE_XNNPACK=$(usex xnnpack) - -DUSE_SYSTEM_XNNPACK=$(usex xnnpack) - -DUSE_TENSORPIPE=$(usex tensorpipe) - -DUSE_PYTORCH_QNNPACK=OFF - -DUSE_NUMPY=$(usex numpy) - -DUSE_OPENCL=$(usex opencl) - -DUSE_OPENCV=$(usex opencv) - -DUSE_OPENMP=$(usex openmp) - -DUSE_ROCM=OFF # TODO - -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) - else - mycmakeargs+=(-DBLAS=Generic -DBLAS_LIBRARIES=) - fi - - if use cuda; then - addpredict "/dev/nvidiactl" # bug 867706 - addpredict "/dev/char" - - mycmakeargs+=( - -DCMAKE_CUDA_FLAGS="$(cuda_gccdir -f | tr -d \")" - ) - fi - - if use onednn; then - mycmakeargs+=( - -DUSE_MKLDNN=ON - -DMKLDNN_FOUND=ON - -DMKLDNN_LIBRARIES=dnnl - -DMKLDNN_INCLUDE_DIR="${ESYSROOT}/usr/include/oneapi/dnnl;${WORKDIR}/ideep-${IDEEP_VERSION}/include" - ) - fi - - cmake_src_configure -} - -src_install() { - cmake_src_install - - insinto "/var/lib/${PN}" - doins "${BUILD_DIR}"/CMakeCache.txt - - rm -rf python - mkdir -p python/torch/include || die - mv "${ED}"/usr/lib/python*/site-packages/caffe2 python/ || die - if use cuda; then - mv "${ED}${S}"/nvfuser python/nvfuser || die - mv "${ED}"/usr/$(get_libdir)/nvfuser.so python/nvfuser/_C.so || die - fi - cp torch/version.py python/torch/ || die - python_domodule python/caffe2 - python_domodule python/torch - ln -s ../../../../../include/torch \ - "${D}$(python_get_sitedir)"/torch/include/torch || die # bug 923269 - if use cuda; then - python_domodule python/nvfuser - fi - find "${ED}" -empty -delete -} diff --git a/sci-libs/caffe2/caffe2-2.1.2-r4.ebuild b/sci-libs/caffe2/caffe2-2.1.2-r4.ebuild new file mode 100644 index 000000000000..e4d9ad2932f3 --- /dev/null +++ b/sci-libs/caffe2/caffe2-2.1.2-r4.ebuild @@ -0,0 +1,242 @@ +# Copyright 2022-2024 Gentoo Authors +# Distributed under the terms of the GNU General Public License v2 + +EAPI=8 + +PYTHON_COMPAT=( python3_{9..12} ) +inherit python-single-r1 cmake cuda flag-o-matic prefix + +MYPN=pytorch +MYP=${MYPN}-${PV} +IDEEP_VERSION="6f4d653802bd43bc4eda515460df9f90353dbebe" + +DESCRIPTION="A deep learning framework" +HOMEPAGE="https://pytorch.org/" +SRC_URI="https://github.com/pytorch/${MYPN}/archive/refs/tags/v${PV}.tar.gz -> ${MYP}.tar.gz +onednn? ( https://github.com/intel/ideep/archive/${IDEEP_VERSION}.tar.gz -> ideep-${IDEEP_VERSION}.tar.gz ) +" + +LICENSE="BSD" +SLOT="0" +KEYWORDS="~amd64" +IUSE="cuda distributed fbgemm ffmpeg gloo mkl mpi nnpack +numpy onednn openblas opencl opencv openmp qnnpack tensorpipe xnnpack" +RESTRICT="test" +REQUIRED_USE=" + ${PYTHON_REQUIRED_USE} + ffmpeg? ( opencv ) + mpi? ( distributed ) + tensorpipe? ( distributed ) + distributed? ( tensorpipe ) + gloo? ( distributed ) +" # ?? ( cuda rocm ) + +# 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-1.12.0 + =dev-libs/cudnn-frontend-0.9.2:0/8 + dev-util/nvidia-cuda-toolkit:=[profiler] + ) + fbgemm? ( >=dev-libs/FBGEMM-2023.11.02 ) + 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 ) + tensorpipe? ( 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-3.1.0 ) + 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[${PYTHON_USEDEP}] + ') +" + +S="${WORKDIR}"/${MYP} + +PATCHES=( + "${FILESDIR}"/${PN}-2.1.1-gentoo.patch + "${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}"/${PN}-2.0.0-gcc13.patch + "${FILESDIR}"/${PN}-2.0.0-cudnn_include_fix.patch + "${FILESDIR}"/${PN}-2.1.1-cudaExtra.patch + "${FILESDIR}"/${PN}-2.1.2-fix-rpath.patch + "${FILESDIR}"/${PN}-2.1.2-fix-openmp-link.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 +} + +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_CUDNN=$(usex cuda) + -DTORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST:-3.5 7.0}" + -DBUILD_NVFUSER=$(usex cuda) + -DUSE_DISTRIBUTED=$(usex distributed) + -DUSE_MPI=$(usex mpi) + -DUSE_FAKELOWP=OFF + -DUSE_FBGEMM=$(usex fbgemm) + -DUSE_FFMPEG=$(usex ffmpeg) + -DUSE_GFLAGS=ON + -DUSE_GLOG=ON + -DUSE_GLOO=$(usex gloo) + -DUSE_KINETO=OFF # TODO + -DUSE_LEVELDB=OFF + -DUSE_MAGMA=OFF # TODO: In GURU as sci-libs/magma + -DUSE_MKLDNN=$(usex onednn) + -DUSE_NCCL=OFF # TODO: NVIDIA Collective Communication Library + -DUSE_NNPACK=$(usex nnpack) + -DUSE_QNNPACK=$(usex qnnpack) + -DUSE_XNNPACK=$(usex xnnpack) + -DUSE_SYSTEM_XNNPACK=$(usex xnnpack) + -DUSE_TENSORPIPE=$(usex tensorpipe) + -DUSE_PYTORCH_QNNPACK=OFF + -DUSE_NUMPY=$(usex numpy) + -DUSE_OPENCL=$(usex opencl) + -DUSE_OPENCV=$(usex opencv) + -DUSE_OPENMP=$(usex openmp) + -DUSE_ROCM=OFF # TODO + -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" + + mycmakeargs+=( + -DCMAKE_CUDA_FLAGS="$(cuda_gccdir -f | tr -d \")" + ) + fi + + if use onednn; then + mycmakeargs+=( + -DUSE_MKLDNN=ON + -DMKLDNN_FOUND=ON + -DMKLDNN_LIBRARIES=dnnl + -DMKLDNN_INCLUDE_DIR="${ESYSROOT}/usr/include/oneapi/dnnl;${WORKDIR}/ideep-${IDEEP_VERSION}/include" + ) + fi + + cmake_src_configure +} + +src_install() { + cmake_src_install + + insinto "/var/lib/${PN}" + doins "${BUILD_DIR}"/CMakeCache.txt + + rm -rf python + mkdir -p python/torch/include || die + mv "${ED}"/usr/lib/python*/site-packages/caffe2 python/ || die + if use cuda; then + mv "${ED}${S}"/nvfuser python/nvfuser || die + mv "${ED}"/usr/$(get_libdir)/nvfuser.so python/nvfuser/_C.so || die + fi + cp torch/version.py python/torch/ || die + python_domodule python/caffe2 + python_domodule python/torch + ln -s ../../../../../include/torch \ + "${D}$(python_get_sitedir)"/torch/include/torch || die # bug 923269 + if use cuda; then + python_domodule python/nvfuser + fi + find "${ED}" -empty -delete +} diff --git a/sci-libs/caffe2/metadata.xml b/sci-libs/caffe2/metadata.xml index 64d212edd735..3fe84b0977fc 100644 --- a/sci-libs/caffe2/metadata.xml +++ b/sci-libs/caffe2/metadata.xml @@ -10,15 +10,16 @@ Use FBGEMM Add support for video processing operators Use sci-libs/gloo + Use sci-libs/mkl for blas, lapack and sparse blas routines Use NNPACK Add support for math operations through numpy Use oneDNN + Use sci-libs/openblas for blas routines Add support for image processing operators Use OpenMP for parallel code Use QNNPACK Use tensorpipe Use XNNPACK - Use sci-libs/mkl for blas, lapack and sparse blas routines pytorch/pytorch -- cgit v1.2.3