## START: Set by rpmautospec ## (rpmautospec version 0.7.3) ## RPMAUTOSPEC: autorelease, autochangelog %define autorelease(e:s:pb:n) %{?-p:0.}%{lua: release_number = 1; base_release_number = tonumber(rpm.expand("%{?-b*}%{!?-b:1}")); print(release_number + base_release_number - 1); }%{?-e:.%{-e*}}%{?-s:.%{-s*}}%{!?-n:%{?dist}} ## END: Set by rpmautospec %global pypi_name torch # Where the src comes from %global forgeurl https://github.com/pytorch/pytorch # So pre releases can be tried %bcond_with gitcommit %if %{with gitcommit} # v2.5.0-rc9 %global commit0 417a0763a7d69f6ce80719ac89c1d2deeee78163 %global shortcommit0 %(c=%{commit0}; echo ${c:0:7}) %global date0 2024103 %global pypi_version 2.5.0 %else %global pypi_version 2.5.0 %endif # For -test subpackage # suitable only for local testing # Install and do something like # export LD_LIBRARY_PATH=/usr/lib64/python3.12/site-packages/torch/lib # /usr/lib64/python3.12/site-packages/torch/bin/test_api, test_lazy %bcond_with test %ifarch x86_64 %bcond_without rocm %endif %bcond_without hipblaslt %bcond_without magma %bcond_with rocm_loop %global rocm_default_gpu default %global rocm_gpu_list gfx9 # Caffe2 support came in F41 %if 0%{?fedora} > 40 %bcond_without caffe2 %else %bcond_with caffe2 %endif # Distributed support came in F41 %if 0%{?fedora} > 40 %bcond_without distributed # For testing distributed+rccl etc. %bcond_with rccl %bcond_with gloo %bcond_without mpi %bcond_without tensorpipe %else %bcond_with distributed %endif # Do no confuse xnnpack versions %if 0%{?fedora} > 40 %bcond_without xnnpack %else %bcond_with xnnpack %endif %bcond_without pthreadpool %bcond_without pocketfft %ifarch x86_64 %if %{with rocm} %bcond_with fbgemm %else %bcond_without fbgemm %endif %else %bcond_with fbgemm %endif # For testing cuda %ifarch x86_64 %bcond_with cuda %endif # Pick a CUDA version that works %global cuda_ver 12.5 # For testing compat-gcc %global compat_gcc_major 13 %bcond_with compat_gcc # Disable dwz with rocm because memory can be exhausted %if %{with rocm} %define _find_debuginfo_dwz_opts %{nil} %endif %if %{with cuda} # workaround problems with -pie %global build_cxxflags %{nil} %global build_ldflags %{nil} %endif # These came in 2.4 and not yet in Fedora %bcond_with opentelemetry %bcond_with httplib %bcond_with kineto Name: python-%{pypi_name} %if %{with gitcommit} Version: %{pypi_version}^git%{date0}.%{shortcommit0} %else Version: %{pypi_version} %endif Release: %autorelease Summary: PyTorch AI/ML framework # See license.txt for license details License: BSD-3-Clause AND BSD-2-Clause AND 0BSD AND Apache-2.0 AND MIT AND BSL-1.0 AND GPL-3.0-or-later AND Zlib URL: https://pytorch.org/ %if %{with gitcommit} Source0: %{forgeurl}/archive/%{commit0}/pytorch-%{shortcommit0}.tar.gz Source1000: pyproject.toml %else Source0: %{forgeurl}/releases/download/v%{version}/pytorch-v%{version}.tar.gz %endif Source1: https://github.com/google/flatbuffers/archive/refs/tags/v23.3.3.tar.gz Source2: https://github.com/pybind/pybind11/archive/refs/tags/v2.11.1.tar.gz %if %{with cuda} %global cuf_ver 1.1.2 Source10: https://github.com/NVIDIA/cudnn-frontend/archive/refs/tags/v%{cuf_ver}.tar.gz %global cul_ver 3.4.1 Source11: https://github.com/NVIDIA/cutlass/archive/refs/tags/v%{cul_ver}.tar.gz %endif # Developement on tensorpipe has stopped, repo made read only July 1, 2023, this is the last commit %global tp_commit 52791a2fd214b2a9dc5759d36725909c1daa7f2e %global tp_scommit %(c=%{tp_commit}; echo ${c:0:7}) Source20: https://github.com/pytorch/tensorpipe/archive/%{tp_commit}/tensorpipe-%{tp_scommit}.tar.gz # The old libuv tensorpipe uses Source21: https://github.com/libuv/libuv/archive/refs/tags/v1.41.0.tar.gz # Developement afaik on libnop has stopped, this is the last commit %global nop_commit 910b55815be16109f04f4180e9adee14fb4ce281 %global nop_scommit %(c=%{nop_commit}; echo ${c:0:7}) Source22: https://github.com/google/libnop/archive/%{nop_commit}/libnop-%{nop_scommit}.tar.gz %if %{without xnnpack} %global xnn_commit fcbf55af6cf28a4627bcd1f703ab7ad843f0f3a2 %global xnn_scommit %(c=%{xnn_commit}; echo ${c:0:7}) Source30: https://github.com/google/xnnpack/archive/%{xnn_commit}/xnnpack-%{xnn_scommit}.tar.gz %global fx_commit 63058eff77e11aa15bf531df5dd34395ec3017c8 %global fx_scommit %(c=%{fx_commit}; echo ${c:0:7}) Source31: https://github.com/Maratyszcza/fxdiv/archive/%{fx_commit}/FXdiv-%{fx_scommit}.tar.gz %global fp_commit 0a92994d729ff76a58f692d3028ca1b64b145d91 %global fp_scommit %(c=%{fp_commit}; echo ${c:0:7}) Source32: https://github.com/Maratyszcza/FP16/archive/%{fp_commit}/FP16-%{fp_scommit}.tar.gz %global ps_commit 072586a71b55b7f8c584153d223e95687148a900 %global ps_scommit %(c=%{ps_commit}; echo ${c:0:7}) Source33: https://github.com/Maratyszcza/psimd/archive/%{ps_commit}/psimd-%{ps_scommit}.tar.gz %global ci_commit 16bfc1622c6902d6f91d316ec54894910c620325 %global ci_scommit %(c=%{ci_commit}; echo ${c:0:7}) Source34: https://github.com/pytorch/cpuinfo/archive/%{ci_commit}/cpuinfo-%{ci_scommit}.tar.gz %endif %if %{without pthreadpool} %global pt_commit 4fe0e1e183925bf8cfa6aae24237e724a96479b8 %global pt_scommit %(c=%{pt_commit}; echo ${c:0:7}) Source40: https://github.com/Maratyszcza/pthreadpool/archive/%{pt_commit}/pthreadpool-%{pt_scommit}.tar.gz %endif %if %{without pocketfft} %global pf_commit 076cb3d2536b7c5d0629093ad886e10ac05f3623 %global pf_scommit %(c=%{pf_commit}; echo ${c:0:7}) Source50: https://github.com/mreineck/pocketfft/archive/%{pf_commit}/pocketfft-%{pf_scommit}.tar.gz %endif %if %{without opentelemetry} %global ot_ver 1.14.2 Source60: https://github.com/open-telemetry/opentelemetry-cpp/archive/refs/tags/v%{ot_ver}.tar.gz %endif %if %{without httplib} %global hl_commit 3b6597bba913d51161383657829b7e644e59c006 %global hl_scommit %(c=%{hl_commit}; echo ${c:0:7}) Source70: https://github.com/yhirose/cpp-httplib/archive/%{hl_commit}/cpp-httplib-%{hl_scommit}.tar.gz %endif %if %{without kineto} %global ki_commit be1317644c68b4bfc4646024a6b221066e430031 %global ki_scommit %(c=%{ki_commit}; echo ${c:0:7}) Source80: https://github.com/pytorch/kineto/archive/%{ki_commit}/kineto-%{ki_scommit}.tar.gz %endif Patch11: 0001-Improve-finding-and-using-the-rocm_version.h.patch # ROCm patches # Patches need to be refactored for ToT # These are ROCm packages %if %{without cuda} # https://github.com/pytorch/pytorch/pull/120551 %if %{without hipblaslt} Patch100: 0001-Optionally-use-hipblaslt.patch %endif Patch101: 0001-cuda-hip-signatures.patch %endif ExclusiveArch: x86_64 aarch64 %global toolchain gcc %global _lto_cflags %nil BuildRequires: cmake BuildRequires: binutils-gold BuildRequires: eigen3-devel %if %{with fbgemm} BuildRequires: asmjit-devel BuildRequires: fbgemm-devel %endif BuildRequires: flexiblas-devel BuildRequires: fmt-devel %if %{with caffe2} BuildRequires: foxi-devel %endif %if %{with compat_gcc} BuildRequires: gcc%{compat_gcc_major}-c++ BuildRequires: gcc%{compat_gcc_major}-gfortran %else BuildRequires: gcc-c++ BuildRequires: gcc-gfortran %endif %if %{with distributed} %if %{with gloo} BuildRequires: gloo-devel %endif %endif BuildRequires: json-devel BuildRequires: libomp-devel BuildRequires: numactl-devel BuildRequires: ninja-build BuildRequires: onnx-devel %if %{with distributed} %if %{with mpi} BuildRequires: openmpi-devel %endif %endif BuildRequires: protobuf-devel BuildRequires: sleef-devel BuildRequires: valgrind-devel %if %{with pocketfft} BuildRequires: pocketfft-devel %endif %if %{with pthreadpool} BuildRequires: pthreadpool-devel %endif %if %{with xnnpack} BuildRequires: cpuinfo-devel BuildRequires: FP16-devel BuildRequires: fxdiv-devel BuildRequires: psimd-devel BuildRequires: xnnpack-devel = 0.0^git20240814.312eb7e %endif BuildRequires: python3-devel BuildRequires: python3dist(filelock) BuildRequires: python3dist(jinja2) BuildRequires: python3dist(networkx) BuildRequires: python3dist(numpy) BuildRequires: python3dist(pyyaml) BuildRequires: python3dist(setuptools) BuildRequires: python3dist(sphinx) BuildRequires: python3dist(typing-extensions) %if 0%{?fedora} BuildRequires: python3-pybind11 BuildRequires: python3dist(fsspec) BuildRequires: python3dist(sympy) %endif %if %{with rocm} BuildRequires: hipblas-devel %if %{with hipblaslt} BuildRequires: hipblaslt-devel %endif BuildRequires: hipcub-devel BuildRequires: hipfft-devel BuildRequires: hiprand-devel BuildRequires: hipsparse-devel BuildRequires: hipsolver-devel %if %{with magma} BuildRequires: magma-devel %endif BuildRequires: miopen-devel BuildRequires: rocblas-devel BuildRequires: rocrand-devel BuildRequires: rocfft-devel %if %{with distributed} %if %{with rccl} BuildRequires: rccl-devel %endif %endif BuildRequires: rocprim-devel BuildRequires: rocm-cmake BuildRequires: rocm-comgr-devel BuildRequires: rocm-compilersupport-macros BuildRequires: rocm-core-devel BuildRequires: rocm-hip-devel BuildRequires: rocm-runtime-devel BuildRequires: rocm-rpm-macros BuildRequires: rocm-rpm-macros-modules BuildRequires: rocthrust-devel BuildRequires: roctracer-devel Requires: amdsmi Requires: rocm-rpm-macros-modules %endif %if %{with cuda} BuildRequires: cuda-cudart-devel-%{cuda_ver} BuildRequires: libcublas-devel-%{cuda_ver} BuildRequires: libcufft-devel-%{cuda_ver} BuildRequires: libcurand-devel-%{cuda_ver} BuildRequires: libcusparse-devel-%{cuda_ver} %endif %if %{with test} BuildRequires: google-benchmark-devel %endif Requires: python3dist(dill) %description PyTorch is a Python package that provides two high-level features: * Tensor computation (like NumPy) with strong GPU acceleration * Deep neural networks built on a tape-based autograd system You can reuse your favorite Python packages such as NumPy, SciPy, and Cython to extend PyTorch when needed. %package -n python3-%{pypi_name} Summary: %{summary} # For convience Provides: pytorch # Apache-2.0 Provides: bundled(flatbuffers) = 22.3.3 # MIT Provides: bundled(miniz) = 2.1.0 Provides: bundled(pybind11) = 2.11.1 %if %{with tensorpipe} # BSD-3-Clause Provides: bundled(tensorpipe) # Apache-2.0 Provides: bundled(libnop) # MIT AND CC-BY-4.0 AND ISC AND BSD-2-Clause Provides: bundled(libuv) = 1.41.0 %endif # These are already in Fedora %if %{without xnnpack} # BSD-3-Clause Provides: bundled(xnnpack) # MIT Provides: bundled(FP16) # MIT Provides: bundled(fxdiv) # MIT Provides: bundled(psimd) # BSD-2-Clause Provides: bundled(cpuinfo) %endif %if %{without pthreadpool} # BSD-2-Clause Provides: bundled(pthreadpool) %endif %if %{without pocketfft} # BSD-3-Clause Provides: bundled(pocketfft) %endif %description -n python3-%{pypi_name} PyTorch is a Python package that provides two high-level features: * Tensor computation (like NumPy) with strong GPU acceleration * Deep neural networks built on a tape-based autograd system You can reuse your favorite Python packages such as NumPy, SciPy, and Cython to extend PyTorch when needed. %if %{with cuda} %package -n python3-%{pypi_name}-cuda-%{cuda_ver} Summary: %{name} for CUDA %description -n python3-%{pypi_name}-cuda-%{cuda_ver} %{summary} %endif %if %{with rocm_loop} %package -n python3-%{pypi_name}-rocm-gfx9 Summary: %{name} for ROCm gfx9 %description -n python3-%{pypi_name}-rocm-gfx9 %{summary} %endif %if %{with test} %package -n python3-%{pypi_name}-test Summary: Tests for %{name} Requires: python3-%{pypi_name}%{?_isa} = %{version}-%{release} %description -n python3-%{pypi_name}-test %{summary} %endif %prep %if %{with gitcommit} %autosetup -p1 -n pytorch-%{commit0} # Overwrite with a git checkout of the pyproject.toml cp %{SOURCE1000} . %else %autosetup -p1 -n pytorch-v%{version} %endif # Remove bundled egg-info rm -rf %{pypi_name}.egg-info tar xf %{SOURCE1} rm -rf third_party/flatbuffers/* cp -r flatbuffers-23.3.3/* third_party/flatbuffers/ tar xf %{SOURCE2} rm -rf third_party/pybind11/* cp -r pybind11-2.11.1/* third_party/pybind11/ %if %{with cuda} tar xf %{SOURCE10} rm -rf third_party/cudnn_frontend/* cp -r cudnn-frontend-%{cuf_ver}/* third_party/cudnn_frontend/ tar xf %{SOURCE11} rm -rf third_party/cutlass/* cp -r cutlass-%{cul_ver}/* third_party/cutlass/ %endif %if %{with tensorpipe} tar xf %{SOURCE20} rm -rf third_party/tensorpipe/* cp -r tensorpipe-*/* third_party/tensorpipe/ tar xf %{SOURCE21} rm -rf third_party/tensorpipe/third_party/libuv/* cp -r libuv-*/* third_party/tensorpipe/third_party/libuv/ tar xf %{SOURCE22} rm -rf third_party/tensorpipe/third_party/libnop/* cp -r libnop-*/* third_party/tensorpipe/third_party/libnop/ %endif %if %{without xnnpack} tar xf %{SOURCE30} rm -rf third_party/XNNPACK/* cp -r XNNPACK-*/* third_party/XNNPACK/ tar xf %{SOURCE31} rm -rf third_party/FXdiv/* cp -r FXdiv-*/* third_party/FXdiv/ tar xf %{SOURCE32} rm -rf third_party/FP16/* cp -r FP16-*/* third_party/FP16/ tar xf %{SOURCE33} rm -rf third_party/psimd/* cp -r psimd-*/* third_party/psimd/ tar xf %{SOURCE34} rm -rf third_party/cpuinfo/* cp -r cpuinfo-*/* third_party/cpuinfo/ %endif %if %{without pthreadpool} tar xf %{SOURCE40} rm -rf third_party/pthreadpool/* cp -r pthreadpool-*/* third_party/pthreadpool/ %endif %if %{without pocketfft} tar xf %{SOURCE50} rm -rf third_party/pocketfft/* cp -r pocketfft-*/* third_party/pocketfft/ %endif %if %{without opentelemtry} tar xf %{SOURCE60} rm -rf third_party/opentelemetry-cpp/* cp -r opentelemetry-cpp-*/* third_party/opentelemetry-cpp/ %endif %if %{without httplib} tar xf %{SOURCE70} rm -rf third_party/cpp-httplib/* cp -r cpp-httplib-*/* third_party/cpp-httplib/ %endif %if %{without kineto} tar xf %{SOURCE80} rm -rf third_party/kineto/* cp -r kineto-*/* third_party/kineto/ %endif # hipblaslt only building with gfx90a %if %{with hipblaslt} sed -i -e 's@"gfx90a", "gfx940", "gfx941", "gfx942"@"gfx90a"@' aten/src/ATen/native/cuda/Blas.cpp %endif %if 0%{?rhel} # In RHEL but too old sed -i -e '/typing-extensions/d' setup.py # Need to pip these sed -i -e '/sympy/d' setup.py sed -i -e '/fsspec/d' setup.py %else # for 2.5.0 sed -i -e 's@sympy==1.13.1@sympy>=1.13.1@' setup.py %endif # A new dependency # Connected to USE_FLASH_ATTENTION, since this is off, do not need it sed -i -e '/aotriton.cmake/d' cmake/Dependencies.cmake # Compress hip sed -i -e 's@HIP_CLANG_FLAGS -fno-gpu-rdc@HIP_CLANG_FLAGS -fno-gpu-rdc --offload-compress@' cmake/Dependencies.cmake # No third_party fmt, use system sed -i -e 's@fmt::fmt-header-only@fmt@' CMakeLists.txt sed -i -e 's@fmt::fmt-header-only@fmt@' c10/CMakeLists.txt sed -i -e 's@fmt::fmt-header-only@fmt@' torch/CMakeLists.txt sed -i -e 's@fmt::fmt-header-only@fmt@' cmake/Dependencies.cmake sed -i -e 's@fmt::fmt-header-only@fmt@' caffe2/CMakeLists.txt sed -i -e 's@add_subdirectory(${PROJECT_SOURCE_DIR}/third_party/fmt)@#add_subdirectory(${PROJECT_SOURCE_DIR}/third_party/fmt)@' cmake/Dependencies.cmake sed -i -e 's@set_target_properties(fmt-header-only PROPERTIES INTERFACE_COMPILE_FEATURES "")@#set_target_properties(fmt-header-only PROPERTIES INTERFACE_COMPILE_FEATURES "")@' cmake/Dependencies.cmake sed -i -e 's@list(APPEND Caffe2_DEPENDENCY_LIBS fmt::fmt-header-only)@#list(APPEND Caffe2_DEPENDENCY_LIBS fmt::fmt-header-only)@' cmake/Dependencies.cmake # No third_party FXdiv %if %{with xnnpack} sed -i -e 's@if(NOT TARGET fxdiv)@if(MSVC AND USE_XNNPACK)@' caffe2/CMakeLists.txt sed -i -e 's@TARGET_LINK_LIBRARIES(torch_cpu PRIVATE fxdiv)@#TARGET_LINK_LIBRARIES(torch_cpu PRIVATE fxdiv)@' caffe2/CMakeLists.txt %endif # Disable the use of check_submodule's in the setup.py, we are a tarball, not a git repo sed -i -e 's@check_submodules()$@#check_submodules()@' setup.py # Release comes fully loaded with third party src # Remove what we can # # For 2.1 this is all but miniz-2.1.0 # Instead of building as a library, caffe2 reaches into # the third_party dir to compile the file. # mimiz is licensed MIT # https://github.com/richgel999/miniz/blob/master/LICENSE mv third_party/miniz-2.1.0 . # # setup.py depends on this script mv third_party/build_bundled.py . # Need the just untarred flatbuffers/flatbuffers.h mv third_party/flatbuffers . mv third_party/pybind11 . %if %{with cuda} mv third_party/cudnn_frontend . mv third_party/cutlass . %endif %if %{with tensorpipe} mv third_party/tensorpipe . %endif %if %{without xnnpack} mv third_party/XNNPACK . mv third_party/FXdiv . mv third_party/FP16 . mv third_party/psimd . mv third_party/cpuinfo . %endif %if %{without pthreadpool} mv third_party/pthreadpool . %endif %if %{without pocketfft} mv third_party/pocketfft . %endif %if %{without opentelemetry} mv third_party/opentelemetry-cpp . %endif %if %{without httplib} mv third_party/cpp-httplib . %endif %if %{without kineto} mv third_party/kineto . %endif %if %{with test} mv third_party/googletest . %endif # Remove everything rm -rf third_party/* # Put stuff back mv build_bundled.py third_party mv miniz-2.1.0 third_party mv flatbuffers third_party mv pybind11 third_party %if %{with cuda} mv cudnn_frontend third_party mv cutlass third_party %endif %if %{with tensorpipe} mv tensorpipe third_party %endif %if %{without xnnpack} mv XNNPACK third_party mv FXdiv third_party mv FP16 third_party mv psimd third_party mv cpuinfo third_party %endif %if %{without pthreadpool} mv pthreadpool third_party %endif %if %{without pocketfft} mv pocketfft third_party %endif %if %{without opentelemetry} mv opentelemetry-cpp third_party %endif %if %{without httplib} mv cpp-httplib third_party %endif %if %{without kineto} mv kineto third_party %endif %if %{with test} mv googletest third_party %endif %if %{with pocketfft} # # Fake out pocketfft, and system header will be used mkdir third_party/pocketfft %endif # # Use the system valgrind headers mkdir third_party/valgrind-headers cp %{_includedir}/valgrind/* third_party/valgrind-headers # Fix installing to /usr/lib64 sed -i -e 's@DESTINATION ${PYTHON_LIB_REL_PATH}@DESTINATION ${CMAKE_INSTALL_PREFIX}/${PYTHON_LIB_REL_PATH}@' caffe2/CMakeLists.txt # reenable foxi linking sed -i -e 's@list(APPEND Caffe2_DEPENDENCY_LIBS foxi_loader)@#list(APPEND Caffe2_DEPENDENCY_LIBS foxi_loader)@' cmake/Dependencies.cmake %if %{with rocm} # hipify ./tools/amd_build/build_amd.py # Fedora installs to /usr/include, not /usr/include/rocm-core sed -i -e 's@rocm-core/rocm_version.h@rocm_version.h@' aten/src/ATen/hip/tunable/TunableGemm.h # use any hip, correct CMAKE_MODULE_PATH sed -i -e 's@lib/cmake/hip@lib64/cmake/hip@' cmake/public/LoadHIP.cmake sed -i -e 's@HIP 1.0@HIP MODULE@' cmake/public/LoadHIP.cmake # silence an assert # sed -i -e '/qvalue = std::clamp(qvalue, qmin, qmax);/d' aten/src/ATen/native/cuda/IndexKernel.cu %endif %if %{with cuda} # TBD %endif %build # # Control the number of jobs # # The build can fail if too many threads exceed the physical memory # So count core and and memory and increase the build memory util the build succeeds # # Real cores, No hyperthreading COMPILE_JOBS=`cat /proc/cpuinfo | grep -m 1 'cpu cores' | awk '{ print $4 }'` if [ ${COMPILE_JOBS}x = x ]; then COMPILE_JOBS=1 fi # Take into account memmory usage per core, do not thrash real memory %if %{with cuda} BUILD_MEM=4 %else BUILD_MEM=2 %endif MEM_KB=0 MEM_KB=`cat /proc/meminfo | grep MemTotal | awk '{ print $2 }'` MEM_MB=`eval "expr ${MEM_KB} / 1024"` MEM_GB=`eval "expr ${MEM_MB} / 1024"` COMPILE_JOBS_MEM=`eval "expr 1 + ${MEM_GB} / ${BUILD_MEM}"` if [ "$COMPILE_JOBS_MEM" -lt "$COMPILE_JOBS" ]; then COMPILE_JOBS=$COMPILE_JOBS_MEM fi export MAX_JOBS=$COMPILE_JOBS %if %{with compat_gcc} export CC=%{_bindir}/gcc-%{compat_gcc_major} export CXX=%{_bindir}/g++-%{compat_gcc_major} export FC=%{_bindir}/gfortran-%{compat_gcc_major} %endif # For debugging setup.py # export SETUPTOOLS_SCM_DEBUG=1 # For verbose cmake output # export VERBOSE=ON # For verbose linking # export CMAKE_SHARED_LINKER_FLAGS=-Wl,--verbose # Manually set this hardening flag # CUDA is unhappy with pie, so do not use it %if %{without cuda} export CMAKE_EXE_LINKER_FLAGS=-pie %endif export BUILD_CUSTOM_PROTOBUF=OFF export BUILD_NVFUSER=OFF export BUILD_SHARED_LIBS=ON export BUILD_TEST=OFF export CMAKE_BUILD_TYPE=RelWithDebInfo export CMAKE_FIND_PACKAGE_PREFER_CONFIG=ON export CAFFE2_LINK_LOCAL_PROTOBUF=OFF export INTERN_BUILD_MOBILE=OFF export USE_DISTRIBUTED=OFF export USE_CUDA=OFF export USE_FAKELOWP=OFF %if %{with fbgemm} export USE_FBGEMM=ON export USE_SYSTEM_FBGEMM=ON %else export USE_FBGEMM=OFF %endif export USE_FLASH_ATTENTION=OFF export USE_GOLD_LINKER=ON export USE_GLOO=OFF export USE_ITT=OFF export USE_KINETO=OFF export USE_LITE_INTERPRETER_PROFILER=OFF export USE_LITE_PROTO=OFF export USE_MAGMA=OFF export USE_MEM_EFF_ATTENTION=OFF export USE_MKLDNN=OFF export USE_MPI=OFF export USE_NCCL=OFF export USE_NNPACK=OFF export USE_NUMPY=ON export USE_OPENMP=ON export USE_PYTORCH_QNNPACK=OFF export USE_ROCM=OFF export USE_SYSTEM_SLEEF=ON export USE_SYSTEM_EIGEN_INSTALL=ON export USE_SYSTEM_ONNX=ON export USE_SYSTEM_PYBIND11=OFF export USE_SYSTEM_LIBS=OFF export USE_TENSORPIPE=OFF export USE_XNNPACK=ON export USE_XPU=OFF %if %{with pthreadpool} export USE_SYSTEM_PTHREADPOOL=ON %endif %if %{with xnnpack} export USE_SYSTEM_CPUINFO=ON export USE_SYSTEM_FP16=ON export USE_SYSTEM_FXDIV=ON export USE_SYSTEM_PSIMD=ON export USE_SYSTEM_XNNPACK=ON %endif %if %{with cuda} %if %{without rocm} export CPLUS_INCLUDE_PATH=/usr/local/cuda-%{cuda_ver}/include export CUDACXX=/usr/local/cuda-%{cuda_ver}/bin/nvcc export CUDA_HOME=/usr/local/cuda-%{cuda_ver}/ export USE_CUDA=ON # The arches to build for export TORCH_CUDA_ARCH_LIST="8.0 8.6 8.9 9.0" %endif %endif %if %{with distributed} export USE_DISTRIBUTED=ON %if %{with tensorpipe} export USE_TENSORPIPE=ON export TP_BUILD_LIBUV=OFF %endif %if %{with gloo} export USE_GLOO=ON export USE_SYSTEM_GLOO=ON %endif %if %{with mpi} export USE_MPI=ON %endif %endif %if %{with test} export BUILD_TEST=ON %endif # Why we are using py3_ vs pyproject_ # # current pyproject problem with mock # + /usr/bin/python3 -Bs /usr/lib/rpm/redhat/pyproject_wheel.py /builddir/build/BUILD/pytorch-v2.1.0/pyproject-wheeldir # /usr/bin/python3: No module named pip # Adding pip to build requires does not fix # # See BZ 2244862 %if %{with rocm} export USE_ROCM=ON %if %{with magma} export USE_MAGMA=ON %endif export HIP_PATH=`hipconfig -p` export ROCM_PATH=`hipconfig -R` RESOURCE_DIR=`%{rocmllvm_bindir}/clang -print-resource-dir` export DEVICE_LIB_PATH=${RESOURCE_DIR}/amdgcn/bitcode # pytorch uses clang, not hipcc export HIP_CLANG_PATH=%{rocmllvm_bindir} gpu=%{rocm_default_gpu} module load rocm/$gpu export PYTORCH_ROCM_ARCH=$ROCM_GPUS %py3_build mv build build-${gpu} module purge %if %{with rocm_loop} for gpu in %{rocm_gpu_list} do module load rocm/$gpu export PYTORCH_ROCM_ARCH=$ROCM_GPUS %py3_build mv build build-${gpu} module purge done %endif %else %py3_build %endif %install %if %{with compat_gcc} export CC=%{_bindir}/gcc%{compat_gcc_major} export CXX=%{_bindir}/g++%{compat_gcc_major} export FC=%{_bindir}/gfortran%{compat_gcc_major} %endif %if %{with rocm} export USE_ROCM=ON export HIP_PATH=`hipconfig -p` export ROCM_PATH=`hipconfig -R` RESOURCE_DIR=`%{rocmllvm_bindir}/clang -print-resource-dir` export DEVICE_LIB_PATH=${RESOURCE_DIR}/amdgcn/bitcode # pytorch uses clang, not hipcc export HIP_CLANG_PATH=%{rocmllvm_bindir} gpu=%{rocm_default_gpu} module load rocm/$gpu export PYTORCH_ROCM_ARCH=$ROCM_GPUS mv build-${gpu} build %py3_install mv build build-${gpu} module purge %if %{with rocm_loop} for gpu in %{rocm_gpu_list} do module load rocm/$gpu export PYTORCH_ROCM_ARCH=$ROCM_GPUS mv build-${gpu} build # need to customize the install location, so replace py3_install %{__python3} %{py_setup} %{?py_setup_args} install -O1 --skip-build --root %{buildroot} --prefix /usr/lib64/rocm/${gpu} %{?*} rm -rfv %{buildroot}/usr/lib/rocm/${gpu}/bin/__pycache__ mv build build-${gpu} module purge done %endif %else %py3_install %endif # Do not remote the empty files %if %{with cuda} %files -n python3-%{pypi_name}-cuda-%{cuda_ver} %else %files -n python3-%{pypi_name} %endif %license LICENSE %doc README.md %{_bindir}/convert-caffe2-to-onnx %{_bindir}/convert-onnx-to-caffe2 %{_bindir}/torchrun %{_bindir}/torchfrtrace %{python3_sitearch}/%{pypi_name} %{python3_sitearch}/%{pypi_name}-*.egg-info %{python3_sitearch}/functorch %{python3_sitearch}/torchgen %if %{with rocm} %if %{with rocm_loop} %files -n python3-%{pypi_name}-rocm-gfx9 %{_libdir}/rocm/gfx9/bin/* %{_libdir}/rocm/gfx9/lib64/* %endif %endif %changelog ## START: Generated by rpmautospec * Tue Nov 26 2024 Tom Rix - 2.5.0-1 - Update for 2.5.0 * Thu Nov 14 2024 Tom Rix - 2.4.1-12 - Use rocmllvm_bindir * Thu Oct 31 2024 Peter Robinson - 2.4.1-11 - drop old versions of pytorch from sources * Thu Oct 31 2024 Peter Robinson - 2.4.1-10 - Add binutils-gold build dep * Thu Oct 31 2024 Peter Robinson - 2.4.1-9 - Fix various Provides including the pytotch provides * Tue Oct 29 2024 Tom Rix - 2.4.1-8 - Use the new xnnpack * Fri Oct 11 2024 Tom Rix - 2.4.1-7 - Update gitcommit to v2.5.0-rc9 * Thu Oct 10 2024 Tom Rix - 2.4.1-6 - Update for llvm18 * Mon Oct 07 2024 Tom Rix - 2.4.1-5 - Some help finding llvm18 * Mon Sep 30 2024 Tom Rix - 2.4.1-4 - Update gitcommit * Sun Sep 15 2024 Tom Rix - 2.4.1-3 - Simplify cuda versions * Sun Sep 15 2024 Tom Rix - 2.4.1-2 - Update gitcommit * Mon Sep 09 2024 Tom Rix - 2.4.1-1 - Update to 2.4.1 * Tue Sep 03 2024 Tom Rix - 2.4.0-10 - amdsmi is a runtime dependency for ROCm * Fri Aug 30 2024 Tom Rix - 2.4.0-9 - Update the gitcommit * Thu Aug 15 2024 Tom Rix - 2.4.0-8 - Start tracking 2.5 * Wed Aug 07 2024 Tom Rix - 2.4.0-7 - Disable fbgemm with rocm * Mon Aug 05 2024 Tom Rix - 2.4.0-6 - Enable hipblaslt * Sun Aug 04 2024 Tom Rix - 2.4.0-5 - Remove the packages * Sun Aug 04 2024 Tom Rix - 2.4.0-4 - Simplify ROCm gpu list * Sat Jul 27 2024 Tom Rix - 2.4.0-3 - Fbgemm not available on aarch64 * Thu Jul 25 2024 Sérgio M. Basto - 2.4.0-2 - Rebuild for opencv 4.10.0 * Thu Jul 25 2024 Tom Rix - 2.4.0-1 - PyTorch 2.4 * Sat Jul 20 2024 Tom Rix - 2.3.1-23 - Fix USE_NUMA * Sat Jul 20 2024 Tom Rix - 2.3.1-22 - Use fbgemm on 2.4 * Tue Jul 16 2024 Kefu Chai - 2.3.1-20 - Rebuilt for fmt 11 * Wed Jul 10 2024 Tom Rix - 2.3.1-19 - Update to 2.4-rc8 * Fri Jul 05 2024 Tom Rix - 2.3.1-18 - Switch from openblas to flexiblas (rhbz#2295953) * Thu Jul 04 2024 Tom Rix - 2.3.1-17 - Show use of hipblaslt package * Thu Jul 04 2024 Tom Rix - 2.3.1-16 - Revisions of patches for 2.4 * Wed Jun 26 2024 Tom Rix - 2.3.1-15 - Add a CUDA subpackage * Wed Jun 26 2024 Tom Rix - 2.3.1-14 - Update gitcommit to v2.4.0-rc6 * Tue Jun 25 2024 Tom Rix - 2.3.1-13 - Add CUDA BuildRequires * Mon Jun 24 2024 Tom Rix - 2.3.1-12 - Update gitcommit to 2.4.0-rc5 * Fri Jun 21 2024 Tom Rix - 2.3.1-11 - Update gitcommit to 2.4.0-rc3 * Tue Jun 18 2024 Benjamin A. Beasley - 2.3.1-10 - Patch for sleef 3.6 * Fri Jun 14 2024 Python Maint - 2.3.1-9 - Rebuilt for Python 3.13 * Thu Jun 13 2024 Tom Rix - 2.3.1-8 - Update gitcommit * Thu Jun 13 2024 Tom Rix - 2.3.1-7 - Use specific version of CUDA base on disto release * Tue Jun 11 2024 Tom Rix - 2.3.1-6 - Fix broken cpuinfo for aarch64 * Tue Jun 11 2024 Tom Rix - 2.3.1-5 - Reduce amd gpu list on F40 * Mon Jun 10 2024 Tom Rix - 2.3.1-4 - Start a readme for NVIDIA * Mon Jun 10 2024 Tom Rix - 2.3.1-3 - Fix the normal build. * Sun Jun 09 2024 Tom Rix - 2.3.1-2 - Update gitcommit * Sun Jun 09 2024 Tom Rix - 2.3.1-1 - Update to 2.3.1 * Sat Jun 08 2024 Tom Rix - 2.3.0-15 - Add --with compat_gcc * Sat Jun 08 2024 Tom Rix - 2.3.0-14 - Do not apply ROCm patches with CUDA build * Fri Jun 07 2024 Tom Rix - 2.3.0-13 - Do not conditionally patch * Thu Jun 06 2024 Tom Rix - 2.3.0-12 - Update for ROCm 6.1.1 * Wed Jun 05 2024 Tom Rix - 2.3.0-11 - Update the ToT git commit * Tue May 21 2024 Tom Rix - 2.3.0-10 - Start tracking upstream 2.4 * Sat May 18 2024 Tom Rix - 2.3.0-9 - Roll ROCm support claim back to f40 * Thu May 16 2024 Tom Rix - 2.3.0-8 - Add cuda arches to build for * Tue May 07 2024 Tom Rix - 2.3.0-7 - Fill in missing packages on F40 and F39 with third_party. * Sun May 05 2024 Tom Rix - 2.3.0-6 - Collect the buildrequires that depend on F40 together. * Sun May 05 2024 Tom Rix - 2.3.0-5 - Improve fedora conditional use versions. * Fri May 03 2024 Tom Rix - 2.3.0-4 - Enable dynamo on 3.12 * Thu May 02 2024 Tom Rix - 2.3.0-3 - Disable dwz with ROCm * Tue Apr 30 2024 Tom Rix - 2.3.0-2 - Update sources * Tue Apr 30 2024 Tom Rix - 2.3.0-1 - Initial 2.3 release * Mon Apr 15 2024 Tom Rix - 2.3.0^git20240408.97ff6cf-2 - Use the system gloo * Thu Apr 11 2024 Tom Rix - 2.3.0^git20240408.97ff6cf-1 - v2.3.0-rc12 * Sat Apr 06 2024 Tom Rix - 2.3.0^git20240402.4bb5cb5-1 - Update to 2.3-rc7 * Sun Mar 31 2024 Tom Rix - 2.3.0^git20242213.74832f1-2 - Provide pytorch as a convience * Wed Mar 27 2024 Tom Rix - 2.3.0^git20242213.74832f1-1 - Update to 2.3-rc6 * Fri Mar 22 2024 Tom Rix - 2.3.0^git20240313.6a89a75-8 - Remove conditional around the rocm patches * Fri Mar 22 2024 Tom Rix - 2.3.0^git20240313.6a89a75-7 - Split the ROCm gpu families out into subpackages. * Thu Mar 21 2024 Tom Rix - 2.3.0^git20240313.6a89a75-6 - Update the source to 2.3-rc2 * Thu Mar 21 2024 Tom Rix - 2.3.0^git20240313.6a89a75-5 - RPMAUTOSPEC: unresolvable merge ## END: Generated by rpmautospec