[arch-commits] Commit in python-pytorch/repos (2 files)
Konstantin Gizdov
kgizdov at archlinux.org
Thu Nov 28 12:57:53 UTC 2019
Date: Thursday, November 28, 2019 @ 12:57:53
Author: kgizdov
Revision: 534278
archrelease: copy trunk to community-testing-x86_64
Added:
python-pytorch/repos/community-testing-x86_64/
python-pytorch/repos/community-testing-x86_64/PKGBUILD
(from rev 534277, python-pytorch/trunk/PKGBUILD)
----------+
PKGBUILD | 163 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
1 file changed, 163 insertions(+)
Copied: python-pytorch/repos/community-testing-x86_64/PKGBUILD (from rev 534277, python-pytorch/trunk/PKGBUILD)
===================================================================
--- community-testing-x86_64/PKGBUILD (rev 0)
+++ community-testing-x86_64/PKGBUILD 2019-11-28 12:57:53 UTC (rev 534278)
@@ -0,0 +1,163 @@
+# Maintainer: Sven-Hendrik Haase <sh at lutzhaase.com>
+# Contributor: Stephen Zhang <zsrkmyn at gmail dot com>
+
+pkgbase="python-pytorch"
+pkgname=("python-pytorch" "python-pytorch-opt" "python-pytorch-cuda" "python-pytorch-opt-cuda")
+_pkgname="pytorch"
+pkgver=1.3.1
+pkgrel=4
+pkgdesc="Tensors and Dynamic neural networks in Python with strong GPU acceleration"
+arch=('x86_64')
+url="https://pytorch.org"
+license=('BSD')
+depends=('google-glog' 'gflags' 'opencv' 'openmp' 'nccl' 'pybind11' 'python' 'python-yaml' 'python-numpy' 'protobuf' 'ffmpeg' 'python-future' 'qt5-base')
+makedepends=('python' 'python-setuptools' 'python-yaml' 'python-numpy' 'cmake' 'cuda' 'cudnn' 'git' 'magma')
+source=("${_pkgname}-${pkgver}::git+https://github.com/pytorch/pytorch.git#tag=v$pkgver")
+sha256sums=('SKIP')
+
+get_pyver () {
+ python -c 'import sys; print(str(sys.version_info[0]) + "." + str(sys.version_info[1]))'
+}
+
+prepare() {
+ cd "${_pkgname}-${pkgver}"
+
+ # This is the lazy way since pytorch has sooo many submodules and they keep
+ # changing them around but we've run into more problems so far doing it the
+ # manual than the lazy way. This lazy way (not explicitly specifying all
+ # submodules) will make building inefficient but for now I'll take it.
+ # It will result in the same package, don't worry.
+ git submodule update --init --recursive
+
+ # https://github.com/pytorch/pytorch/issues/26555
+ sed -i 's#^ ${CMAKE_CURRENT_SOURCE_DIR}/tensor_iterator_test.cpp##g' aten/src/ATen/test/CMakeLists.txt
+
+ # Fix build with Python 3.8
+ # https://github.com/pytorch/pytorch/issues/28060
+ find -name '*.cpp' -exec sed -i '/tp_print/s/nullptr/0/' {} +
+
+ cd ..
+
+ cp -a "${_pkgname}-${pkgver}" "${_pkgname}-${pkgver}-opt"
+ cp -a "${_pkgname}-${pkgver}" "${_pkgname}-${pkgver}-cuda"
+ cp -a "${_pkgname}-${pkgver}" "${_pkgname}-${pkgver}-opt-cuda"
+
+ export VERBOSE=1
+ export PYTORCH_BUILD_VERSION="${pkgver}"
+ export PYTORCH_BUILD_NUMBER=1
+
+ # Check tools/setup_helpers/cmake.py, setup.py and CMakeLists.txt for a list of flags that can be set via env vars.
+ export USE_MKLDNN=OFF
+ # export BUILD_CUSTOM_PROTOBUF=OFF
+ # export BUILD_SHARED_LIBS=OFF
+ export USE_FFMPEG=ON
+ export USE_GFLAGS=ON
+ export USE_GLOG=ON
+ export BUILD_BINARY=ON
+ export USE_OPENCV=ON
+ export USE_SYSTEM_NCCL=ON
+ export CUDAHOSTCXX=g++-8
+ export CUDA_HOME=/opt/cuda
+ export CUDNN_LIB_DIR=/usr/lib
+ export CUDNN_INCLUDE_DIR=/usr/include
+ export TORCH_NVCC_FLAGS="-Xfatbin -compress-all"
+ export TORCH_CUDA_ARCH_LIST="3.2;3.5;3.7;5.0;5.2;5.3;6.0;6.0+PTX;6.1;6.1+PTX;6.2;6.2+PTX;7.0;7.0+PTX;7.2;7.2+PTX;7.5;7.5+PTX"
+}
+
+build() {
+ echo "Building without cuda and without non-x86-64 optimizations"
+ export USE_CUDA=0
+ export USE_CUDNN=0
+ cd "${srcdir}/${_pkgname}-${pkgver}"
+ python setup.py build
+
+
+ echo "Building without cuda and with non-x86-64 optimizations"
+ export USE_CUDA=0
+ export USE_CUDNN=0
+ cd "${srcdir}/${_pkgname}-${pkgver}-opt"
+ echo "add_definitions(-march=haswell)" >> cmake/MiscCheck.cmake
+ python setup.py build
+
+
+ echo "Building with cuda and without non-x86-64 optimizations"
+ export USE_CUDA=1
+ export USE_CUDNN=1
+ cd "${srcdir}/${_pkgname}-${pkgver}-cuda"
+ python setup.py build
+
+
+ echo "Building with cuda and with non-x86-64 optimizations"
+ export USE_CUDA=1
+ export USE_CUDNN=1
+ cd "${srcdir}/${_pkgname}-${pkgver}-opt-cuda"
+ echo "add_definitions(-march=haswell)" >> cmake/MiscCheck.cmake
+ python setup.py build
+}
+
+_package() {
+ # Prevent setup.py from re-running CMake and rebuilding
+ sed -e 's/RUN_BUILD_DEPS = True/RUN_BUILD_DEPS = False/g' -i setup.py
+
+ python setup.py install --root="${pkgdir}"/ --optimize=1 --skip-build
+
+ install -Dm644 LICENSE "${pkgdir}/usr/share/licenses/${pkgname}/LICENSE"
+
+ pytorchpath="usr/lib/python$(get_pyver)/site-packages/torch"
+ install -d "${pkgdir}/usr/lib"
+
+ # put CMake files in correct place
+ mv "${pkgdir}/${pytorchpath}/share/cmake" "${pkgdir}/usr/lib/cmake"
+
+ # put C++ API in correct place
+ mv "${pkgdir}/${pytorchpath}/include" "${pkgdir}/usr/include"
+ mv "${pkgdir}/${pytorchpath}/lib"/*.so* "${pkgdir}/usr/lib/"
+
+ # clean up duplicates
+ # TODO: move towards direct shared library dependecy of:
+ # c10, caffe2, libcpuinfo, CUDA RT, gloo, GTest, Intel MKL,
+ # NVRTC, ONNX, protobuf, libthreadpool, QNNPACK
+ rm -rf "${pkgdir}/usr/include/pybind11"
+
+ # python module is hardcoded to look there at runtime
+ ln -s /usr/include "${pkgdir}/${pytorchpath}/include"
+ find "${pkgdir}"/usr/lib -type f -name "*.so*" -print0 | while read -rd $'\0' _lib; do
+ ln -s ${_lib#"$pkgdir"} "${pkgdir}/${pytorchpath}/lib/"
+ done
+}
+
+package_python-pytorch() {
+ cd "${srcdir}/${_pkgname}-${pkgver}"
+ _package
+}
+
+package_python-pytorch-opt() {
+ pkgdesc="Tensors and Dynamic neural networks in Python with strong GPU acceleration (with CPU optimizations)"
+ conflicts=(python-pytorch)
+ provides=(python-pytorch)
+
+ cd "${srcdir}/${_pkgname}-${pkgver}-opt"
+ _package
+}
+
+package_python-pytorch-cuda() {
+ pkgdesc="Tensors and Dynamic neural networks in Python with strong GPU acceleration (with CUDA)"
+ depends+=(cuda cudnn magma)
+ conflicts=(python-pytorch)
+ provides=(python-pytorch)
+
+ cd "${srcdir}/${_pkgname}-${pkgver}-cuda"
+ _package
+}
+
+package_python-pytorch-opt-cuda() {
+ pkgdesc="Tensors and Dynamic neural networks in Python with strong GPU acceleration (with CUDA and CPU optimizations)"
+ depends+=(cuda cudnn magma)
+ conflicts=(python-pytorch)
+ provides=(python-pytorch python-pytorch-cuda)
+
+ cd "${srcdir}/${_pkgname}-${pkgver}-opt-cuda"
+ _package
+}
+
+# vim:set ts=2 sw=2 et:
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