[arch-commits] Commit in python-pytorch/repos (2 files)

Konstantin Gizdov kgizdov at archlinux.org
Mon Dec 9 09:15:31 UTC 2019


    Date: Monday, December 9, 2019 @ 09:15:31
  Author: kgizdov
Revision: 536385

archrelease: copy trunk to community-staging-x86_64

Added:
  python-pytorch/repos/community-staging-x86_64/
  python-pytorch/repos/community-staging-x86_64/PKGBUILD
    (from rev 536384, python-pytorch/trunk/PKGBUILD)

----------+
 PKGBUILD |  163 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 163 insertions(+)

Copied: python-pytorch/repos/community-staging-x86_64/PKGBUILD (from rev 536384, python-pytorch/trunk/PKGBUILD)
===================================================================
--- community-staging-x86_64/PKGBUILD	                        (rev 0)
+++ community-staging-x86_64/PKGBUILD	2019-12-09 09:15:31 UTC (rev 536385)
@@ -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=5
+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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