# Maintainer: acxz <akashpatel2008 at yahoo dot com>
# Contributor: Sven-Hendrik Haase <svenstaro@gmail.com>
# Contributor: Stephen Zhang <zsrkmyn at gmail dot com>

pkgbase=python-pytorch-rocm

# Flags for building without/with cpu optimizations
_build_no_opt=1
_build_opt=1

pkgname=()
[ "$_build_no_opt" -eq 1 ] && pkgname+=("python-pytorch-rocm")
[ "$_build_opt" -eq 1 ]    && pkgname+=("python-pytorch-opt-rocm")

_pkgname="pytorch"
pkgver=1.7.1
_pkgver=1.7.1
pkgrel=7
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' 'rccl' 'pybind11' 'python' 'python-yaml' 'libuv'
         'python-numpy' 'protobuf' 'ffmpeg' 'python-future' 'qt5-base' 'onednn' 'intel-mkl')
makedepends=('python' 'python-setuptools' 'python-yaml' 'python-numpy' 'cmake' 'rocm'
             'rocm-libs' 'miopen' 'git' 'ninja' 'pkgconfig' 'doxygen')
source=("${_pkgname}-${pkgver}::git+https://github.com/pytorch/pytorch.git#tag=v$_pkgver"
        fix_include_system.patch
        use-system-libuv.patch
        use-system-libuv2.patch
        nccl_version.patch
        disable_non_x86_64.patch
        "find-hsa-runtime.patch::https://patch-diff.githubusercontent.com/raw/pytorch/pytorch/pull/45550.patch")
sha256sums=('SKIP'
            '83c81ec6a461110da6ae6182529f58100986b068c5182ca62cd53c648b4e4fb0'
            '26b1dd596f1e21a011ee18cab939924483d6c6d4d98e543bf76f5a9312d54d67'
            '7b65c3b209fc39f92ba58a58be6d3da40799f1922910b1171ccd9209eda1f9eb'
            'e4a96887b41cbdfd4204ce5f16fcb16a23558d23126331794ab6aa30a66f2e0d'
            'd3ef8491718ed7e814fe63e81df2f49862fffbea891d2babbcb464796a1bd680'
            'SKIP')

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://bugs.archlinux.org/task/64981
  patch -N torch/utils/cpp_extension.py "${srcdir}"/fix_include_system.patch

  # Use system libuv
  patch -Np1 -i "${srcdir}"/use-system-libuv.patch

  # FindNCCL patch to export correct nccl version
  # patch -Np1 -i "${srcdir}"/nccl_version.patch

  # https://github.com/pytorch/pytorch/pull/45550
  patch -Np1 -i "${srcdir}"/find-hsa-runtime.patch

  # remove local nccl
  rm -rf third_party/nccl/nccl

  cd ..

  [ "$_build_no_opt" -eq 1 ] && cp -a "${_pkgname}-${pkgver}" "${_pkgname}-${pkgver}-rocm"
  [ "$_build_opt" -eq 1 ]    && cp -a "${_pkgname}-${pkgver}" "${_pkgname}-${pkgver}-opt-rocm"

  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=ON
  export BUILD_CUSTOM_PROTOBUF=ON
  # 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 USE_SYSTEM_LIBS=ON
  export NCCL_VERSION=$(pkg-config nccl --modversion)
  export NCCL_VER_CODE=$(sed -n 's/^#define NCCL_VERSION_CODE\s*\(.*\).*/\1/p' /usr/include/nccl.h)
  export CUDAHOSTCXX=g++
  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="5.2;5.3;6.0;6.1;6.2;7.0;7.0+PTX;7.2;7.2+PTX;7.5;7.5+PTX;8.0;8.0+PTX;8.6;8.6+PTX"
}

build() {
  if [ "$_build_no_opt" -eq 1 ]; then
    echo "Building with rocm and without non-x86-64 optimizations"
    export USE_CUDA=OFF
    export USE_ROCM=ON
    cd "${srcdir}/${_pkgname}-${pkgver}-rocm"
    patch -Np1 -i "${srcdir}/disable_non_x86_64.patch"
    echo "add_definitions(-march=x86-64)" >> cmake/MiscCheck.cmake

    # Apply changes needed for ROCm
    python tools/amd_build/build_amd.py

    # Fix so amdip64 library ending with a dash
    python setup.py build --cmake-only
    sed -E -i 's#opt/rocm/hip/lib/libamdhip64\.so\.[0-9.]+-#opt/rocm/hip/lib/libamdhip64.so#' build/build.ninja

    python setup.py build
  fi

  if [ "$_build_opt" -eq 1 ]; then
    echo "Building with rocm and with non-x86-64 optimizations"
    export USE_CUDA=OFF
    export USE_ROCM=ON
    cd "${srcdir}/${_pkgname}-${pkgver}-opt-rocm"
    echo "add_definitions(-march=haswell)" >> cmake/MiscCheck.cmake

    # Apply changes needed for ROCm
    python tools/amd_build/build_amd.py

    # Fix so amdip64 library ending with a dash
    python setup.py build --cmake-only
    sed -E -i 's#opt/rocm/hip/lib/libamdhip64\.so\.[0-9.]+-#opt/rocm/hip/lib/libamdhip64.so#' build/build.ninja

    python setup.py build
  fi
}

_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/python3.9/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-rocm() {
  pkgdesc="Tensors and Dynamic neural networks in Python with strong GPU acceleration (with ROCM)"
  depends+=(rocm rocm-libs miopen)
  conflicts=(python-pytorch)
  provides=(python-pytorch)

  cd "${srcdir}/${_pkgname}-${pkgver}-rocm"
  _package
}

package_python-pytorch-opt-rocm() {
  pkgdesc="Tensors and Dynamic neural networks in Python with strong GPU acceleration (with ROCM and AVX2 CPU optimizations)"
  depends+=(rocm rocm-libs miopen)
  conflicts=(python-pytorch)
  provides=(python-pytorch python-pytorch-rocm)

  cd "${srcdir}/${_pkgname}-${pkgver}-opt-rocm"
  _package
}

# vim:set ts=2 sw=2 et: