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Gentoo's Bugzilla – Attachment 607168 Details for
Bug 705712
sci-libs/tensorflow - enable rocm backend support for AMD video cards
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Modified tensorflow-9999 ebuild
tensorflow-9999.ebuild (text/plain), 13.20 KB, created by
Miroslav Piskor
on 2020-01-28 20:06:47 UTC
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Description:
Modified tensorflow-9999 ebuild
Filename:
MIME Type:
Creator:
Miroslav Piskor
Created:
2020-01-28 20:06:47 UTC
Size:
13.20 KB
patch
obsolete
># Copyright 1999-2020 Gentoo Authors ># Distributed under the terms of the GNU General Public License v2 > >EAPI=7 > >DISTUTILS_OPTIONAL=1 >PYTHON_COMPAT=( python{3_6,3_7} ) >#MY_PV=${PV/_rc/-rc} >#MY_P=${PN}-${MY_PV} >MY_PV="2.1.0" > >inherit bazel check-reqs cuda distutils-r1 flag-o-matic toolchain-funcs > >DESCRIPTION="Computation framework using data flow graphs for scalable machine learning" >HOMEPAGE="https://www.tensorflow.org/" > >LICENSE="Apache-2.0" >SLOT="0" >KEYWORDS="~amd64" >IUSE="cuda mpi +python rocm xla" >CPU_USE_FLAGS_X86="sse sse2 sse3 sse4_1 sse4_2 avx avx2 fma3 fma4" >for i in $CPU_USE_FLAGS_X86; do > IUSE+=" cpu_flags_x86_$i" >done > ># distfiles that bazel uses for the workspace, will be copied to basel-distdir >bazel_external_uris=" > https://storage.googleapis.com/mirror.tensorflow.org/www.kurims.kyoto-u.ac.jp/~ooura/fft2d.tgz -> oourafft2d-20061228.tgz > https://gitlab.com/libeigen/eigen/-/archive/b9362fb8f76fbba805b56afbc0f5de0a279631b5/eigen-b9362fb8f76fbba805b56afbc0f5de0a279631b5.tar.gz -> eigen-b9362fb8f76fbba805b56afbc0f5de0a279631b5.tar.gz > https://github.com/abseil/abseil-cpp/archive/43ef2148c0936ebf7cb4be6b19927a9d9d145b8f.tar.gz -> abseil-cpp-43ef2148c0936ebf7cb4be6b19927a9d9d145b8f.tar.gz > https://github.com/bazelbuild/bazel-skylib/releases/download/0.9.0/bazel_skylib-0.9.0.tar.gz > https://github.com/bazelbuild/bazel-toolchains/archive/92dd8a7a518a2fb7ba992d47c8b38299fe0be825.tar.gz -> bazel-toolchains-92dd8a7a518a2fb7ba992d47c8b38299fe0be825.tar.gz > https://github.com/bazelbuild/rules_cc/archive/01d4a48911d5e7591ecb1c06d3b8af47fe872371.zip -> bazelbuild-rules_cc-01d4a48911d5e7591ecb1c06d3b8af47fe872371.zip > https://github.com/bazelbuild/rules_java/archive/7cf3cefd652008d0a64a419c34c13bdca6c8f178.zip -> bazelbuild-rules_java-7cf3cefd652008d0a64a419c34c13bdca6c8f178.zip > https://github.com/bazelbuild/rules_closure/archive/308b05b2419edb5c8ee0471b67a40403df940149.tar.gz -> bazelbuild-rules_closure-308b05b2419edb5c8ee0471b67a40403df940149.tar.gz > https://github.com/bazelbuild/rules_docker/releases/download/v0.10.0/rules_docker-v0.10.0.tar.gz -> bazelbuild-rules_docker-v0.10.0.tar.gz > https://github.com/bazelbuild/rules_swift/releases/download/0.12.1/rules_swift.0.12.1.tar.gz -> bazelbuild-rules_swift.0.12.1.tar.gz > https://github.com/google/farmhash/archive/816a4ae622e964763ca0862d9dbd19324a1eaf45.tar.gz -> farmhash-816a4ae622e964763ca0862d9dbd19324a1eaf45.tar.gz > https://github.com/google/gemmlowp/archive/12fed0cd7cfcd9e169bf1925bc3a7a58725fdcc3.zip -> gemmlowp-12fed0cd7cfcd9e169bf1925bc3a7a58725fdcc3.zip > https://github.com/google/highwayhash/archive/fd3d9af80465e4383162e4a7c5e2f406e82dd968.tar.gz -> highwayhash-fd3d9af80465e4383162e4a7c5e2f406e82dd968.tar.gz > https://github.com/google/re2/archive/506cfa4bffd060c06ec338ce50ea3468daa6c814.tar.gz -> re2-506cfa4bffd060c06ec338ce50ea3468daa6c814.tar.gz > https://github.com/mborgerding/kissfft/archive/36dbc057604f00aacfc0288ddad57e3b21cfc1b8.tar.gz -> kissfft-36dbc057604f00aacfc0288ddad57e3b21cfc1b8.tar.gz > https://github.com/pybind/pybind11/archive/v2.3.0.tar.gz -> pybind11-v2.3.0.tar.gz > https://github.com/llvm/llvm-project/archive/c8695ba9cdebfc25af3312a84d91ae6f0f98487b.tar.gz -> llvm-c8695ba9cdebfc25af3312a84d91ae6f0f98487b.tar.gz > https://github.com/joe-kuo/sobol_data/archive/835a7d7b1ee3bc83e575e302a985c66ec4b65249.tar.gz -> sobol_data-835a7d7b1ee3bc83e575e302a985c66ec4b65249.tar.gz > https://files.pythonhosted.org/packages/f3/af/4182184d3c338792894f34a62672919db7ca008c89abee9b564dd34d8029/astunparse-1.6.3.tar.gz > https://raw.githubusercontent.com/simonpercivall/astunparse/v1.6.2/LICENSE -> astunparse.licence > cuda? ( > https://github.com/nvidia/nccl/archive/0ceaec9cee96ae7658aa45686853286651f36384.tar.gz -> nvidia-nccl-0ceaec9cee96ae7658aa45686853286651f36384.tar.gz > https://github.com/NVlabs/cub/archive/1.8.0.zip -> cub-1.8.0.zip > ) > python? ( > https://github.com/intel/ARM_NEON_2_x86_SSE/archive/1200fe90bb174a6224a525ee60148671a786a71f.tar.gz -> ARM_NEON_2_x86_SSE-1200fe90bb174a6224a525ee60148671a786a71f.tar.gz > https://storage.googleapis.com/mirror.tensorflow.org/docs.python.org/2.7/_sources/license.rst.txt -> tensorflow-1.15.0-python-license.rst.txt > https://pypi.python.org/packages/bc/cc/3cdb0a02e7e96f6c70bd971bc8a90b8463fda83e264fa9c5c1c98ceabd81/backports.weakref-1.0rc1.tar.gz > )" > >SRC_URI="https://github.com/tensorflow/tensorflow/archive/master.zip -> ${P}.zip > ${bazel_external_uris}" > >RDEPEND=" > app-arch/snappy > dev-db/lmdb > dev-db/sqlite > dev-libs/double-conversion > dev-libs/icu > ~dev-libs/jsoncpp-1.9.2 > dev-libs/libpcre > dev-libs/nsync > dev-libs/openssl:0= > >=dev-libs/protobuf-3.8.0:= > >=dev-libs/re2-0.2019.06.01 > media-libs/giflib > media-libs/libjpeg-turbo > media-libs/libpng:0 > >=net-libs/grpc-1.22.0 > net-misc/curl > sys-libs/zlib > >=sys-apps/hwloc-2 > cuda? ( > >=dev-util/nvidia-cuda-toolkit-9.1[profiler] > dev-libs/cudnn > ) > mpi? ( virtual/mpi ) > python? ( > ${PYTHON_DEPS} > >=dev-libs/flatbuffers-1.8.0 > dev-python/absl-py[${PYTHON_USEDEP}] > >=dev-python/astor-0.7.1[${PYTHON_USEDEP}] > dev-python/gast[${PYTHON_USEDEP}] > >=dev-python/numpy-1.16[${PYTHON_USEDEP}] > dev-python/google-pasta[${PYTHON_USEDEP}] > dev-python/opt-einsum[${PYTHON_USEDEP}] > >=dev-python/protobuf-python-3.8.0[${PYTHON_USEDEP}] > dev-python/six[${PYTHON_USEDEP}] > dev-python/termcolor[${PYTHON_USEDEP}] > >=dev-python/grpcio-1.22.0[${PYTHON_USEDEP}] > >=dev-python/wrapt-1.11.1[${PYTHON_USEDEP}] > >=net-libs/google-cloud-cpp-0.10.0 > >=sci-libs/keras-applications-1.0.8[${PYTHON_USEDEP}] > >=sci-libs/keras-preprocessing-1.1.0[${PYTHON_USEDEP}] > >=sci-visualization/tensorboard-2.0.0[${PYTHON_USEDEP}] > ) > rocm? ( dev-util/amd-rocm-meta[hip,science,opencl,tensorflow] )" > >DEPEND="${RDEPEND} > python? ( > dev-python/mock > dev-python/setuptools > )" >PDEPEND="python? ( > >=sci-libs/tensorflow-estimator-2.0.0[${PYTHON_USEDEP}] > )" >BDEPEND=" > app-arch/unzip > >=dev-libs/protobuf-3.8.0 > dev-java/java-config > dev-lang/swig > =dev-util/bazel-1.2.1 > cuda? ( > >=dev-util/nvidia-cuda-toolkit-9.1[profiler] > ) > !python? ( dev-lang/python ) > python? ( > dev-python/cython > dev-python/mock > >=dev-python/grpcio-tools-1.22.0 > )" >REQUIRED_USE="python? ( ${PYTHON_REQUIRED_USE} )" > >S="${WORKDIR}/tensorflow-master" > >PATCHES=( > "${FILESDIR}/tensorflow-1.15.0_rc0-0001-WORKSPACE-add-rules-docker-http_archive-bazel-toolch.patch" > "${FILESDIR}/tensorflow-2.1.0-python3.8-pywrap_tensor.patch" >) >DOCS=( AUTHORS CONTRIBUTING.md ISSUE_TEMPLATE.md README.md RELEASE.md ) >CHECKREQS_MEMORY="5G" >CHECKREQS_DISK_BUILD="10G" > >get-cpu-flags() { > local i f=() > # Keep this list in sync with tensorflow/core/platform/cpu_feature_guard.cc. > for i in sse sse2 sse3 sse4_1 sse4_2 avx avx2 fma4; do > use cpu_flags_x86_${i} && f+=( -m${i/_/.} ) > done > use cpu_flags_x86_fma3 && f+=( -mfma ) > echo "${f[*]}" >} > >pkg_setup() { > ewarn "TensorFlow 2.0 is a major release that contains some incompatibilities" > ewarn "with TensorFlow 1.x. For more information about migrating to TF2.0 see:" > ewarn "https://www.tensorflow.org/guide/migrate" > > local num_pythons_enabled > num_pythons_enabled=0 > count_impls(){ > num_pythons_enabled=$((${num_pythons_enabled} + 1)) > } > use python && python_foreach_impl count_impls > > # 10G to build C/C++ libs, 5G per python impl > CHECKREQS_DISK_BUILD="$((10 + 6 * ${num_pythons_enabled}))G" > check-reqs_pkg_setup > } > >src_unpack() { > # Only unpack the main distfile > unpack "${P}.zip" > bazel_load_distfiles "${bazel_external_uris}" >} > >src_prepare() { > # jsoncpp-1.9.2-r1 renamned features.h to json_features.h > sed -i -e's|json/features.h|json/json_features.h|' \ > third_party/systemlibs/jsoncpp.BUILD third_party/jsoncpp.BUILD > > export JAVA_HOME=$(java-config --jre-home) # so keepwork works > > append-flags $(get-cpu-flags) > bazel_setup_bazelrc > > default > use python && python_copy_sources > > use cuda && cuda_add_sandbox >} > >src_configure() { > addpredict /dev/kfd > export JAVA_HOME=$(java-config --jre-home) # so keepwork works > > do_configure() { > export CC_OPT_FLAGS=" " > export TF_ENABLE_XLA=$(usex xla 1 0) > export TF_NEED_OPENCL_SYCL=0 > export TF_NEED_OPENCL=0 > export TF_NEED_COMPUTECPP=0 > export TF_NEED_ROCM=$(usex rocm 1 0) > export TF_NEED_MPI=$(usex mpi 1 0) > export TF_SET_ANDROID_WORKSPACE=0 > > if use rocm; then > export GCC_HOST_COMPILER_PATH="/usr/x86_64-pc-linux-gnu/gcc-bin/9.2.0/gcc" > export GCC_HOST_COMPILER_PREFIX="/usr/x86_64-pc-linux-gnu/gcc-bin/9.2.0" > export ROCM_TOOLKIT_PATH="/usr" > export TF_ROCM_AMDGPU_TARGETS="gfx803" > export TF_MIOPEN_VERSION="" > eapply "${FILESDIR}/tensorflow-rocm-3.0.0_configure_bazel.patch" > fi > > if use python; then > python_export PYTHON_SITEDIR > export PYTHON_BIN_PATH="${PYTHON}" > export PYTHON_LIB_PATH="${PYTHON_SITEDIR}" > else > export PYTHON_BIN_PATH="$(which python)" > export PYTHON_LIB_PATH="$(python -c 'from distutils.sysconfig import *; print(get_python_lib())')" > fi > > export TF_NEED_CUDA=$(usex cuda 1 0) > export TF_DOWNLOAD_CLANG=0 > export TF_CUDA_CLANG=0 > export TF_NEED_TENSORRT=0 > if use cuda; then > export TF_CUDA_PATHS="${EPREFIX%/}/opt/cuda" > export GCC_HOST_COMPILER_PATH="$(cuda_gccdir)/$(tc-getCC)" > export TF_CUDA_VERSION="$(cuda_toolkit_version)" > export TF_CUDNN_VERSION="$(cuda_cudnn_version)" > einfo "Setting CUDA version: $TF_CUDA_VERSION" > einfo "Setting CUDNN version: $TF_CUDNN_VERSION" > > if [[ -z "$TF_CUDA_COMPUTE_CAPABILITIES" ]]; then > ewarn "WARNING: Tensorflow 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 Tensorflow with the CUDA compute capability that is optimal for your GPU," > ewarn "set TF_CUDA_COMPUTE_CAPABILITIES in your make.conf, and re-emerge tensorflow." > ewarn "For example, to use CUDA capability 7.5 & 3.5, add: TF_CUDA_COMPUTE_CAPABILITIES=7.5,3.5" > 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 > fi > > # com_googlesource_code_re2 weird branch using absl, doesnt work with released re2 > local SYSLIBS=( > absl_py > astor_archive > boringssl > com_github_googleapis_googleapis > com_github_googlecloudplatform_google_cloud_cpp > com_google_protobuf > curl > cython > double_conversion > enum34_archive > flatbuffers > functools32_archive > gast_archive > gif > grpc > hwloc > icu > libjpeg_turbo > jsoncpp_git > lmdb > nasm > nsync > opt_einsum_archive > org_sqlite > pasta > pcre > png > six_archive > snappy > swig > termcolor_archive > wrapt > zlib_archive > ) > > export TF_SYSTEM_LIBS="${SYSLIBS[@]}" > export TF_IGNORE_MAX_BAZEL_VERSION=1 > > # This is not autoconf > ./configure || die > > echo 'build --config=noaws --config=nohdfs' >> .bazelrc || die > echo 'build --define tensorflow_mkldnn_contraction_kernel=0' >> .bazelrc || die > echo 'build --incompatible_no_support_tools_in_action_inputs=false' >> .bazelrc || die > } > if use python; then > python_foreach_impl run_in_build_dir do_configure > else > do_configure > fi >} > >src_compile() { > export JAVA_HOME=$(java-config --jre-home) # so keepwork works > > if use python; then > python_setup > BUILD_DIR="${S}-${EPYTHON/./_}" > cd "${BUILD_DIR}" > fi > > # fail early if any deps are missing > ebazel build --nobuild \ > //tensorflow:libtensorflow_framework.so \ > //tensorflow:libtensorflow.so \ > //tensorflow:libtensorflow_cc.so \ > $(usex python '//tensorflow/tools/pip_package:build_pip_package' '') > > ebazel build \ > //tensorflow:libtensorflow_framework.so \ > //tensorflow:libtensorflow.so > ebazel build //tensorflow:libtensorflow_cc.so > > do_compile() { > ebazel build //tensorflow/tools/pip_package:build_pip_package > } > BUILD_DIR="${S}" > cd "${BUILD_DIR}" > use python && python_foreach_impl run_in_build_dir do_compile > ebazel shutdown >} > >src_install() { > local i j > export JAVA_HOME=$(java-config --jre-home) # so keepwork works > > do_install() { > einfo "Installing ${EPYTHON} files" > local srcdir="${T}/src-${MULTIBUILD_VARIANT}" > mkdir -p "${srcdir}" || die > bazel-bin/tensorflow/tools/pip_package/build_pip_package --src "${srcdir}" || die > cd "${srcdir}" || die > esetup.py install > > # libtensorflow_framework.so is in /usr/lib already > python_export PYTHON_SITEDIR PYTHON_SCRIPTDIR > rm -f "${D}/${PYTHON_SITEDIR}"/${PN}/lib${PN}_framework.so* || die > rm -f "${D}/${PYTHON_SITEDIR}"/${PN}_core/lib${PN}_framework.so* || die > python_optimize > } > > if use python; then > python_foreach_impl run_in_build_dir do_install > > # Symlink to python-exec scripts > for i in "${ED}"/usr/lib/python-exec/*/*; do > n="${i##*/}" > [[ -e "${ED}/usr/bin/${n}" ]] || dosym ../lib/python-exec/python-exec2 "/usr/bin/${n}" > done > > python_setup > local BUILD_DIR="${S}-${EPYTHON/./_}" > cd "${BUILD_DIR}" || die > fi > > einfo "Installing headers" > ebazel build //tensorflow:install_headers > ebazel shutdown > insinto /usr/include/${PN}/ > doins -r bazel-bin/tensorflow/include/* > > einfo "Installing libs" > # Generate pkg-config file > ${PN}/c/generate-pc.sh --prefix="${EPREFIX}"/usr --libdir=$(get_libdir) --version=${MY_PV} || die > insinto /usr/$(get_libdir)/pkgconfig > doins ${PN}.pc ${PN}_cc.pc > > for l in libtensorflow{,_framework,_cc}.so; do > dolib.so bazel-bin/tensorflow/${l} > dolib.so bazel-bin/tensorflow/${l}.$(ver_cut 1 ${MY_PV}) > dolib.so bazel-bin/tensorflow/${l}.$(ver_cut 1-3 ${MY_PV}) > done > > einstalldocs >}
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bug 705712
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