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dev-cpp/tiny-dnn: initial import
Signed-off-by: Alessandro Barbieri <lssndrbarbieri@gmail.com>
This commit is contained in:
Alessandro Barbieri
1
dev-cpp/tiny-dnn/Manifest
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1
dev-cpp/tiny-dnn/Manifest
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DIST tiny-dnn-1.0.0_alpha3.tar.gz 12885646 BLAKE2B 85c0715ab6c692b77522487775e70b0db645528baed1830c83c9f44d2b67a5207e4f7ea1709b35c6a4217d287199549304e9be19f4a5cec9a1183b0b5dccc562 SHA512 5f2c1a161771efa67e85b1fea395953b7744e29f61187ac5a6c54c912fb195b3aef9a5827135c3668bd0eeea5ae04a33cc433e1f6683e2b7955010a2632d168b
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@@ -0,0 +1,11 @@
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--- a/docs/conf.py
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+++ b/docs/conf.py
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@@ -32,7 +32,7 @@
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# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
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# ones.
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extensions = [
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- 'sphinx.ext.mathjax'
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+ 'sphinx.ext.mathjax', 'sphinx.ext.autodoc'
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]
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# Add any paths that contain templates here, relative to this directory.
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29
dev-cpp/tiny-dnn/files/tiny-dnn-disable-gtest-download.patch
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dev-cpp/tiny-dnn/files/tiny-dnn-disable-gtest-download.patch
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--- a/test/CMakeLists.txt
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+++ b/test/CMakeLists.txt
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@@ -2,17 +2,6 @@
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enable_testing()
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-include(../cmake/DownloadProject/DownloadProject.cmake)
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-#set(gtest_disable_pthreads on) #TODO(randl): Windows?
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-download_project(
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- PROJ googletest
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- GIT_REPOSITORY https://github.com/google/googletest.git
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- GIT_TAG master
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- UPDATE_DISCONNECTED 1
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-)
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-
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-add_subdirectory(${googletest_SOURCE_DIR} ${googletest_BINARY_DIR})
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-
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enable_testing()
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# in ../googletest-src/googletest/CMakeLists.txt, BUILD_SHARED_LIBS is set to OFF
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@@ -29,7 +18,7 @@
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add_executable(tiny_dnn_test test.cpp test_no_duplicate_symbols.cpp)
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target_link_libraries(tiny_dnn_test
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- ${project_library_target_name} ${REQUIRED_LIBRARIES} gtest gmock)
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+ ${project_library_target_name} ${REQUIRED_LIBRARIES})
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add_test(all_tests tiny_dnn_test)
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# workaround for https://gitlab.kitware.com/cmake/cmake/issues/8774
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89
dev-cpp/tiny-dnn/metadata.xml
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dev-cpp/tiny-dnn/metadata.xml
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<?xml version="1.0" encoding="UTF-8"?>
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<!DOCTYPE pkgmetadata SYSTEM "http://www.gentoo.org/dtd/metadata.dtd">
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<pkgmetadata>
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<maintainer type="person">
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<email>lssndrbarbieri@gmail.com</email>
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<name>Alessandro Barbieri</name>
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</maintainer>
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<longdescription>
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Features
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Reasonably fast, without GPU:
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With TBB threading and SSE/AVX vectorization.
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98.8% accuracy on MNIST in 13 minutes training (@Core i7-3520M).
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Portable and header-only:
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Runs anywhere as long as you have a compiler which supports C++14.
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Just include tiny_dnn.h and write your model in C++. There is nothing to install.
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Easy to integrate with real applications:
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No output to stdout/stderr.
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A constant throughput (simple parallelization model, no garbage collection).
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Works without throwing an exception.
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Can import caffe's model.
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Simply implemented:
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A good library for learning neural networks.
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Supported networks
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layer-types
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core
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fully connected
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dropout
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linear operation
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zero padding
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power
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convolution
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convolutional
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average pooling
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max pooling
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deconvolutional
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average unpooling
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max unpooling
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normalization
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contrast normalization (only forward pass)
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batch normalization
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split/merge
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concat
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slice
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elementwise-add
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activation functions
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tanh
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asinh
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sigmoid
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softmax
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softplus
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softsign
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rectified linear(relu)
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leaky relu
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identity
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scaled tanh
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exponential linear units(elu)
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scaled exponential linear units (selu)
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loss functions
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cross-entropy
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mean squared error
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mean absolute error
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mean absolute error with epsilon range
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optimization algorithms
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stochastic gradient descent (with/without L2 normalization)
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momentum and Nesterov momentum
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adagrad
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rmsprop
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adam
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adamax
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</longdescription>
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<use>
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<flag name="double-precision">Build tiny-dnn with double precision computations</flag>
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<!--<flag name="libdnn">Build tiny-dnn with GreenteaLibDNN library support</flag>-->
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<!--<flag name="nnpack">Build tiny-dnn with NNPACK library support</flag>-->
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<flag name="opencl">Build tiny-dnn with OpenCL library support</flag>
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<flag name="serialization">Build tiny-dnn with Serialization support</flag>
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<flag name="tbb">Build tiny-dnn with TBB library support</flag>
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</use>
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<upstream>
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<remote-id type="github">tiny-dnn/tiny-dnn</remote-id>
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</upstream>
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</pkgmetadata>
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84
dev-cpp/tiny-dnn/tiny-dnn-1.0.0_alpha3.ebuild
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dev-cpp/tiny-dnn/tiny-dnn-1.0.0_alpha3.ebuild
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# Copyright 1999-2021 Gentoo Authors
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# Distributed under the terms of the GNU General Public License v2
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EAPI=7
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DOCS_BUILDER="sphinx"
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DOCS_DEPEND="dev-python/recommonmark"
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DOCS_DIR="docs"
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MYPV="${PV/_alpha/a}"
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PYTHON_COMPAT=( python3_{7,8,9} )
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inherit cmake python-any-r1 docs
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DESCRIPTION="header only, dependency-free deep learning framework in C++14"
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HOMEPAGE="https://github.com/tiny-dnn/tiny-dnn"
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SRC_URI="https://github.com/${PN}/${PN}/archive/refs/tags/v${MYPV}.tar.gz -> ${P}.tar.gz"
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S="${WORKDIR}/${PN}-${MYPV}"
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LICENSE="BSD"
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SLOT="0"
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KEYWORDS="~amd64"
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IUSE="cpu_flags_x86_avx cpu_flags_x86_avx2 cpu_flags_x86_sse double-precision opencl openmp +serialization tbb test"
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REQUIRED_USE="
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?? ( openmp tbb )
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"
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RESTRICT="test" #tests doesn't build ...
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# headers as rdepend because this is also an header only library
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RDEPEND="
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opencl? (
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dev-util/opencl-headers
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virtual/opencl
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)
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serialization? ( dev-libs/cereal )
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tbb? ( dev-cpp/tbb )
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"
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DEPEND="${RDEPEND}"
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BDEPEND="
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test? ( dev-cpp/gtest )
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"
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PATCHES=(
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"${FILESDIR}/${PN}-add-sphinx-ext-autodoc-to-conf-py.patch"
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"${FILESDIR}/${PN}-disable-gtest-download.patch"
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)
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src_prepare() {
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#remove bundled cereal
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rm -r cereal || die
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cmake_src_prepare
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}
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src_configure() {
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local mycmakeargs=(
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-DBUILD_DOCS=OFF
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-DBUILD_EXAMPLES=OFF
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-DCOVERALLS=OFF
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-DUSE_LIBDNN=OFF
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-DUSE_NNPACK=OFF
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-DBUILD_TESTS=$(usex test)
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-DUSE_AVX=$(usex cpu_flags_x86_avx)
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-DUSE_AVX2=$(usex cpu_flags_x86_avx2)
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-DUSE_DOUBLE=$(usex double-precision)
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-DUSE_OMP=$(usex openmp)
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-DUSE_OPENCL=$(usex opencl)
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-DUSE_SERIALIZER=$(usex serialization)
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-DUSE_SSE=$(usex cpu_flags_x86_sse)
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-DUSE_TBB=$(usex tbb)
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)
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cmake_src_configure
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}
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src_compile() {
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cmake_src_compile
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docs_compile
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}
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src_install() {
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cmake_src_install
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if use doc; then
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dodoc -r _build/html
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docompress -x "/usr/share/doc/${PF}/html"
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fi
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}
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