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Merged eigen/eigen into default
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3f80696ae1
@ -221,6 +221,12 @@ if(NOT MSVC)
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message(STATUS "Enabling FMA in tests/examples")
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endif()
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option(EIGEN_TEST_F16C "Enable/Disable F16C in tests/examples" OFF)
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if(EIGEN_TEST_F16C)
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mf16c")
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message(STATUS "Enabling F16C in tests/examples")
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endif()
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option(EIGEN_TEST_ALTIVEC "Enable/Disable AltiVec in tests/examples" OFF)
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if(EIGEN_TEST_ALTIVEC)
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -maltivec -mabi=altivec")
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@ -397,6 +397,10 @@ CompleteOrthogonalDecomposition<MatrixType>& CompleteOrthogonalDecomposition<
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const Index rank = m_cpqr.rank();
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const Index cols = matrix.cols();
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const Index rows = matrix.rows();
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m_zCoeffs.resize((std::min)(rows, cols));
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m_temp.resize(cols);
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if (rank < cols) {
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// We have reduced the (permuted) matrix to the form
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// [R11 R12]
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@ -201,9 +201,15 @@ template <typename Device, typename T> class BenchmarkSuite {
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size_b[1] = k_/2;
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TensorMap<Tensor<T, 2>, Eigen::Aligned> B(b_, size_b);
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#ifndef EIGEN_HAS_INDEX_LIST
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Eigen::array<TensorIndex, 2> strides;
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strides[0] = 1;
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strides[1] = 2;
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#else
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// Take advantage of cxx11 to give the compiler information it can use to
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// optimize the code.
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Eigen::IndexList<Eigen::type2index<1>, Eigen::type2index<2> > strides;
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#endif
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StartBenchmarkTiming();
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for (int iter = 0; iter < num_iters; ++iter) {
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@ -14,7 +14,13 @@ namespace Eigen {
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// Use the SimpleThreadPool by default. We'll switch to the new non blocking
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// thread pool later.
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#ifdef EIGEN_USE_NONBLOCKING_THREAD_POOL
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template <typename Env> using ThreadPoolTempl = NonBlockingThreadPoolTempl<Env>;
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typedef NonBlockingThreadPool ThreadPool;
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#else
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template <typename Env> using ThreadPoolTempl = SimpleThreadPoolTempl<Env>;
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typedef SimpleThreadPool ThreadPool;
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#endif
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// Barrier is an object that allows one or more threads to wait until
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@ -135,7 +135,7 @@ class TensorExecutor<Expression, ThreadPoolDevice, Vectorizable> {
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{
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const Index PacketSize = Vectorizable ? unpacket_traits<typename Evaluator::PacketReturnType>::size : 1;
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const Index size = array_prod(evaluator.dimensions());
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int num_threads = device.numThreads();
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size_t num_threads = device.numThreads();
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#ifdef EIGEN_USE_COST_MODEL
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if (num_threads > 1) {
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num_threads = TensorCostModel<ThreadPoolDevice>::numThreads(
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@ -168,7 +168,7 @@ class RunQueue {
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// larger than it is during concurrent modifications. E.g. pop can
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// decrement size before the corresponding push has incremented it.
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// So the computed size can be up to kSize + 1, fix it.
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if (size > kSize) size = kSize;
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if (size > static_cast<int>(kSize)) size = kSize;
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return size;
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}
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}
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@ -95,7 +95,7 @@ static void test_stress_eventcount()
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ec.Notify(false);
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continue;
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}
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std::this_thread::yield();
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EIGEN_THREAD_YIELD();
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j--;
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}
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}));
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@ -30,11 +30,11 @@ void test_basic_runqueue()
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RunQueue<int, 4> q;
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// Check empty state.
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VERIFY(q.Empty());
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VERIFY_IS_EQUAL(0, q.Size());
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VERIFY_IS_EQUAL(0u, q.Size());
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VERIFY_IS_EQUAL(0, q.PopFront());
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std::vector<int> stolen;
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VERIFY_IS_EQUAL(0, q.PopBackHalf(&stolen));
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VERIFY_IS_EQUAL(0, stolen.size());
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VERIFY_IS_EQUAL(0u, stolen.size());
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// Push one front, pop one front.
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VERIFY_IS_EQUAL(0, q.PushFront(1));
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VERIFY_IS_EQUAL(1, q.Size());
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@ -184,7 +184,7 @@ void test_stress_runqueue()
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sum += j;
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continue;
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}
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std::this_thread::yield();
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EIGEN_THREAD_YIELD();
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j--;
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}
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total += sum;
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@ -194,7 +194,7 @@ void test_stress_runqueue()
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std::vector<int> stolen;
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for (int j = 1; j < kEvents;) {
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if (q.PopBackHalf(&stolen) == 0) {
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std::this_thread::yield();
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EIGEN_THREAD_YIELD();
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continue;
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}
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while (stolen.size() && j < kEvents) {
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@ -209,7 +209,7 @@ void test_stress_runqueue()
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int v = stolen.back();
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stolen.pop_back();
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VERIFY_IS_NOT_EQUAL(v, 0);
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while ((v = q.PushBack(v)) != 0) std::this_thread::yield();
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while ((v = q.PushBack(v)) != 0) EIGEN_THREAD_YIELD();
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}
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total -= sum;
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}));
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