1 // This file is part of Eigen, a lightweight C++ template library 2 // for linear algebra. 3 // 4 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1 (at) gmail.com> 5 // 6 // This Source Code Form is subject to the terms of the Mozilla 7 // Public License v. 2.0. If a copy of the MPL was not distributed 8 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 9 10 static int nb_temporaries; 11 12 inline void on_temporary_creation(int size) { 13 // here's a great place to set a breakpoint when debugging failures in this test! 14 if(size!=0) nb_temporaries++; 15 } 16 17 18 #define EIGEN_DENSE_STORAGE_CTOR_PLUGIN { on_temporary_creation(size); } 19 20 #include "main.h" 21 22 #define VERIFY_EVALUATION_COUNT(XPR,N) {\ 23 nb_temporaries = 0; \ 24 XPR; \ 25 if(nb_temporaries!=N) std::cerr << "nb_temporaries == " << nb_temporaries << "\n"; \ 26 VERIFY( (#XPR) && nb_temporaries==N ); \ 27 } 28 29 template<typename MatrixType> void product_notemporary(const MatrixType& m) 30 { 31 /* This test checks the number of temporaries created 32 * during the evaluation of a complex expression */ 33 typedef typename MatrixType::Index Index; 34 typedef typename MatrixType::Scalar Scalar; 35 typedef typename MatrixType::RealScalar RealScalar; 36 typedef Matrix<Scalar, 1, Dynamic> RowVectorType; 37 typedef Matrix<Scalar, Dynamic, 1> ColVectorType; 38 typedef Matrix<Scalar, Dynamic, Dynamic, ColMajor> ColMajorMatrixType; 39 typedef Matrix<Scalar, Dynamic, Dynamic, RowMajor> RowMajorMatrixType; 40 41 Index rows = m.rows(); 42 Index cols = m.cols(); 43 44 ColMajorMatrixType m1 = MatrixType::Random(rows, cols), 45 m2 = MatrixType::Random(rows, cols), 46 m3(rows, cols); 47 RowVectorType rv1 = RowVectorType::Random(rows), rvres(rows); 48 ColVectorType cv1 = ColVectorType::Random(cols), cvres(cols); 49 RowMajorMatrixType rm3(rows, cols); 50 51 Scalar s1 = internal::random<Scalar>(), 52 s2 = internal::random<Scalar>(), 53 s3 = internal::random<Scalar>(); 54 55 Index c0 = internal::random<Index>(4,cols-8), 56 c1 = internal::random<Index>(8,cols-c0), 57 r0 = internal::random<Index>(4,cols-8), 58 r1 = internal::random<Index>(8,rows-r0); 59 60 VERIFY_EVALUATION_COUNT( m3 = (m1 * m2.adjoint()), 1); 61 VERIFY_EVALUATION_COUNT( m3.noalias() = m1 * m2.adjoint(), 0); 62 63 VERIFY_EVALUATION_COUNT( m3.noalias() = s1 * (m1 * m2.transpose()), 0); 64 65 VERIFY_EVALUATION_COUNT( m3.noalias() = s1 * m1 * s2 * m2.adjoint(), 0); 66 VERIFY_EVALUATION_COUNT( m3.noalias() = s1 * m1 * s2 * (m1*s3+m2*s2).adjoint(), 1); 67 VERIFY_EVALUATION_COUNT( m3.noalias() = (s1 * m1).adjoint() * s2 * m2, 0); 68 VERIFY_EVALUATION_COUNT( m3.noalias() += s1 * (-m1*s3).adjoint() * (s2 * m2 * s3), 0); 69 VERIFY_EVALUATION_COUNT( m3.noalias() -= s1 * (m1.transpose() * m2), 0); 70 71 VERIFY_EVALUATION_COUNT(( m3.block(r0,r0,r1,r1).noalias() += -m1.block(r0,c0,r1,c1) * (s2*m2.block(r0,c0,r1,c1)).adjoint() ), 0); 72 VERIFY_EVALUATION_COUNT(( m3.block(r0,r0,r1,r1).noalias() -= s1 * m1.block(r0,c0,r1,c1) * m2.block(c0,r0,c1,r1) ), 0); 73 74 // NOTE this is because the Block expression is not handled yet by our expression analyser 75 VERIFY_EVALUATION_COUNT(( m3.block(r0,r0,r1,r1).noalias() = s1 * m1.block(r0,c0,r1,c1) * (s1*m2).block(c0,r0,c1,r1) ), 1); 76 77 VERIFY_EVALUATION_COUNT( m3.noalias() -= (s1 * m1).template triangularView<Lower>() * m2, 0); 78 VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template triangularView<Upper>() * (m2+m2), 1); 79 VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template triangularView<UnitUpper>() * m2.adjoint(), 0); 80 81 VERIFY_EVALUATION_COUNT( m3.template triangularView<Upper>() = (m1 * m2.adjoint()), 0); 82 VERIFY_EVALUATION_COUNT( m3.template triangularView<Upper>() -= (m1 * m2.adjoint()), 0); 83 84 // NOTE this is because the blas_traits require innerstride==1 to avoid a temporary, but that doesn't seem to be actually needed for the triangular products 85 VERIFY_EVALUATION_COUNT( rm3.col(c0).noalias() = (s1 * m1.adjoint()).template triangularView<UnitUpper>() * (s2*m2.row(c0)).adjoint(), 1); 86 87 VERIFY_EVALUATION_COUNT( m1.template triangularView<Lower>().solveInPlace(m3), 0); 88 VERIFY_EVALUATION_COUNT( m1.adjoint().template triangularView<Lower>().solveInPlace(m3.transpose()), 0); 89 90 VERIFY_EVALUATION_COUNT( m3.noalias() -= (s1 * m1).adjoint().template selfadjointView<Lower>() * (-m2*s3).adjoint(), 0); 91 VERIFY_EVALUATION_COUNT( m3.noalias() = s2 * m2.adjoint() * (s1 * m1.adjoint()).template selfadjointView<Upper>(), 0); 92 VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template selfadjointView<Lower>() * m2.adjoint(), 0); 93 94 // NOTE this is because the blas_traits require innerstride==1 to avoid a temporary, but that doesn't seem to be actually needed for the triangular products 95 VERIFY_EVALUATION_COUNT( m3.col(c0).noalias() = (s1 * m1).adjoint().template selfadjointView<Lower>() * (-m2.row(c0)*s3).adjoint(), 1); 96 VERIFY_EVALUATION_COUNT( m3.col(c0).noalias() -= (s1 * m1).adjoint().template selfadjointView<Upper>() * (-m2.row(c0)*s3).adjoint(), 1); 97 98 VERIFY_EVALUATION_COUNT( m3.block(r0,c0,r1,c1).noalias() += m1.block(r0,r0,r1,r1).template selfadjointView<Upper>() * (s1*m2.block(r0,c0,r1,c1)), 0); 99 VERIFY_EVALUATION_COUNT( m3.block(r0,c0,r1,c1).noalias() = m1.block(r0,r0,r1,r1).template selfadjointView<Upper>() * m2.block(r0,c0,r1,c1), 0); 100 101 VERIFY_EVALUATION_COUNT( m3.template selfadjointView<Lower>().rankUpdate(m2.adjoint()), 0); 102 103 // Here we will get 1 temporary for each resize operation of the lhs operator; resize(r1,c1) would lead to zero temporaries 104 m3.resize(1,1); 105 VERIFY_EVALUATION_COUNT( m3.noalias() = m1.block(r0,r0,r1,r1).template selfadjointView<Lower>() * m2.block(r0,c0,r1,c1), 1); 106 m3.resize(1,1); 107 VERIFY_EVALUATION_COUNT( m3.noalias() = m1.block(r0,r0,r1,r1).template triangularView<UnitUpper>() * m2.block(r0,c0,r1,c1), 1); 108 109 // Zero temporaries for lazy products ... 110 VERIFY_EVALUATION_COUNT( Scalar tmp = 0; tmp += Scalar(RealScalar(1)) / (m3.transpose().lazyProduct(m3)).diagonal().sum(), 0 ); 111 112 // ... and even no temporary for even deeply (>=2) nested products 113 VERIFY_EVALUATION_COUNT( Scalar tmp = 0; tmp += Scalar(RealScalar(1)) / (m3.transpose() * m3).diagonal().sum(), 0 ); 114 VERIFY_EVALUATION_COUNT( Scalar tmp = 0; tmp += Scalar(RealScalar(1)) / (m3.transpose() * m3).diagonal().array().abs().sum(), 0 ); 115 116 // Zero temporaries for ... CoeffBasedProductMode 117 // - does not work with GCC because of the <..>, we'ld need variadic macros ... 118 //VERIFY_EVALUATION_COUNT( m3.col(0).head<5>() * m3.col(0).transpose() + m3.col(0).head<5>() * m3.col(0).transpose(), 0 ); 119 120 // Check matrix * vectors 121 VERIFY_EVALUATION_COUNT( cvres.noalias() = m1 * cv1, 0 ); 122 VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * cv1, 0 ); 123 VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * m2.col(0), 0 ); 124 VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * rv1.adjoint(), 0 ); 125 VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * m2.row(0).transpose(), 0 ); 126 } 127 128 void test_product_notemporary() 129 { 130 int s; 131 for(int i = 0; i < g_repeat; i++) { 132 s = internal::random<int>(16,EIGEN_TEST_MAX_SIZE); 133 CALL_SUBTEST_1( product_notemporary(MatrixXf(s, s)) ); 134 s = internal::random<int>(16,EIGEN_TEST_MAX_SIZE); 135 CALL_SUBTEST_2( product_notemporary(MatrixXd(s, s)) ); 136 s = internal::random<int>(16,EIGEN_TEST_MAX_SIZE/2); 137 CALL_SUBTEST_3( product_notemporary(MatrixXcf(s,s)) ); 138 s = internal::random<int>(16,EIGEN_TEST_MAX_SIZE/2); 139 CALL_SUBTEST_4( product_notemporary(MatrixXcd(s,s)) ); 140 } 141 } 142
