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 #define TEST_ENABLE_TEMPORARY_TRACKING 11 12 #include "main.h" 13 14 template<typename MatrixType> void product_notemporary(const MatrixType& m) 15 { 16 /* This test checks the number of temporaries created 17 * during the evaluation of a complex expression */ 18 typedef typename MatrixType::Index Index; 19 typedef typename MatrixType::Scalar Scalar; 20 typedef typename MatrixType::RealScalar RealScalar; 21 typedef Matrix<Scalar, 1, Dynamic> RowVectorType; 22 typedef Matrix<Scalar, Dynamic, 1> ColVectorType; 23 typedef Matrix<Scalar, Dynamic, Dynamic, ColMajor> ColMajorMatrixType; 24 typedef Matrix<Scalar, Dynamic, Dynamic, RowMajor> RowMajorMatrixType; 25 26 Index rows = m.rows(); 27 Index cols = m.cols(); 28 29 ColMajorMatrixType m1 = MatrixType::Random(rows, cols), 30 m2 = MatrixType::Random(rows, cols), 31 m3(rows, cols); 32 RowVectorType rv1 = RowVectorType::Random(rows), rvres(rows); 33 ColVectorType cv1 = ColVectorType::Random(cols), cvres(cols); 34 RowMajorMatrixType rm3(rows, cols); 35 36 Scalar s1 = internal::random<Scalar>(), 37 s2 = internal::random<Scalar>(), 38 s3 = internal::random<Scalar>(); 39 40 Index c0 = internal::random<Index>(4,cols-8), 41 c1 = internal::random<Index>(8,cols-c0), 42 r0 = internal::random<Index>(4,cols-8), 43 r1 = internal::random<Index>(8,rows-r0); 44 45 VERIFY_EVALUATION_COUNT( m3 = (m1 * m2.adjoint()), 1); 46 VERIFY_EVALUATION_COUNT( m3 = (m1 * m2.adjoint()).transpose(), 1); 47 VERIFY_EVALUATION_COUNT( m3.noalias() = m1 * m2.adjoint(), 0); 48 49 VERIFY_EVALUATION_COUNT( m3 = s1 * (m1 * m2.transpose()), 1); 50 // VERIFY_EVALUATION_COUNT( m3 = m3 + s1 * (m1 * m2.transpose()), 1); 51 VERIFY_EVALUATION_COUNT( m3.noalias() = s1 * (m1 * m2.transpose()), 0); 52 53 VERIFY_EVALUATION_COUNT( m3 = m3 + (m1 * m2.adjoint()), 1); 54 VERIFY_EVALUATION_COUNT( m3 = m3 - (m1 * m2.adjoint()), 1); 55 56 VERIFY_EVALUATION_COUNT( m3 = m3 + (m1 * m2.adjoint()).transpose(), 1); 57 VERIFY_EVALUATION_COUNT( m3.noalias() = m3 + m1 * m2.transpose(), 0); 58 VERIFY_EVALUATION_COUNT( m3.noalias() += m3 + m1 * m2.transpose(), 0); 59 VERIFY_EVALUATION_COUNT( m3.noalias() -= m3 + m1 * m2.transpose(), 0); 60 VERIFY_EVALUATION_COUNT( m3.noalias() = m3 - m1 * m2.transpose(), 0); 61 VERIFY_EVALUATION_COUNT( m3.noalias() += m3 - m1 * m2.transpose(), 0); 62 VERIFY_EVALUATION_COUNT( m3.noalias() -= m3 - m1 * m2.transpose(), 0); 63 64 VERIFY_EVALUATION_COUNT( m3.noalias() = s1 * m1 * s2 * m2.adjoint(), 0); 65 VERIFY_EVALUATION_COUNT( m3.noalias() = s1 * m1 * s2 * (m1*s3+m2*s2).adjoint(), 1); 66 VERIFY_EVALUATION_COUNT( m3.noalias() = (s1 * m1).adjoint() * s2 * m2, 0); 67 VERIFY_EVALUATION_COUNT( m3.noalias() += s1 * (-m1*s3).adjoint() * (s2 * m2 * s3), 0); 68 VERIFY_EVALUATION_COUNT( m3.noalias() -= s1 * (m1.transpose() * m2), 0); 69 70 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); 71 VERIFY_EVALUATION_COUNT(( m3.block(r0,r0,r1,r1).noalias() -= s1 * m1.block(r0,c0,r1,c1) * m2.block(c0,r0,c1,r1) ), 0); 72 73 // NOTE this is because the Block expression is not handled yet by our expression analyser 74 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); 75 76 VERIFY_EVALUATION_COUNT( m3.noalias() -= (s1 * m1).template triangularView<Lower>() * m2, 0); 77 VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template triangularView<Upper>() * (m2+m2), 1); 78 VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template triangularView<UnitUpper>() * m2.adjoint(), 0); 79 80 VERIFY_EVALUATION_COUNT( m3.template triangularView<Upper>() = (m1 * m2.adjoint()), 0); 81 VERIFY_EVALUATION_COUNT( m3.template triangularView<Upper>() -= (m1 * m2.adjoint()), 0); 82 83 // 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 84 VERIFY_EVALUATION_COUNT( rm3.col(c0).noalias() = (s1 * m1.adjoint()).template triangularView<UnitUpper>() * (s2*m2.row(c0)).adjoint(), 1); 85 86 VERIFY_EVALUATION_COUNT( m1.template triangularView<Lower>().solveInPlace(m3), 0); 87 VERIFY_EVALUATION_COUNT( m1.adjoint().template triangularView<Lower>().solveInPlace(m3.transpose()), 0); 88 89 VERIFY_EVALUATION_COUNT( m3.noalias() -= (s1 * m1).adjoint().template selfadjointView<Lower>() * (-m2*s3).adjoint(), 0); 90 VERIFY_EVALUATION_COUNT( m3.noalias() = s2 * m2.adjoint() * (s1 * m1.adjoint()).template selfadjointView<Upper>(), 0); 91 VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template selfadjointView<Lower>() * m2.adjoint(), 0); 92 93 // 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 94 VERIFY_EVALUATION_COUNT( m3.col(c0).noalias() = (s1 * m1).adjoint().template selfadjointView<Lower>() * (-m2.row(c0)*s3).adjoint(), 1); 95 VERIFY_EVALUATION_COUNT( m3.col(c0).noalias() -= (s1 * m1).adjoint().template selfadjointView<Upper>() * (-m2.row(c0)*s3).adjoint(), 1); 96 97 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); 98 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); 99 100 VERIFY_EVALUATION_COUNT( m3.template selfadjointView<Lower>().rankUpdate(m2.adjoint()), 0); 101 102 // Here we will get 1 temporary for each resize operation of the lhs operator; resize(r1,c1) would lead to zero temporaries 103 m3.resize(1,1); 104 VERIFY_EVALUATION_COUNT( m3.noalias() = m1.block(r0,r0,r1,r1).template selfadjointView<Lower>() * m2.block(r0,c0,r1,c1), 1); 105 m3.resize(1,1); 106 VERIFY_EVALUATION_COUNT( m3.noalias() = m1.block(r0,r0,r1,r1).template triangularView<UnitUpper>() * m2.block(r0,c0,r1,c1), 1); 107 108 // Zero temporaries for lazy products ... 109 VERIFY_EVALUATION_COUNT( Scalar tmp = 0; tmp += Scalar(RealScalar(1)) / (m3.transpose().lazyProduct(m3)).diagonal().sum(), 0 ); 110 111 // ... and even no temporary for even deeply (>=2) nested products 112 VERIFY_EVALUATION_COUNT( Scalar tmp = 0; tmp += Scalar(RealScalar(1)) / (m3.transpose() * m3).diagonal().sum(), 0 ); 113 VERIFY_EVALUATION_COUNT( Scalar tmp = 0; tmp += Scalar(RealScalar(1)) / (m3.transpose() * m3).diagonal().array().abs().sum(), 0 ); 114 115 // Zero temporaries for ... CoeffBasedProductMode 116 VERIFY_EVALUATION_COUNT( m3.col(0).template head<5>() * m3.col(0).transpose() + m3.col(0).template head<5>() * m3.col(0).transpose(), 0 ); 117 118 // Check matrix * vectors 119 VERIFY_EVALUATION_COUNT( cvres.noalias() = m1 * cv1, 0 ); 120 VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * cv1, 0 ); 121 VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * m2.col(0), 0 ); 122 VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * rv1.adjoint(), 0 ); 123 VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * m2.row(0).transpose(), 0 ); 124 125 VERIFY_EVALUATION_COUNT( cvres.noalias() = (m1+m1) * cv1, 0 ); 126 VERIFY_EVALUATION_COUNT( cvres.noalias() = (rm3+rm3) * cv1, 0 ); 127 VERIFY_EVALUATION_COUNT( cvres.noalias() = (m1+m1) * (m1*cv1), 1 ); 128 VERIFY_EVALUATION_COUNT( cvres.noalias() = (rm3+rm3) * (m1*cv1), 1 ); 129 130 // Check outer products 131 m3 = cv1 * rv1; 132 VERIFY_EVALUATION_COUNT( m3.noalias() = cv1 * rv1, 0 ); 133 VERIFY_EVALUATION_COUNT( m3.noalias() = (cv1+cv1) * (rv1+rv1), 1 ); 134 VERIFY_EVALUATION_COUNT( m3.noalias() = (m1*cv1) * (rv1), 1 ); 135 VERIFY_EVALUATION_COUNT( m3.noalias() += (m1*cv1) * (rv1), 1 ); 136 VERIFY_EVALUATION_COUNT( rm3.noalias() = (cv1) * (rv1 * m1), 1 ); 137 VERIFY_EVALUATION_COUNT( rm3.noalias() -= (cv1) * (rv1 * m1), 1 ); 138 VERIFY_EVALUATION_COUNT( rm3.noalias() = (m1*cv1) * (rv1 * m1), 2 ); 139 VERIFY_EVALUATION_COUNT( rm3.noalias() += (m1*cv1) * (rv1 * m1), 2 ); 140 141 // Check nested products 142 VERIFY_EVALUATION_COUNT( cvres.noalias() = m1.adjoint() * m1 * cv1, 1 ); 143 VERIFY_EVALUATION_COUNT( rvres.noalias() = rv1 * (m1 * m2.adjoint()), 1 ); 144 } 145 146 void test_product_notemporary() 147 { 148 int s; 149 for(int i = 0; i < g_repeat; i++) { 150 s = internal::random<int>(16,EIGEN_TEST_MAX_SIZE); 151 CALL_SUBTEST_1( product_notemporary(MatrixXf(s, s)) ); 152 CALL_SUBTEST_2( product_notemporary(MatrixXd(s, s)) ); 153 TEST_SET_BUT_UNUSED_VARIABLE(s) 154 155 s = internal::random<int>(16,EIGEN_TEST_MAX_SIZE/2); 156 CALL_SUBTEST_3( product_notemporary(MatrixXcf(s,s)) ); 157 CALL_SUBTEST_4( product_notemporary(MatrixXcd(s,s)) ); 158 TEST_SET_BUT_UNUSED_VARIABLE(s) 159 } 160 } 161
