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@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
on_temporary_creation(int size)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
product_notemporary(const MatrixType & m)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
test_product_notemporary()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