You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

141 lines
7.3 KiB

  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. static int nb_temporaries;
  10. inline void on_temporary_creation(int size) {
  11. // here's a great place to set a breakpoint when debugging failures in this test!
  12. if(size!=0) nb_temporaries++;
  13. }
  14. #define EIGEN_DENSE_STORAGE_CTOR_PLUGIN { on_temporary_creation(size); }
  15. #include "main.h"
  16. #define VERIFY_EVALUATION_COUNT(XPR,N) {\
  17. nb_temporaries = 0; \
  18. XPR; \
  19. if(nb_temporaries!=N) std::cerr << "nb_temporaries == " << nb_temporaries << "\n"; \
  20. VERIFY( (#XPR) && nb_temporaries==N ); \
  21. }
  22. template<typename MatrixType> void product_notemporary(const MatrixType& m)
  23. {
  24. /* This test checks the number of temporaries created
  25. * during the evaluation of a complex expression */
  26. typedef typename MatrixType::Index Index;
  27. typedef typename MatrixType::Scalar Scalar;
  28. typedef typename MatrixType::RealScalar RealScalar;
  29. typedef Matrix<Scalar, 1, Dynamic> RowVectorType;
  30. typedef Matrix<Scalar, Dynamic, 1> ColVectorType;
  31. typedef Matrix<Scalar, Dynamic, Dynamic, ColMajor> ColMajorMatrixType;
  32. typedef Matrix<Scalar, Dynamic, Dynamic, RowMajor> RowMajorMatrixType;
  33. Index rows = m.rows();
  34. Index cols = m.cols();
  35. ColMajorMatrixType m1 = MatrixType::Random(rows, cols),
  36. m2 = MatrixType::Random(rows, cols),
  37. m3(rows, cols);
  38. RowVectorType rv1 = RowVectorType::Random(rows), rvres(rows);
  39. ColVectorType cv1 = ColVectorType::Random(cols), cvres(cols);
  40. RowMajorMatrixType rm3(rows, cols);
  41. Scalar s1 = internal::random<Scalar>(),
  42. s2 = internal::random<Scalar>(),
  43. s3 = internal::random<Scalar>();
  44. Index c0 = internal::random<Index>(4,cols-8),
  45. c1 = internal::random<Index>(8,cols-c0),
  46. r0 = internal::random<Index>(4,cols-8),
  47. r1 = internal::random<Index>(8,rows-r0);
  48. VERIFY_EVALUATION_COUNT( m3 = (m1 * m2.adjoint()), 1);
  49. VERIFY_EVALUATION_COUNT( m3.noalias() = m1 * m2.adjoint(), 0);
  50. VERIFY_EVALUATION_COUNT( m3.noalias() = s1 * (m1 * m2.transpose()), 0);
  51. VERIFY_EVALUATION_COUNT( m3.noalias() = s1 * m1 * s2 * m2.adjoint(), 0);
  52. VERIFY_EVALUATION_COUNT( m3.noalias() = s1 * m1 * s2 * (m1*s3+m2*s2).adjoint(), 1);
  53. VERIFY_EVALUATION_COUNT( m3.noalias() = (s1 * m1).adjoint() * s2 * m2, 0);
  54. VERIFY_EVALUATION_COUNT( m3.noalias() += s1 * (-m1*s3).adjoint() * (s2 * m2 * s3), 0);
  55. VERIFY_EVALUATION_COUNT( m3.noalias() -= s1 * (m1.transpose() * m2), 0);
  56. 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);
  57. VERIFY_EVALUATION_COUNT(( m3.block(r0,r0,r1,r1).noalias() -= s1 * m1.block(r0,c0,r1,c1) * m2.block(c0,r0,c1,r1) ), 0);
  58. // NOTE this is because the Block expression is not handled yet by our expression analyser
  59. 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);
  60. VERIFY_EVALUATION_COUNT( m3.noalias() -= (s1 * m1).template triangularView<Lower>() * m2, 0);
  61. VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template triangularView<Upper>() * (m2+m2), 1);
  62. VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template triangularView<UnitUpper>() * m2.adjoint(), 0);
  63. VERIFY_EVALUATION_COUNT( m3.template triangularView<Upper>() = (m1 * m2.adjoint()), 0);
  64. VERIFY_EVALUATION_COUNT( m3.template triangularView<Upper>() -= (m1 * m2.adjoint()), 0);
  65. // 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
  66. VERIFY_EVALUATION_COUNT( rm3.col(c0).noalias() = (s1 * m1.adjoint()).template triangularView<UnitUpper>() * (s2*m2.row(c0)).adjoint(), 1);
  67. VERIFY_EVALUATION_COUNT( m1.template triangularView<Lower>().solveInPlace(m3), 0);
  68. VERIFY_EVALUATION_COUNT( m1.adjoint().template triangularView<Lower>().solveInPlace(m3.transpose()), 0);
  69. VERIFY_EVALUATION_COUNT( m3.noalias() -= (s1 * m1).adjoint().template selfadjointView<Lower>() * (-m2*s3).adjoint(), 0);
  70. VERIFY_EVALUATION_COUNT( m3.noalias() = s2 * m2.adjoint() * (s1 * m1.adjoint()).template selfadjointView<Upper>(), 0);
  71. VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template selfadjointView<Lower>() * m2.adjoint(), 0);
  72. // 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
  73. VERIFY_EVALUATION_COUNT( m3.col(c0).noalias() = (s1 * m1).adjoint().template selfadjointView<Lower>() * (-m2.row(c0)*s3).adjoint(), 1);
  74. VERIFY_EVALUATION_COUNT( m3.col(c0).noalias() -= (s1 * m1).adjoint().template selfadjointView<Upper>() * (-m2.row(c0)*s3).adjoint(), 1);
  75. 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);
  76. 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);
  77. VERIFY_EVALUATION_COUNT( m3.template selfadjointView<Lower>().rankUpdate(m2.adjoint()), 0);
  78. // Here we will get 1 temporary for each resize operation of the lhs operator; resize(r1,c1) would lead to zero temporaries
  79. m3.resize(1,1);
  80. VERIFY_EVALUATION_COUNT( m3.noalias() = m1.block(r0,r0,r1,r1).template selfadjointView<Lower>() * m2.block(r0,c0,r1,c1), 1);
  81. m3.resize(1,1);
  82. VERIFY_EVALUATION_COUNT( m3.noalias() = m1.block(r0,r0,r1,r1).template triangularView<UnitUpper>() * m2.block(r0,c0,r1,c1), 1);
  83. // Zero temporaries for lazy products ...
  84. VERIFY_EVALUATION_COUNT( Scalar tmp = 0; tmp += Scalar(RealScalar(1)) / (m3.transpose().lazyProduct(m3)).diagonal().sum(), 0 );
  85. // ... and even no temporary for even deeply (>=2) nested products
  86. VERIFY_EVALUATION_COUNT( Scalar tmp = 0; tmp += Scalar(RealScalar(1)) / (m3.transpose() * m3).diagonal().sum(), 0 );
  87. VERIFY_EVALUATION_COUNT( Scalar tmp = 0; tmp += Scalar(RealScalar(1)) / (m3.transpose() * m3).diagonal().array().abs().sum(), 0 );
  88. // Zero temporaries for ... CoeffBasedProductMode
  89. // - does not work with GCC because of the <..>, we'ld need variadic macros ...
  90. //VERIFY_EVALUATION_COUNT( m3.col(0).head<5>() * m3.col(0).transpose() + m3.col(0).head<5>() * m3.col(0).transpose(), 0 );
  91. // Check matrix * vectors
  92. VERIFY_EVALUATION_COUNT( cvres.noalias() = m1 * cv1, 0 );
  93. VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * cv1, 0 );
  94. VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * m2.col(0), 0 );
  95. VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * rv1.adjoint(), 0 );
  96. VERIFY_EVALUATION_COUNT( cvres.noalias() -= m1 * m2.row(0).transpose(), 0 );
  97. }
  98. void test_product_notemporary()
  99. {
  100. int s;
  101. for(int i = 0; i < g_repeat; i++) {
  102. s = internal::random<int>(16,EIGEN_TEST_MAX_SIZE);
  103. CALL_SUBTEST_1( product_notemporary(MatrixXf(s, s)) );
  104. s = internal::random<int>(16,EIGEN_TEST_MAX_SIZE);
  105. CALL_SUBTEST_2( product_notemporary(MatrixXd(s, s)) );
  106. s = internal::random<int>(16,EIGEN_TEST_MAX_SIZE/2);
  107. CALL_SUBTEST_3( product_notemporary(MatrixXcf(s,s)) );
  108. s = internal::random<int>(16,EIGEN_TEST_MAX_SIZE/2);
  109. CALL_SUBTEST_4( product_notemporary(MatrixXcd(s,s)) );
  110. }
  111. }