product_large.cpp
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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 #include "product.h"
11 
12 template<typename T>
14 {
15  int rows = internal::random<int>(1,12);
16  int cols = internal::random<int>(1,12);
19  VectorType x(cols); x.setRandom();
20  VectorType z(x);
21  VectorType y(rows); y.setZero();
22  MatrixType A(rows,cols); A.setRandom();
23  // CwiseBinaryOp
24  VERIFY_IS_APPROX(x = y + A*x, A*z); // OK because "y + A*x" is marked as "assume-aliasing"
25  x = z;
26  // CwiseUnaryOp
27  VERIFY_IS_APPROX(x = T(1.)*(A*x), A*z); // OK because 1*(A*x) is replaced by (1*A*x) which is a Product<> expression
28  x = z;
29  // VERIFY_IS_APPROX(x = y-A*x, -A*z); // Not OK in 3.3 because x is resized before A*x gets evaluated
30  x = z;
31 }
32 
34 {
35  for(int i = 0; i < g_repeat; i++) {
36  CALL_SUBTEST_1( product(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
37  CALL_SUBTEST_2( product(MatrixXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
38  CALL_SUBTEST_3( product(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
39  CALL_SUBTEST_4( product(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) );
40  CALL_SUBTEST_5( product(Matrix<float,Dynamic,Dynamic,RowMajor>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
41 
42  CALL_SUBTEST_1( test_aliasing<float>() );
43  }
44 
45 #if defined EIGEN_TEST_PART_6
46  {
47  // test a specific issue in DiagonalProduct
48  int N = 1000000;
49  VectorXf v = VectorXf::Ones(N);
50  MatrixXf m = MatrixXf::Ones(N,3);
51  m = (v+v).asDiagonal() * m;
52  VERIFY_IS_APPROX(m, MatrixXf::Constant(N,3,2));
53  }
54 
55  {
56  // test deferred resizing in Matrix::operator=
57  MatrixXf a = MatrixXf::Random(10,4), b = MatrixXf::Random(4,10), c = a;
58  VERIFY_IS_APPROX((a = a * b), (c * b).eval());
59  }
60 
61  {
62  // check the functions to setup blocking sizes compile and do not segfault
63  // FIXME check they do what they are supposed to do !!
64  std::ptrdiff_t l1 = internal::random<int>(10000,20000);
65  std::ptrdiff_t l2 = internal::random<int>(100000,200000);
66  std::ptrdiff_t l3 = internal::random<int>(1000000,2000000);
67  setCpuCacheSizes(l1,l2,l3);
68  VERIFY(l1==l1CacheSize());
69  VERIFY(l2==l2CacheSize());
70  std::ptrdiff_t k1 = internal::random<int>(10,100)*16;
71  std::ptrdiff_t m1 = internal::random<int>(10,100)*16;
72  std::ptrdiff_t n1 = internal::random<int>(10,100)*16;
73  // only makes sure it compiles fine
74  internal::computeProductBlockingSizes<float,float,std::ptrdiff_t>(k1,m1,n1,1);
75  }
76 
77  {
78  // test regression in row-vector by matrix (bad Map type)
79  MatrixXf mat1(10,32); mat1.setRandom();
80  MatrixXf mat2(32,32); mat2.setRandom();
81  MatrixXf r1 = mat1.row(2)*mat2.transpose();
82  VERIFY_IS_APPROX(r1, (mat1.row(2)*mat2.transpose()).eval());
83 
84  MatrixXf r2 = mat1.row(2)*mat2;
85  VERIFY_IS_APPROX(r2, (mat1.row(2)*mat2).eval());
86  }
87 
88  {
89  Eigen::MatrixXd A(10,10), B, C;
90  A.setRandom();
91  C = A;
92  for(int k=0; k<79; ++k)
93  C = C * A;
94  B.noalias() = (((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A)) * ((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A)))
95  * (((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A)) * ((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A))*((A*A)*(A*A)));
96  VERIFY_IS_APPROX(B,C);
97  }
98 #endif
99 
100  // Regression test for bug 714:
101 #if defined EIGEN_HAS_OPENMP
102  omp_set_dynamic(1);
103  for(int i = 0; i < g_repeat; i++) {
104  CALL_SUBTEST_6( product(Matrix<float,Dynamic,Dynamic>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
105  }
106 #endif
107 }
Matrix3f m
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Definition: Cwise_arg.cpp:1
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Definition: bench_gemm.cpp:36
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#define VERIFY_IS_APPROX(a, b)
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static const double r2
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The matrix class, also used for vectors and row-vectors.
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std::ptrdiff_t l1CacheSize()
void test_product_large()
void product(const MatrixType &m)
Definition: product.h:20


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autogenerated on Sat May 8 2021 02:43:33