| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com> |
| // |
| // This Source Code Form is subject to the terms of the Mozilla |
| // Public License v. 2.0. If a copy of the MPL was not distributed |
| // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. |
| |
| #include "product.h" |
| #include <Eigen/LU> |
| |
| // regression test for bug 447 |
| template <int> |
| void product1x1() { |
| Matrix<float, 1, 3> matAstatic; |
| Matrix<float, 3, 1> matBstatic; |
| matAstatic.setRandom(); |
| matBstatic.setRandom(); |
| VERIFY_IS_APPROX((matAstatic * matBstatic).coeff(0, 0), matAstatic.cwiseProduct(matBstatic.transpose()).sum()); |
| |
| MatrixXf matAdynamic(1, 3); |
| MatrixXf matBdynamic(3, 1); |
| matAdynamic.setRandom(); |
| matBdynamic.setRandom(); |
| VERIFY_IS_APPROX((matAdynamic * matBdynamic).coeff(0, 0), matAdynamic.cwiseProduct(matBdynamic.transpose()).sum()); |
| } |
| |
| template <typename TC, typename TA, typename TB> |
| const TC &ref_prod(TC &C, const TA &A, const TB &B) { |
| for (Index i = 0; i < C.rows(); ++i) |
| for (Index j = 0; j < C.cols(); ++j) |
| for (Index k = 0; k < A.cols(); ++k) C.coeffRef(i, j) += A.coeff(i, k) * B.coeff(k, j); |
| return C; |
| } |
| |
| template <typename T, int Rows, int Cols, int Depth, int OC, int OA, int OB> |
| std::enable_if_t<!((Rows == 1 && Depth != 1 && OA == ColMajor) || (Depth == 1 && Rows != 1 && OA == RowMajor) || |
| (Cols == 1 && Depth != 1 && OB == RowMajor) || (Depth == 1 && Cols != 1 && OB == ColMajor) || |
| (Rows == 1 && Cols != 1 && OC == ColMajor) || (Cols == 1 && Rows != 1 && OC == RowMajor)), |
| void> |
| test_lazy_single(int rows, int cols, int depth) { |
| Matrix<T, Rows, Depth, OA> A(rows, depth); |
| A.setRandom(); |
| Matrix<T, Depth, Cols, OB> B(depth, cols); |
| B.setRandom(); |
| Matrix<T, Rows, Cols, OC> C(rows, cols); |
| C.setRandom(); |
| Matrix<T, Rows, Cols, OC> D(C); |
| VERIFY_IS_APPROX(C += A.lazyProduct(B), ref_prod(D, A, B)); |
| } |
| |
| void test_dynamic_bool() { |
| int rows = internal::random<int>(1, 64); |
| int cols = internal::random<int>(1, 64); |
| int depth = internal::random<int>(1, 65); |
| |
| typedef Matrix<bool, Dynamic, Dynamic> MatrixX; |
| MatrixX A(rows, depth); |
| A.setRandom(); |
| MatrixX B(depth, cols); |
| B.setRandom(); |
| MatrixX C(rows, cols); |
| C.setRandom(); |
| MatrixX D(C); |
| for (Index i = 0; i < C.rows(); ++i) |
| for (Index j = 0; j < C.cols(); ++j) |
| for (Index k = 0; k < A.cols(); ++k) D.coeffRef(i, j) |= (A.coeff(i, k) && B.coeff(k, j)); |
| C += A * B; |
| VERIFY_IS_EQUAL(C, D); |
| |
| MatrixX E = B.transpose(); |
| for (Index i = 0; i < B.rows(); ++i) |
| for (Index j = 0; j < B.cols(); ++j) VERIFY_IS_EQUAL(B(i, j), E(j, i)); |
| } |
| |
| template <typename T, int Rows, int Cols, int Depth, int OC, int OA, int OB> |
| std::enable_if_t<((Rows == 1 && Depth != 1 && OA == ColMajor) || (Depth == 1 && Rows != 1 && OA == RowMajor) || |
| (Cols == 1 && Depth != 1 && OB == RowMajor) || (Depth == 1 && Cols != 1 && OB == ColMajor) || |
| (Rows == 1 && Cols != 1 && OC == ColMajor) || (Cols == 1 && Rows != 1 && OC == RowMajor)), |
| void> |
| test_lazy_single(int, int, int) {} |
| |
| template <typename T, int Rows, int Cols, int Depth> |
| void test_lazy_all_layout(int rows = Rows, int cols = Cols, int depth = Depth) { |
| CALL_SUBTEST((test_lazy_single<T, Rows, Cols, Depth, ColMajor, ColMajor, ColMajor>(rows, cols, depth))); |
| CALL_SUBTEST((test_lazy_single<T, Rows, Cols, Depth, RowMajor, ColMajor, ColMajor>(rows, cols, depth))); |
| CALL_SUBTEST((test_lazy_single<T, Rows, Cols, Depth, ColMajor, RowMajor, ColMajor>(rows, cols, depth))); |
| CALL_SUBTEST((test_lazy_single<T, Rows, Cols, Depth, RowMajor, RowMajor, ColMajor>(rows, cols, depth))); |
| CALL_SUBTEST((test_lazy_single<T, Rows, Cols, Depth, ColMajor, ColMajor, RowMajor>(rows, cols, depth))); |
| CALL_SUBTEST((test_lazy_single<T, Rows, Cols, Depth, RowMajor, ColMajor, RowMajor>(rows, cols, depth))); |
| CALL_SUBTEST((test_lazy_single<T, Rows, Cols, Depth, ColMajor, RowMajor, RowMajor>(rows, cols, depth))); |
| CALL_SUBTEST((test_lazy_single<T, Rows, Cols, Depth, RowMajor, RowMajor, RowMajor>(rows, cols, depth))); |
| } |
| |
| template <typename T> |
| void test_lazy_l1() { |
| int rows = internal::random<int>(1, 12); |
| int cols = internal::random<int>(1, 12); |
| int depth = internal::random<int>(1, 12); |
| |
| // Inner |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, 1, 1>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, 1, 2>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, 1, 3>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, 1, 8>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, 1, 9>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, 1, -1>(1, 1, depth))); |
| |
| // Outer |
| CALL_SUBTEST((test_lazy_all_layout<T, 2, 1, 1>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, 2, 1>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 2, 2, 1>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 3, 3, 1>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 4, 4, 1>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 4, 8, 1>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 4, -1, 1>(4, cols))); |
| CALL_SUBTEST((test_lazy_all_layout<T, 7, -1, 1>(7, cols))); |
| CALL_SUBTEST((test_lazy_all_layout<T, -1, 8, 1>(rows))); |
| CALL_SUBTEST((test_lazy_all_layout<T, -1, 3, 1>(rows))); |
| CALL_SUBTEST((test_lazy_all_layout<T, -1, -1, 1>(rows, cols))); |
| } |
| |
| template <typename T> |
| void test_lazy_l2() { |
| int rows = internal::random<int>(1, 12); |
| int cols = internal::random<int>(1, 12); |
| int depth = internal::random<int>(1, 12); |
| |
| // mat-vec |
| CALL_SUBTEST((test_lazy_all_layout<T, 2, 1, 2>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 2, 1, 4>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 4, 1, 2>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 4, 1, 4>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 5, 1, 4>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 4, 1, 5>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 4, 1, 6>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 6, 1, 4>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 8, 1, 8>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, -1, 1, 4>(rows))); |
| CALL_SUBTEST((test_lazy_all_layout<T, 4, 1, -1>(4, 1, depth))); |
| CALL_SUBTEST((test_lazy_all_layout<T, -1, 1, -1>(rows, 1, depth))); |
| |
| // vec-mat |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, 2, 2>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, 2, 4>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, 4, 2>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, 4, 4>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, 5, 4>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, 4, 5>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, 4, 6>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, 6, 4>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, 8, 8>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, -1, 4>(1, cols))); |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, 4, -1>(1, 4, depth))); |
| CALL_SUBTEST((test_lazy_all_layout<T, 1, -1, -1>(1, cols, depth))); |
| } |
| |
| template <typename T> |
| void test_lazy_l3() { |
| int rows = internal::random<int>(1, 12); |
| int cols = internal::random<int>(1, 12); |
| int depth = internal::random<int>(1, 12); |
| // mat-mat |
| CALL_SUBTEST((test_lazy_all_layout<T, 2, 4, 2>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 2, 6, 4>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 4, 3, 2>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 4, 8, 4>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 5, 6, 4>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 4, 2, 5>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 4, 7, 6>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 6, 8, 4>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 8, 3, 8>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, -1, 6, 4>(rows))); |
| CALL_SUBTEST((test_lazy_all_layout<T, 4, 3, -1>(4, 3, depth))); |
| CALL_SUBTEST((test_lazy_all_layout<T, -1, 6, -1>(rows, 6, depth))); |
| CALL_SUBTEST((test_lazy_all_layout<T, 8, 2, 2>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 5, 2, 4>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 4, 4, 2>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 8, 4, 4>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 6, 5, 4>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 4, 4, 5>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 3, 4, 6>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 2, 6, 4>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 7, 8, 8>())); |
| CALL_SUBTEST((test_lazy_all_layout<T, 8, -1, 4>(8, cols))); |
| CALL_SUBTEST((test_lazy_all_layout<T, 3, 4, -1>(3, 4, depth))); |
| CALL_SUBTEST((test_lazy_all_layout<T, 4, -1, -1>(4, cols, depth))); |
| } |
| |
| template <typename T, int N, int M, int K> |
| void test_linear_but_not_vectorizable() { |
| // Check tricky cases for which the result of the product is a vector and thus must exhibit the LinearBit flag, |
| // but is not vectorizable along the linear dimension. |
| Index n = N == Dynamic ? internal::random<Index>(1, 32) : N; |
| Index m = M == Dynamic ? internal::random<Index>(1, 32) : M; |
| Index k = K == Dynamic ? internal::random<Index>(1, 32) : K; |
| |
| { |
| Matrix<T, N, M + 1> A; |
| A.setRandom(n, m + 1); |
| Matrix<T, M * 2, K> B; |
| B.setRandom(m * 2, k); |
| Matrix<T, 1, K> C; |
| Matrix<T, 1, K> R; |
| |
| C.noalias() = A.template topLeftCorner<1, M>() * (B.template topRows<M>() + B.template bottomRows<M>()); |
| R.noalias() = A.template topLeftCorner<1, M>() * (B.template topRows<M>() + B.template bottomRows<M>()).eval(); |
| VERIFY_IS_APPROX(C, R); |
| } |
| |
| { |
| Matrix<T, M + 1, N, RowMajor> A; |
| A.setRandom(m + 1, n); |
| Matrix<T, K, M * 2, RowMajor> B; |
| B.setRandom(k, m * 2); |
| Matrix<T, K, 1> C; |
| Matrix<T, K, 1> R; |
| |
| C.noalias() = (B.template leftCols<M>() + B.template rightCols<M>()) * A.template topLeftCorner<M, 1>(); |
| R.noalias() = (B.template leftCols<M>() + B.template rightCols<M>()).eval() * A.template topLeftCorner<M, 1>(); |
| VERIFY_IS_APPROX(C, R); |
| } |
| } |
| |
| template <int Rows> |
| void bug_1311() { |
| Matrix<double, Rows, 2> A; |
| A.setRandom(); |
| Vector2d b = Vector2d::Random(); |
| Matrix<double, Rows, 1> res; |
| res.noalias() = 1. * (A * b); |
| VERIFY_IS_APPROX(res, A * b); |
| res.noalias() = 1. * A * b; |
| VERIFY_IS_APPROX(res, A * b); |
| res.noalias() = (1. * A).lazyProduct(b); |
| VERIFY_IS_APPROX(res, A * b); |
| res.noalias() = (1. * A).lazyProduct(1. * b); |
| VERIFY_IS_APPROX(res, A * b); |
| res.noalias() = (A).lazyProduct(1. * b); |
| VERIFY_IS_APPROX(res, A * b); |
| } |
| |
| template <int> |
| void product_small_regressions() { |
| { |
| // test compilation of (outer_product) * vector |
| Vector3f v = Vector3f::Random(); |
| VERIFY_IS_APPROX((v * v.transpose()) * v, (v * v.transpose()).eval() * v); |
| } |
| |
| { |
| // regression test for pull-request #93 |
| Eigen::Matrix<double, 1, 1> A; |
| A.setRandom(); |
| Eigen::Matrix<double, 18, 1> B; |
| B.setRandom(); |
| Eigen::Matrix<double, 1, 18> C; |
| C.setRandom(); |
| VERIFY_IS_APPROX(B * A.inverse(), B * A.inverse()[0]); |
| VERIFY_IS_APPROX(A.inverse() * C, A.inverse()[0] * C); |
| } |
| |
| { |
| Eigen::Matrix<double, 10, 10> A, B, C; |
| A.setRandom(); |
| C = A; |
| for (int k = 0; k < 79; ++k) C = C * A; |
| 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))) * |
| (((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))); |
| VERIFY_IS_APPROX(B, C); |
| } |
| } |
| |
| template <typename T> |
| void product_sweep(int max_m, int max_k, int max_n) { |
| using Matrix = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>; |
| for (int m = 1; m < max_m; ++m) { |
| for (int n = 1; n < max_n; ++n) { |
| Matrix C = Matrix::Zero(m, n); |
| Matrix Cref = Matrix::Zero(m, n); |
| for (int k = 1; k < max_k; ++k) { |
| Matrix A = Matrix::Random(m, k); |
| Matrix B = Matrix::Random(k, n); |
| C = A * B; |
| Cref.setZero(); |
| ref_prod(Cref, A, B); |
| VERIFY_IS_APPROX(C, Cref); |
| } |
| } |
| } |
| } |
| |
| EIGEN_DECLARE_TEST(product_small) { |
| for (int i = 0; i < g_repeat; i++) { |
| CALL_SUBTEST_1(product(Matrix<float, 3, 2>())); |
| CALL_SUBTEST_2(product(Matrix<int, 3, 17>())); |
| CALL_SUBTEST_8(product(Matrix<double, 3, 17>())); |
| CALL_SUBTEST_3(product(Matrix3d())); |
| CALL_SUBTEST_4(product(Matrix4d())); |
| CALL_SUBTEST_5(product(Matrix4f())); |
| CALL_SUBTEST_10(product(Matrix<bfloat16, 3, 2>())); |
| CALL_SUBTEST_6(product1x1<0>()); |
| |
| CALL_SUBTEST_11(test_lazy_l1<float>()); |
| CALL_SUBTEST_12(test_lazy_l2<float>()); |
| CALL_SUBTEST_13(test_lazy_l3<float>()); |
| |
| CALL_SUBTEST_21(test_lazy_l1<double>()); |
| CALL_SUBTEST_22(test_lazy_l2<double>()); |
| CALL_SUBTEST_23(test_lazy_l3<double>()); |
| |
| CALL_SUBTEST_31(test_lazy_l1<std::complex<float> >()); |
| CALL_SUBTEST_32(test_lazy_l2<std::complex<float> >()); |
| CALL_SUBTEST_33(test_lazy_l3<std::complex<float> >()); |
| |
| CALL_SUBTEST_41(test_lazy_l1<std::complex<double> >()); |
| CALL_SUBTEST_42(test_lazy_l2<std::complex<double> >()); |
| CALL_SUBTEST_43(test_lazy_l3<std::complex<double> >()); |
| |
| CALL_SUBTEST_7((test_linear_but_not_vectorizable<float, 2, 1, Dynamic>())); |
| CALL_SUBTEST_7((test_linear_but_not_vectorizable<float, 3, 1, Dynamic>())); |
| CALL_SUBTEST_7((test_linear_but_not_vectorizable<float, 2, 1, 16>())); |
| |
| CALL_SUBTEST_6(bug_1311<3>()); |
| CALL_SUBTEST_6(bug_1311<5>()); |
| |
| CALL_SUBTEST_9(test_dynamic_bool()); |
| |
| // Commonly specialized vectorized types. |
| CALL_SUBTEST_50(product_sweep<float>(10, 10, 10)); |
| CALL_SUBTEST_51(product_sweep<double>(10, 10, 10)); |
| CALL_SUBTEST_52(product_sweep<Eigen::half>(10, 10, 10)); |
| CALL_SUBTEST_53(product_sweep<Eigen::bfloat16>(10, 10, 10)); |
| } |
| |
| CALL_SUBTEST_6(product_small_regressions<0>()); |
| } |