| // 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); | |
| } | |
| } | |
| // Test products at sizes near critical code-path transitions: | |
| // - EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD = 8 (coeff-based vs GEBP) | |
| // - Blocking early-return at max(k,m,n) < 48 | |
| // Uses a sparse set of sizes so total count is 14^3 = 2744 (fast). | |
| template <typename T> | |
| void product_transition_sizes() { | |
| using Matrix = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>; | |
| const int critical[] = {1, 2, 4, 7, 8, 9, 12, 16, 24, 32, 47, 48, 49, 64}; | |
| for (int im = 0; im < 14; ++im) { | |
| for (int in = 0; in < 14; ++in) { | |
| Matrix C = Matrix::Zero(critical[im], critical[in]); | |
| Matrix Cref = Matrix::Zero(critical[im], critical[in]); | |
| for (int ik = 0; ik < 14; ++ik) { | |
| int m = critical[im], n = critical[in], k = critical[ik]; | |
| 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); | |
| } | |
| } | |
| } | |
| } | |
| 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>()); | |
| // Deterministic sweep at transition boundaries (outside g_repeat). | |
| CALL_SUBTEST_54(product_transition_sizes<float>()); | |
| CALL_SUBTEST_55(product_transition_sizes<double>()); | |
| } |