diff options
Diffstat (limited to 'eigen/Eigen')
76 files changed, 980 insertions, 687 deletions
diff --git a/eigen/Eigen/Cholesky b/eigen/Eigen/Cholesky index 369d1f5..1332b54 100644 --- a/eigen/Eigen/Cholesky +++ b/eigen/Eigen/Cholesky @@ -9,6 +9,7 @@ #define EIGEN_CHOLESKY_MODULE_H #include "Core" +#include "Jacobi" #include "src/Core/util/DisableStupidWarnings.h" @@ -31,7 +32,11 @@ #include "src/Cholesky/LLT.h" #include "src/Cholesky/LDLT.h" #ifdef EIGEN_USE_LAPACKE +#ifdef EIGEN_USE_MKL +#include "mkl_lapacke.h" +#else #include "src/misc/lapacke.h" +#endif #include "src/Cholesky/LLT_LAPACKE.h" #endif diff --git a/eigen/Eigen/Core b/eigen/Eigen/Core index 0f7fa63..4d4901e 100644 --- a/eigen/Eigen/Core +++ b/eigen/Eigen/Core @@ -14,6 +14,22 @@ // first thing Eigen does: stop the compiler from committing suicide #include "src/Core/util/DisableStupidWarnings.h" +#if defined(__CUDACC__) && !defined(EIGEN_NO_CUDA) + #define EIGEN_CUDACC __CUDACC__ +#endif + +#if defined(__CUDA_ARCH__) && !defined(EIGEN_NO_CUDA) + #define EIGEN_CUDA_ARCH __CUDA_ARCH__ +#endif + +#if defined(__CUDACC_VER_MAJOR__) && (__CUDACC_VER_MAJOR__ >= 9) +#define EIGEN_CUDACC_VER ((__CUDACC_VER_MAJOR__ * 10000) + (__CUDACC_VER_MINOR__ * 100)) +#elif defined(__CUDACC_VER__) +#define EIGEN_CUDACC_VER __CUDACC_VER__ +#else +#define EIGEN_CUDACC_VER 0 +#endif + // Handle NVCC/CUDA/SYCL #if defined(__CUDACC__) || defined(__SYCL_DEVICE_ONLY__) // Do not try asserts on CUDA and SYCL! @@ -155,6 +171,9 @@ #ifdef __AVX512DQ__ #define EIGEN_VECTORIZE_AVX512DQ #endif + #ifdef __AVX512ER__ + #define EIGEN_VECTORIZE_AVX512ER + #endif #endif // include files @@ -229,7 +248,7 @@ #if defined __CUDACC__ #define EIGEN_VECTORIZE_CUDA #include <vector_types.h> - #if defined __CUDACC_VER__ && __CUDACC_VER__ >= 70500 + #if EIGEN_CUDACC_VER >= 70500 #define EIGEN_HAS_CUDA_FP16 #endif #endif @@ -352,6 +371,7 @@ using std::ptrdiff_t; #include "src/Core/MathFunctions.h" #include "src/Core/GenericPacketMath.h" #include "src/Core/MathFunctionsImpl.h" +#include "src/Core/arch/Default/ConjHelper.h" #if defined EIGEN_VECTORIZE_AVX512 #include "src/Core/arch/SSE/PacketMath.h" @@ -367,6 +387,7 @@ using std::ptrdiff_t; #include "src/Core/arch/AVX/MathFunctions.h" #include "src/Core/arch/AVX/Complex.h" #include "src/Core/arch/AVX/TypeCasting.h" + #include "src/Core/arch/SSE/TypeCasting.h" #elif defined EIGEN_VECTORIZE_SSE #include "src/Core/arch/SSE/PacketMath.h" #include "src/Core/arch/SSE/MathFunctions.h" diff --git a/eigen/Eigen/Eigenvalues b/eigen/Eigen/Eigenvalues index 009e529..f3f661b 100644 --- a/eigen/Eigen/Eigenvalues +++ b/eigen/Eigen/Eigenvalues @@ -45,7 +45,11 @@ #include "src/Eigenvalues/GeneralizedEigenSolver.h" #include "src/Eigenvalues/MatrixBaseEigenvalues.h" #ifdef EIGEN_USE_LAPACKE +#ifdef EIGEN_USE_MKL +#include "mkl_lapacke.h" +#else #include "src/misc/lapacke.h" +#endif #include "src/Eigenvalues/RealSchur_LAPACKE.h" #include "src/Eigenvalues/ComplexSchur_LAPACKE.h" #include "src/Eigenvalues/SelfAdjointEigenSolver_LAPACKE.h" diff --git a/eigen/Eigen/LU b/eigen/Eigen/LU index 6f6c556..6418a86 100644 --- a/eigen/Eigen/LU +++ b/eigen/Eigen/LU @@ -28,7 +28,11 @@ #include "src/LU/FullPivLU.h" #include "src/LU/PartialPivLU.h" #ifdef EIGEN_USE_LAPACKE +#ifdef EIGEN_USE_MKL +#include "mkl_lapacke.h" +#else #include "src/misc/lapacke.h" +#endif #include "src/LU/PartialPivLU_LAPACKE.h" #endif #include "src/LU/Determinant.h" diff --git a/eigen/Eigen/QR b/eigen/Eigen/QR index 80838e3..c7e9144 100644 --- a/eigen/Eigen/QR +++ b/eigen/Eigen/QR @@ -36,7 +36,11 @@ #include "src/QR/ColPivHouseholderQR.h" #include "src/QR/CompleteOrthogonalDecomposition.h" #ifdef EIGEN_USE_LAPACKE +#ifdef EIGEN_USE_MKL +#include "mkl_lapacke.h" +#else #include "src/misc/lapacke.h" +#endif #include "src/QR/HouseholderQR_LAPACKE.h" #include "src/QR/ColPivHouseholderQR_LAPACKE.h" #endif diff --git a/eigen/Eigen/QtAlignedMalloc b/eigen/Eigen/QtAlignedMalloc index c6571f1..4f07df0 100644 --- a/eigen/Eigen/QtAlignedMalloc +++ b/eigen/Eigen/QtAlignedMalloc @@ -27,7 +27,7 @@ void qFree(void *ptr) void *qRealloc(void *ptr, std::size_t size) { void* newPtr = Eigen::internal::aligned_malloc(size); - memcpy(newPtr, ptr, size); + std::memcpy(newPtr, ptr, size); Eigen::internal::aligned_free(ptr); return newPtr; } diff --git a/eigen/Eigen/SVD b/eigen/Eigen/SVD index 86143c2..5d0e75f 100644 --- a/eigen/Eigen/SVD +++ b/eigen/Eigen/SVD @@ -37,7 +37,11 @@ #include "src/SVD/JacobiSVD.h" #include "src/SVD/BDCSVD.h" #if defined(EIGEN_USE_LAPACKE) && !defined(EIGEN_USE_LAPACKE_STRICT) +#ifdef EIGEN_USE_MKL +#include "mkl_lapacke.h" +#else #include "src/misc/lapacke.h" +#endif #include "src/SVD/JacobiSVD_LAPACKE.h" #endif diff --git a/eigen/Eigen/src/Cholesky/LDLT.h b/eigen/Eigen/src/Cholesky/LDLT.h index fcee7b2..0313a54 100644 --- a/eigen/Eigen/src/Cholesky/LDLT.h +++ b/eigen/Eigen/src/Cholesky/LDLT.h @@ -248,7 +248,7 @@ template<typename _MatrixType, int _UpLo> class LDLT /** \brief Reports whether previous computation was successful. * * \returns \c Success if computation was succesful, - * \c NumericalIssue if the matrix.appears to be negative. + * \c NumericalIssue if the factorization failed because of a zero pivot. */ ComputationInfo info() const { @@ -376,6 +376,8 @@ template<> struct ldlt_inplace<Lower> if((rs>0) && pivot_is_valid) A21 /= realAkk; + else if(rs>0) + ret = ret && (A21.array()==Scalar(0)).all(); if(found_zero_pivot && pivot_is_valid) ret = false; // factorization failed else if(!pivot_is_valid) found_zero_pivot = true; @@ -568,13 +570,14 @@ void LDLT<_MatrixType,_UpLo>::_solve_impl(const RhsType &rhs, DstType &dst) cons // more precisely, use pseudo-inverse of D (see bug 241) using std::abs; const typename Diagonal<const MatrixType>::RealReturnType vecD(vectorD()); - // In some previous versions, tolerance was set to the max of 1/highest and the maximal diagonal entry * epsilon - // as motivated by LAPACK's xGELSS: + // In some previous versions, tolerance was set to the max of 1/highest (or rather numeric_limits::min()) + // and the maximal diagonal entry * epsilon as motivated by LAPACK's xGELSS: // RealScalar tolerance = numext::maxi(vecD.array().abs().maxCoeff() * NumTraits<RealScalar>::epsilon(),RealScalar(1) / NumTraits<RealScalar>::highest()); // However, LDLT is not rank revealing, and so adjusting the tolerance wrt to the highest // diagonal element is not well justified and leads to numerical issues in some cases. // Moreover, Lapack's xSYTRS routines use 0 for the tolerance. - RealScalar tolerance = RealScalar(1) / NumTraits<RealScalar>::highest(); + // Using numeric_limits::min() gives us more robustness to denormals. + RealScalar tolerance = (std::numeric_limits<RealScalar>::min)(); for (Index i = 0; i < vecD.size(); ++i) { diff --git a/eigen/Eigen/src/Cholesky/LLT.h b/eigen/Eigen/src/Cholesky/LLT.h index 87ca8d4..e1624d2 100644 --- a/eigen/Eigen/src/Cholesky/LLT.h +++ b/eigen/Eigen/src/Cholesky/LLT.h @@ -24,7 +24,7 @@ template<typename MatrixType, int UpLo> struct LLT_Traits; * * \tparam _MatrixType the type of the matrix of which we are computing the LL^T Cholesky decomposition * \tparam _UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper. - * The other triangular part won't be read. + * The other triangular part won't be read. * * This class performs a LL^T Cholesky decomposition of a symmetric, positive definite * matrix A such that A = LL^* = U^*U, where L is lower triangular. @@ -41,14 +41,18 @@ template<typename MatrixType, int UpLo> struct LLT_Traits; * Example: \include LLT_example.cpp * Output: \verbinclude LLT_example.out * + * \b Performance: for best performance, it is recommended to use a column-major storage format + * with the Lower triangular part (the default), or, equivalently, a row-major storage format + * with the Upper triangular part. Otherwise, you might get a 20% slowdown for the full factorization + * step, and rank-updates can be up to 3 times slower. + * * This class supports the \link InplaceDecomposition inplace decomposition \endlink mechanism. * + * Note that during the decomposition, only the lower (or upper, as defined by _UpLo) triangular part of A is considered. + * Therefore, the strict lower part does not have to store correct values. + * * \sa MatrixBase::llt(), SelfAdjointView::llt(), class LDLT */ - /* HEY THIS DOX IS DISABLED BECAUSE THERE's A BUG EITHER HERE OR IN LDLT ABOUT THAT (OR BOTH) - * Note that during the decomposition, only the upper triangular part of A is considered. Therefore, - * the strict lower part does not have to store correct values. - */ template<typename _MatrixType, int _UpLo> class LLT { public: @@ -146,7 +150,7 @@ template<typename _MatrixType, int _UpLo> class LLT } template<typename Derived> - void solveInPlace(MatrixBase<Derived> &bAndX) const; + void solveInPlace(const MatrixBase<Derived> &bAndX) const; template<typename InputType> LLT& compute(const EigenBase<InputType>& matrix); @@ -177,7 +181,7 @@ template<typename _MatrixType, int _UpLo> class LLT /** \brief Reports whether previous computation was successful. * * \returns \c Success if computation was succesful, - * \c NumericalIssue if the matrix.appears to be negative. + * \c NumericalIssue if the matrix.appears not to be positive definite. */ ComputationInfo info() const { @@ -425,7 +429,8 @@ LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const EigenBase<InputType> eigen_assert(a.rows()==a.cols()); const Index size = a.rows(); m_matrix.resize(size, size); - m_matrix = a.derived(); + if (!internal::is_same_dense(m_matrix, a.derived())) + m_matrix = a.derived(); // Compute matrix L1 norm = max abs column sum. m_l1_norm = RealScalar(0); @@ -485,11 +490,14 @@ void LLT<_MatrixType,_UpLo>::_solve_impl(const RhsType &rhs, DstType &dst) const * * This version avoids a copy when the right hand side matrix b is not needed anymore. * + * \warning The parameter is only marked 'const' to make the C++ compiler accept a temporary expression here. + * This function will const_cast it, so constness isn't honored here. + * * \sa LLT::solve(), MatrixBase::llt() */ template<typename MatrixType, int _UpLo> template<typename Derived> -void LLT<MatrixType,_UpLo>::solveInPlace(MatrixBase<Derived> &bAndX) const +void LLT<MatrixType,_UpLo>::solveInPlace(const MatrixBase<Derived> &bAndX) const { eigen_assert(m_isInitialized && "LLT is not initialized."); eigen_assert(m_matrix.rows()==bAndX.rows()); diff --git a/eigen/Eigen/src/Core/AssignEvaluator.h b/eigen/Eigen/src/Core/AssignEvaluator.h index b0ec7b7..dbe435d 100644 --- a/eigen/Eigen/src/Core/AssignEvaluator.h +++ b/eigen/Eigen/src/Core/AssignEvaluator.h @@ -39,7 +39,7 @@ public: enum { DstAlignment = DstEvaluator::Alignment, SrcAlignment = SrcEvaluator::Alignment, - DstHasDirectAccess = DstFlags & DirectAccessBit, + DstHasDirectAccess = (DstFlags & DirectAccessBit) == DirectAccessBit, JointAlignment = EIGEN_PLAIN_ENUM_MIN(DstAlignment,SrcAlignment) }; @@ -83,7 +83,7 @@ private: && int(OuterStride)!=Dynamic && int(OuterStride)%int(InnerPacketSize)==0 && (EIGEN_UNALIGNED_VECTORIZE || int(JointAlignment)>=int(InnerRequiredAlignment)), MayLinearize = bool(StorageOrdersAgree) && (int(DstFlags) & int(SrcFlags) & LinearAccessBit), - MayLinearVectorize = bool(MightVectorize) && MayLinearize && DstHasDirectAccess + MayLinearVectorize = bool(MightVectorize) && bool(MayLinearize) && bool(DstHasDirectAccess) && (EIGEN_UNALIGNED_VECTORIZE || (int(DstAlignment)>=int(LinearRequiredAlignment)) || MaxSizeAtCompileTime == Dynamic), /* If the destination isn't aligned, we have to do runtime checks and we don't unroll, so it's only good for large enough sizes. */ diff --git a/eigen/Eigen/src/Core/Assign_MKL.h b/eigen/Eigen/src/Core/Assign_MKL.h index 6c2ab92..6866095 100644 --- a/eigen/Eigen/src/Core/Assign_MKL.h +++ b/eigen/Eigen/src/Core/Assign_MKL.h @@ -84,7 +84,8 @@ class vml_assign_traits struct Assignment<DstXprType, CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested>, assign_op<EIGENTYPE,EIGENTYPE>, \ Dense2Dense, typename enable_if<vml_assign_traits<DstXprType,SrcXprNested>::EnableVml>::type> { \ typedef CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested> SrcXprType; \ - static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE,EIGENTYPE> &/*func*/) { \ + static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE,EIGENTYPE> &func) { \ + resize_if_allowed(dst, src, func); \ eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); \ if(vml_assign_traits<DstXprType,SrcXprNested>::Traversal==LinearTraversal) { \ VMLOP(dst.size(), (const VMLTYPE*)src.nestedExpression().data(), \ @@ -144,7 +145,8 @@ EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(ceil, Ceil, _) Dense2Dense, typename enable_if<vml_assign_traits<DstXprType,SrcXprNested>::EnableVml>::type> { \ typedef CwiseBinaryOp<scalar_##EIGENOP##_op<EIGENTYPE,EIGENTYPE>, SrcXprNested, \ const CwiseNullaryOp<internal::scalar_constant_op<EIGENTYPE>,Plain> > SrcXprType; \ - static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE,EIGENTYPE> &/*func*/) { \ + static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE,EIGENTYPE> &func) { \ + resize_if_allowed(dst, src, func); \ eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); \ VMLTYPE exponent = reinterpret_cast<const VMLTYPE&>(src.rhs().functor().m_other); \ if(vml_assign_traits<DstXprType,SrcXprNested>::Traversal==LinearTraversal) \ diff --git a/eigen/Eigen/src/Core/CoreEvaluators.h b/eigen/Eigen/src/Core/CoreEvaluators.h index f7c1eff..910889e 100644 --- a/eigen/Eigen/src/Core/CoreEvaluators.h +++ b/eigen/Eigen/src/Core/CoreEvaluators.h @@ -977,7 +977,7 @@ struct evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel> > OuterStrideAtCompileTime = HasSameStorageOrderAsArgType ? int(outer_stride_at_compile_time<ArgType>::ret) : int(inner_stride_at_compile_time<ArgType>::ret), - MaskPacketAccessBit = (InnerStrideAtCompileTime == 1) ? PacketAccessBit : 0, + MaskPacketAccessBit = (InnerStrideAtCompileTime == 1 || HasSameStorageOrderAsArgType) ? PacketAccessBit : 0, FlagsLinearAccessBit = (RowsAtCompileTime == 1 || ColsAtCompileTime == 1 || (InnerPanel && (evaluator<ArgType>::Flags&LinearAccessBit))) ? LinearAccessBit : 0, FlagsRowMajorBit = XprType::Flags&RowMajorBit, @@ -987,7 +987,9 @@ struct evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel> > Flags = Flags0 | FlagsLinearAccessBit | FlagsRowMajorBit, PacketAlignment = unpacket_traits<PacketScalar>::alignment, - Alignment0 = (InnerPanel && (OuterStrideAtCompileTime!=Dynamic) && (((OuterStrideAtCompileTime * int(sizeof(Scalar))) % int(PacketAlignment)) == 0)) ? int(PacketAlignment) : 0, + Alignment0 = (InnerPanel && (OuterStrideAtCompileTime!=Dynamic) + && (OuterStrideAtCompileTime!=0) + && (((OuterStrideAtCompileTime * int(sizeof(Scalar))) % int(PacketAlignment)) == 0)) ? int(PacketAlignment) : 0, Alignment = EIGEN_PLAIN_ENUM_MIN(evaluator<ArgType>::Alignment, Alignment0) }; typedef block_evaluator<ArgType, BlockRows, BlockCols, InnerPanel> block_evaluator_type; @@ -1018,14 +1020,16 @@ struct unary_evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel>, IndexBa EIGEN_DEVICE_FUNC explicit unary_evaluator(const XprType& block) : m_argImpl(block.nestedExpression()), m_startRow(block.startRow()), - m_startCol(block.startCol()) + m_startCol(block.startCol()), + m_linear_offset(InnerPanel?(XprType::IsRowMajor ? block.startRow()*block.cols() : block.startCol()*block.rows()):0) { } typedef typename XprType::Scalar Scalar; typedef typename XprType::CoeffReturnType CoeffReturnType; enum { - RowsAtCompileTime = XprType::RowsAtCompileTime + RowsAtCompileTime = XprType::RowsAtCompileTime, + ForwardLinearAccess = InnerPanel && bool(evaluator<ArgType>::Flags&LinearAccessBit) }; EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE @@ -1037,7 +1041,10 @@ struct unary_evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel>, IndexBa EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { - return coeff(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0); + if (ForwardLinearAccess) + return m_argImpl.coeff(m_linear_offset.value() + index); + else + return coeff(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0); } EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE @@ -1049,7 +1056,10 @@ struct unary_evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel>, IndexBa EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) { - return coeffRef(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0); + if (ForwardLinearAccess) + return m_argImpl.coeffRef(m_linear_offset.value() + index); + else + return coeffRef(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0); } template<int LoadMode, typename PacketType> @@ -1063,8 +1073,11 @@ struct unary_evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel>, IndexBa EIGEN_STRONG_INLINE PacketType packet(Index index) const { - return packet<LoadMode,PacketType>(RowsAtCompileTime == 1 ? 0 : index, - RowsAtCompileTime == 1 ? index : 0); + if (ForwardLinearAccess) + return m_argImpl.template packet<LoadMode,PacketType>(m_linear_offset.value() + index); + else + return packet<LoadMode,PacketType>(RowsAtCompileTime == 1 ? 0 : index, + RowsAtCompileTime == 1 ? index : 0); } template<int StoreMode, typename PacketType> @@ -1078,15 +1091,19 @@ struct unary_evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel>, IndexBa EIGEN_STRONG_INLINE void writePacket(Index index, const PacketType& x) { - return writePacket<StoreMode,PacketType>(RowsAtCompileTime == 1 ? 0 : index, - RowsAtCompileTime == 1 ? index : 0, - x); + if (ForwardLinearAccess) + return m_argImpl.template writePacket<StoreMode,PacketType>(m_linear_offset.value() + index, x); + else + return writePacket<StoreMode,PacketType>(RowsAtCompileTime == 1 ? 0 : index, + RowsAtCompileTime == 1 ? index : 0, + x); } protected: evaluator<ArgType> m_argImpl; const variable_if_dynamic<Index, (ArgType::RowsAtCompileTime == 1 && BlockRows==1) ? 0 : Dynamic> m_startRow; const variable_if_dynamic<Index, (ArgType::ColsAtCompileTime == 1 && BlockCols==1) ? 0 : Dynamic> m_startCol; + const variable_if_dynamic<Index, InnerPanel ? Dynamic : 0> m_linear_offset; }; // TODO: This evaluator does not actually use the child evaluator; diff --git a/eigen/Eigen/src/Core/Diagonal.h b/eigen/Eigen/src/Core/Diagonal.h index 49e7112..afcaf35 100644 --- a/eigen/Eigen/src/Core/Diagonal.h +++ b/eigen/Eigen/src/Core/Diagonal.h @@ -70,7 +70,10 @@ template<typename MatrixType, int _DiagIndex> class Diagonal EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal) EIGEN_DEVICE_FUNC - explicit inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex) : m_matrix(matrix), m_index(a_index) {} + explicit inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex) : m_matrix(matrix), m_index(a_index) + { + eigen_assert( a_index <= m_matrix.cols() && -a_index <= m_matrix.rows() ); + } EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal) diff --git a/eigen/Eigen/src/Core/Dot.h b/eigen/Eigen/src/Core/Dot.h index 06ef18b..1fe7a84 100644 --- a/eigen/Eigen/src/Core/Dot.h +++ b/eigen/Eigen/src/Core/Dot.h @@ -31,7 +31,8 @@ struct dot_nocheck typedef scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> conj_prod; typedef typename conj_prod::result_type ResScalar; EIGEN_DEVICE_FUNC - static inline ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b) + EIGEN_STRONG_INLINE + static ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b) { return a.template binaryExpr<conj_prod>(b).sum(); } @@ -43,7 +44,8 @@ struct dot_nocheck<T, U, true> typedef scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> conj_prod; typedef typename conj_prod::result_type ResScalar; EIGEN_DEVICE_FUNC - static inline ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b) + EIGEN_STRONG_INLINE + static ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b) { return a.transpose().template binaryExpr<conj_prod>(b).sum(); } @@ -65,6 +67,7 @@ struct dot_nocheck<T, U, true> template<typename Derived> template<typename OtherDerived> EIGEN_DEVICE_FUNC +EIGEN_STRONG_INLINE typename ScalarBinaryOpTraits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const { @@ -102,7 +105,7 @@ EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scala * \sa lpNorm(), dot(), squaredNorm() */ template<typename Derived> -inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::norm() const +EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::norm() const { return numext::sqrt(squaredNorm()); } @@ -117,7 +120,7 @@ inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real Matr * \sa norm(), normalize() */ template<typename Derived> -inline const typename MatrixBase<Derived>::PlainObject +EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::PlainObject MatrixBase<Derived>::normalized() const { typedef typename internal::nested_eval<Derived,2>::type _Nested; @@ -139,7 +142,7 @@ MatrixBase<Derived>::normalized() const * \sa norm(), normalized() */ template<typename Derived> -inline void MatrixBase<Derived>::normalize() +EIGEN_STRONG_INLINE void MatrixBase<Derived>::normalize() { RealScalar z = squaredNorm(); // NOTE: after extensive benchmarking, this conditional does not impact performance, at least on recent x86 CPU @@ -160,7 +163,7 @@ inline void MatrixBase<Derived>::normalize() * \sa stableNorm(), stableNormalize(), normalized() */ template<typename Derived> -inline const typename MatrixBase<Derived>::PlainObject +EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::PlainObject MatrixBase<Derived>::stableNormalized() const { typedef typename internal::nested_eval<Derived,3>::type _Nested; @@ -185,7 +188,7 @@ MatrixBase<Derived>::stableNormalized() const * \sa stableNorm(), stableNormalized(), normalize() */ template<typename Derived> -inline void MatrixBase<Derived>::stableNormalize() +EIGEN_STRONG_INLINE void MatrixBase<Derived>::stableNormalize() { RealScalar w = cwiseAbs().maxCoeff(); RealScalar z = (derived()/w).squaredNorm(); diff --git a/eigen/Eigen/src/Core/GeneralProduct.h b/eigen/Eigen/src/Core/GeneralProduct.h index 0f16cd8..6f0cc80 100644 --- a/eigen/Eigen/src/Core/GeneralProduct.h +++ b/eigen/Eigen/src/Core/GeneralProduct.h @@ -24,12 +24,17 @@ template<int Rows, int Cols, int Depth> struct product_type_selector; template<int Size, int MaxSize> struct product_size_category { - enum { is_large = MaxSize == Dynamic || - Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD || - (Size==Dynamic && MaxSize>=EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD), - value = is_large ? Large - : Size == 1 ? 1 - : Small + enum { + #ifndef EIGEN_CUDA_ARCH + is_large = MaxSize == Dynamic || + Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD || + (Size==Dynamic && MaxSize>=EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD), + #else + is_large = 0, + #endif + value = is_large ? Large + : Size == 1 ? 1 + : Small }; }; @@ -379,8 +384,6 @@ template<> struct gemv_dense_selector<OnTheRight,RowMajor,false> * * \sa lazyProduct(), operator*=(const MatrixBase&), Cwise::operator*() */ -#ifndef __CUDACC__ - template<typename Derived> template<typename OtherDerived> inline const Product<Derived, OtherDerived> @@ -412,8 +415,6 @@ MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const return Product<Derived, OtherDerived>(derived(), other.derived()); } -#endif // __CUDACC__ - /** \returns an expression of the matrix product of \c *this and \a other without implicit evaluation. * * The returned product will behave like any other expressions: the coefficients of the product will be diff --git a/eigen/Eigen/src/Core/Map.h b/eigen/Eigen/src/Core/Map.h index 06d1967..548bf9a 100644 --- a/eigen/Eigen/src/Core/Map.h +++ b/eigen/Eigen/src/Core/Map.h @@ -20,11 +20,17 @@ struct traits<Map<PlainObjectType, MapOptions, StrideType> > { typedef traits<PlainObjectType> TraitsBase; enum { + PlainObjectTypeInnerSize = ((traits<PlainObjectType>::Flags&RowMajorBit)==RowMajorBit) + ? PlainObjectType::ColsAtCompileTime + : PlainObjectType::RowsAtCompileTime, + InnerStrideAtCompileTime = StrideType::InnerStrideAtCompileTime == 0 ? int(PlainObjectType::InnerStrideAtCompileTime) : int(StrideType::InnerStrideAtCompileTime), OuterStrideAtCompileTime = StrideType::OuterStrideAtCompileTime == 0 - ? int(PlainObjectType::OuterStrideAtCompileTime) + ? (InnerStrideAtCompileTime==Dynamic || PlainObjectTypeInnerSize==Dynamic + ? Dynamic + : int(InnerStrideAtCompileTime) * int(PlainObjectTypeInnerSize)) : int(StrideType::OuterStrideAtCompileTime), Alignment = int(MapOptions)&int(AlignedMask), Flags0 = TraitsBase::Flags & (~NestByRefBit), @@ -107,10 +113,11 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma EIGEN_DEVICE_FUNC inline Index outerStride() const { - return StrideType::OuterStrideAtCompileTime != 0 ? m_stride.outer() - : IsVectorAtCompileTime ? this->size() - : int(Flags)&RowMajorBit ? this->cols() - : this->rows(); + return int(StrideType::OuterStrideAtCompileTime) != 0 ? m_stride.outer() + : int(internal::traits<Map>::OuterStrideAtCompileTime) != Dynamic ? Index(internal::traits<Map>::OuterStrideAtCompileTime) + : IsVectorAtCompileTime ? (this->size() * innerStride()) + : (int(Flags)&RowMajorBit) ? (this->cols() * innerStride()) + : (this->rows() * innerStride()); } /** Constructor in the fixed-size case. diff --git a/eigen/Eigen/src/Core/MathFunctions.h b/eigen/Eigen/src/Core/MathFunctions.h index a648aa0..6eb974d 100644 --- a/eigen/Eigen/src/Core/MathFunctions.h +++ b/eigen/Eigen/src/Core/MathFunctions.h @@ -348,31 +348,7 @@ struct norm1_retval * Implementation of hypot * ****************************************************************************/ -template<typename Scalar> -struct hypot_impl -{ - typedef typename NumTraits<Scalar>::Real RealScalar; - static inline RealScalar run(const Scalar& x, const Scalar& y) - { - EIGEN_USING_STD_MATH(abs); - EIGEN_USING_STD_MATH(sqrt); - RealScalar _x = abs(x); - RealScalar _y = abs(y); - Scalar p, qp; - if(_x>_y) - { - p = _x; - qp = _y / p; - } - else - { - p = _y; - qp = _x / p; - } - if(p==RealScalar(0)) return RealScalar(0); - return p * sqrt(RealScalar(1) + qp*qp); - } -}; +template<typename Scalar> struct hypot_impl; template<typename Scalar> struct hypot_retval @@ -495,7 +471,7 @@ namespace std_fallback { typedef typename NumTraits<Scalar>::Real RealScalar; EIGEN_USING_STD_MATH(log); Scalar x1p = RealScalar(1) + x; - return ( x1p == Scalar(1) ) ? x : x * ( log(x1p) / (x1p - RealScalar(1)) ); + return numext::equal_strict(x1p, Scalar(1)) ? x : x * ( log(x1p) / (x1p - RealScalar(1)) ); } } diff --git a/eigen/Eigen/src/Core/MathFunctionsImpl.h b/eigen/Eigen/src/Core/MathFunctionsImpl.h index 3c9ef22..9c1ceb0 100644 --- a/eigen/Eigen/src/Core/MathFunctionsImpl.h +++ b/eigen/Eigen/src/Core/MathFunctionsImpl.h @@ -71,6 +71,29 @@ T generic_fast_tanh_float(const T& a_x) return pdiv(p, q); } +template<typename RealScalar> +EIGEN_STRONG_INLINE +RealScalar positive_real_hypot(const RealScalar& x, const RealScalar& y) +{ + EIGEN_USING_STD_MATH(sqrt); + RealScalar p, qp; + p = numext::maxi(x,y); + if(p==RealScalar(0)) return RealScalar(0); + qp = numext::mini(y,x) / p; + return p * sqrt(RealScalar(1) + qp*qp); +} + +template<typename Scalar> +struct hypot_impl +{ + typedef typename NumTraits<Scalar>::Real RealScalar; + static inline RealScalar run(const Scalar& x, const Scalar& y) + { + EIGEN_USING_STD_MATH(abs); + return positive_real_hypot<RealScalar>(abs(x), abs(y)); + } +}; + } // end namespace internal } // end namespace Eigen diff --git a/eigen/Eigen/src/Core/MatrixBase.h b/eigen/Eigen/src/Core/MatrixBase.h index ce41218..05db488 100644 --- a/eigen/Eigen/src/Core/MatrixBase.h +++ b/eigen/Eigen/src/Core/MatrixBase.h @@ -160,20 +160,11 @@ template<typename Derived> class MatrixBase EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator-=(const MatrixBase<OtherDerived>& other); -#ifdef __CUDACC__ template<typename OtherDerived> EIGEN_DEVICE_FUNC - const Product<Derived,OtherDerived,LazyProduct> - operator*(const MatrixBase<OtherDerived> &other) const - { return this->lazyProduct(other); } -#else - - template<typename OtherDerived> const Product<Derived,OtherDerived> operator*(const MatrixBase<OtherDerived> &other) const; -#endif - template<typename OtherDerived> EIGEN_DEVICE_FUNC const Product<Derived,OtherDerived,LazyProduct> diff --git a/eigen/Eigen/src/Core/PlainObjectBase.h b/eigen/Eigen/src/Core/PlainObjectBase.h index 77f4f60..1dc7e22 100644 --- a/eigen/Eigen/src/Core/PlainObjectBase.h +++ b/eigen/Eigen/src/Core/PlainObjectBase.h @@ -577,6 +577,10 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type * while the AlignedMap() functions return aligned Map objects and thus should be called only with 16-byte-aligned * \a data pointers. * + * Here is an example using strides: + * \include Matrix_Map_stride.cpp + * Output: \verbinclude Matrix_Map_stride.out + * * \see class Map */ //@{ diff --git a/eigen/Eigen/src/Core/Product.h b/eigen/Eigen/src/Core/Product.h index ae0c94b..676c480 100644 --- a/eigen/Eigen/src/Core/Product.h +++ b/eigen/Eigen/src/Core/Product.h @@ -97,8 +97,8 @@ class Product : public ProductImpl<_Lhs,_Rhs,Option, && "if you wanted a coeff-wise or a dot product use the respective explicit functions"); } - EIGEN_DEVICE_FUNC inline Index rows() const { return m_lhs.rows(); } - EIGEN_DEVICE_FUNC inline Index cols() const { return m_rhs.cols(); } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index rows() const { return m_lhs.rows(); } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index cols() const { return m_rhs.cols(); } EIGEN_DEVICE_FUNC const LhsNestedCleaned& lhs() const { return m_lhs; } EIGEN_DEVICE_FUNC const RhsNestedCleaned& rhs() const { return m_rhs; } @@ -127,7 +127,7 @@ public: using Base::derived; typedef typename Base::Scalar Scalar; - operator const Scalar() const + EIGEN_STRONG_INLINE operator const Scalar() const { return internal::evaluator<ProductXpr>(derived()).coeff(0,0); } @@ -162,7 +162,7 @@ class ProductImpl<Lhs,Rhs,Option,Dense> public: - EIGEN_DEVICE_FUNC Scalar coeff(Index row, Index col) const + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar coeff(Index row, Index col) const { EIGEN_STATIC_ASSERT(EnableCoeff, THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS); eigen_assert( (Option==LazyProduct) || (this->rows() == 1 && this->cols() == 1) ); @@ -170,7 +170,7 @@ class ProductImpl<Lhs,Rhs,Option,Dense> return internal::evaluator<Derived>(derived()).coeff(row,col); } - EIGEN_DEVICE_FUNC Scalar coeff(Index i) const + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar coeff(Index i) const { EIGEN_STATIC_ASSERT(EnableCoeff, THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS); eigen_assert( (Option==LazyProduct) || (this->rows() == 1 && this->cols() == 1) ); diff --git a/eigen/Eigen/src/Core/ProductEvaluators.h b/eigen/Eigen/src/Core/ProductEvaluators.h index c42725d..9b99bd7 100644 --- a/eigen/Eigen/src/Core/ProductEvaluators.h +++ b/eigen/Eigen/src/Core/ProductEvaluators.h @@ -32,7 +32,7 @@ struct evaluator<Product<Lhs, Rhs, Options> > typedef Product<Lhs, Rhs, Options> XprType; typedef product_evaluator<XprType> Base; - EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr) : Base(xpr) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} }; // Catch "scalar * ( A * B )" and transform it to "(A*scalar) * B" @@ -55,7 +55,7 @@ struct evaluator<CwiseBinaryOp<internal::scalar_product_op<Scalar1,Scalar2>, const Product<Lhs, Rhs, DefaultProduct> > XprType; typedef evaluator<Product<EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar1,Lhs,product), Rhs, DefaultProduct> > Base; - EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr) + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr.lhs().functor().m_other * xpr.rhs().lhs() * xpr.rhs().rhs()) {} }; @@ -68,7 +68,7 @@ struct evaluator<Diagonal<const Product<Lhs, Rhs, DefaultProduct>, DiagIndex> > typedef Diagonal<const Product<Lhs, Rhs, DefaultProduct>, DiagIndex> XprType; typedef evaluator<Diagonal<const Product<Lhs, Rhs, LazyProduct>, DiagIndex> > Base; - EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr) + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(Diagonal<const Product<Lhs, Rhs, LazyProduct>, DiagIndex>( Product<Lhs, Rhs, LazyProduct>(xpr.nestedExpression().lhs(), xpr.nestedExpression().rhs()), xpr.index() )) @@ -246,19 +246,19 @@ template<typename Lhs, typename Rhs> struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,InnerProduct> { template<typename Dst> - static inline void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) + static EIGEN_STRONG_INLINE void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) { dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); } template<typename Dst> - static inline void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) + static EIGEN_STRONG_INLINE void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) { dst.coeffRef(0,0) += (lhs.transpose().cwiseProduct(rhs)).sum(); } template<typename Dst> - static void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) + static EIGEN_STRONG_INLINE void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) { dst.coeffRef(0,0) -= (lhs.transpose().cwiseProduct(rhs)).sum(); } }; @@ -312,25 +312,25 @@ struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,OuterProduct> }; template<typename Dst> - static inline void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) + static EIGEN_STRONG_INLINE void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) { internal::outer_product_selector_run(dst, lhs, rhs, set(), is_row_major<Dst>()); } template<typename Dst> - static inline void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) + static EIGEN_STRONG_INLINE void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) { internal::outer_product_selector_run(dst, lhs, rhs, add(), is_row_major<Dst>()); } template<typename Dst> - static inline void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) + static EIGEN_STRONG_INLINE void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) { internal::outer_product_selector_run(dst, lhs, rhs, sub(), is_row_major<Dst>()); } template<typename Dst> - static inline void scaleAndAddTo(Dst& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha) + static EIGEN_STRONG_INLINE void scaleAndAddTo(Dst& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha) { internal::outer_product_selector_run(dst, lhs, rhs, adds(alpha), is_row_major<Dst>()); } @@ -785,7 +785,11 @@ public: _Vectorizable = bool(int(MatrixFlags)&PacketAccessBit) && _SameTypes && (_ScalarAccessOnDiag || (bool(int(DiagFlags)&PacketAccessBit))), _LinearAccessMask = (MatrixType::RowsAtCompileTime==1 || MatrixType::ColsAtCompileTime==1) ? LinearAccessBit : 0, Flags = ((HereditaryBits|_LinearAccessMask) & (unsigned int)(MatrixFlags)) | (_Vectorizable ? PacketAccessBit : 0), - Alignment = evaluator<MatrixType>::Alignment + Alignment = evaluator<MatrixType>::Alignment, + + AsScalarProduct = (DiagonalType::SizeAtCompileTime==1) + || (DiagonalType::SizeAtCompileTime==Dynamic && MatrixType::RowsAtCompileTime==1 && ProductOrder==OnTheLeft) + || (DiagonalType::SizeAtCompileTime==Dynamic && MatrixType::ColsAtCompileTime==1 && ProductOrder==OnTheRight) }; diagonal_product_evaluator_base(const MatrixType &mat, const DiagonalType &diag) @@ -797,7 +801,10 @@ public: EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index idx) const { - return m_diagImpl.coeff(idx) * m_matImpl.coeff(idx); + if(AsScalarProduct) + return m_diagImpl.coeff(0) * m_matImpl.coeff(idx); + else + return m_diagImpl.coeff(idx) * m_matImpl.coeff(idx); } protected: diff --git a/eigen/Eigen/src/Core/Redux.h b/eigen/Eigen/src/Core/Redux.h index b6e8f88..760e9f8 100644 --- a/eigen/Eigen/src/Core/Redux.h +++ b/eigen/Eigen/src/Core/Redux.h @@ -407,7 +407,7 @@ protected: */ template<typename Derived> template<typename Func> -typename internal::traits<Derived>::Scalar +EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar DenseBase<Derived>::redux(const Func& func) const { eigen_assert(this->rows()>0 && this->cols()>0 && "you are using an empty matrix"); diff --git a/eigen/Eigen/src/Core/Ref.h b/eigen/Eigen/src/Core/Ref.h index bdf24f5..9c6e3c5 100644 --- a/eigen/Eigen/src/Core/Ref.h +++ b/eigen/Eigen/src/Core/Ref.h @@ -95,6 +95,8 @@ protected: template<typename Expression> EIGEN_DEVICE_FUNC void construct(Expression& expr) { + EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(PlainObjectType,Expression); + if(PlainObjectType::RowsAtCompileTime==1) { eigen_assert(expr.rows()==1 || expr.cols()==1); diff --git a/eigen/Eigen/src/Core/SelfAdjointView.h b/eigen/Eigen/src/Core/SelfAdjointView.h index 504c98f..b2e51f3 100644 --- a/eigen/Eigen/src/Core/SelfAdjointView.h +++ b/eigen/Eigen/src/Core/SelfAdjointView.h @@ -71,7 +71,9 @@ template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView EIGEN_DEVICE_FUNC explicit inline SelfAdjointView(MatrixType& matrix) : m_matrix(matrix) - {} + { + EIGEN_STATIC_ASSERT(UpLo==Lower || UpLo==Upper,SELFADJOINTVIEW_ACCEPTS_UPPER_AND_LOWER_MODE_ONLY); + } EIGEN_DEVICE_FUNC inline Index rows() const { return m_matrix.rows(); } @@ -189,7 +191,7 @@ template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView TriangularView<typename MatrixType::AdjointReturnType,TriMode> >::type(tmp2); } - typedef SelfAdjointView<const MatrixConjugateReturnType,Mode> ConjugateReturnType; + typedef SelfAdjointView<const MatrixConjugateReturnType,UpLo> ConjugateReturnType; /** \sa MatrixBase::conjugate() const */ EIGEN_DEVICE_FUNC inline const ConjugateReturnType conjugate() const diff --git a/eigen/Eigen/src/Core/SelfCwiseBinaryOp.h b/eigen/Eigen/src/Core/SelfCwiseBinaryOp.h index 50099df..7c89c2e 100644 --- a/eigen/Eigen/src/Core/SelfCwiseBinaryOp.h +++ b/eigen/Eigen/src/Core/SelfCwiseBinaryOp.h @@ -17,7 +17,6 @@ namespace Eigen { template<typename Derived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator*=(const Scalar& other) { - typedef typename Derived::PlainObject PlainObject; internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::mul_assign_op<Scalar,Scalar>()); return derived(); } @@ -25,7 +24,6 @@ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator*=(co template<typename Derived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& ArrayBase<Derived>::operator+=(const Scalar& other) { - typedef typename Derived::PlainObject PlainObject; internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op<Scalar,Scalar>()); return derived(); } @@ -33,7 +31,6 @@ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& ArrayBase<Derived>::operator+=(co template<typename Derived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& ArrayBase<Derived>::operator-=(const Scalar& other) { - typedef typename Derived::PlainObject PlainObject; internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::sub_assign_op<Scalar,Scalar>()); return derived(); } @@ -41,7 +38,6 @@ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& ArrayBase<Derived>::operator-=(co template<typename Derived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator/=(const Scalar& other) { - typedef typename Derived::PlainObject PlainObject; internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::div_assign_op<Scalar,Scalar>()); return derived(); } diff --git a/eigen/Eigen/src/Core/StableNorm.h b/eigen/Eigen/src/Core/StableNorm.h index be04ed4..88c8d98 100644 --- a/eigen/Eigen/src/Core/StableNorm.h +++ b/eigen/Eigen/src/Core/StableNorm.h @@ -165,7 +165,7 @@ MatrixBase<Derived>::stableNorm() const typedef typename internal::nested_eval<Derived,2>::type DerivedCopy; typedef typename internal::remove_all<DerivedCopy>::type DerivedCopyClean; - DerivedCopy copy(derived()); + const DerivedCopy copy(derived()); enum { CanAlign = ( (int(DerivedCopyClean::Flags)&DirectAccessBit) diff --git a/eigen/Eigen/src/Core/Transpositions.h b/eigen/Eigen/src/Core/Transpositions.h index 19c17bb..86da5af 100644 --- a/eigen/Eigen/src/Core/Transpositions.h +++ b/eigen/Eigen/src/Core/Transpositions.h @@ -384,7 +384,7 @@ class Transpose<TranspositionsBase<TranspositionsDerived> > const Product<OtherDerived, Transpose, AliasFreeProduct> operator*(const MatrixBase<OtherDerived>& matrix, const Transpose& trt) { - return Product<OtherDerived, Transpose, AliasFreeProduct>(matrix.derived(), trt.derived()); + return Product<OtherDerived, Transpose, AliasFreeProduct>(matrix.derived(), trt); } /** \returns the \a matrix with the inverse transpositions applied to the rows. diff --git a/eigen/Eigen/src/Core/arch/AVX/Complex.h b/eigen/Eigen/src/Core/arch/AVX/Complex.h index 99439c8..7fa6196 100644 --- a/eigen/Eigen/src/Core/arch/AVX/Complex.h +++ b/eigen/Eigen/src/Core/arch/AVX/Complex.h @@ -204,23 +204,7 @@ template<> struct conj_helper<Packet4cf, Packet4cf, true,true> } }; -template<> struct conj_helper<Packet8f, Packet4cf, false,false> -{ - EIGEN_STRONG_INLINE Packet4cf pmadd(const Packet8f& x, const Packet4cf& y, const Packet4cf& c) const - { return padd(c, pmul(x,y)); } - - EIGEN_STRONG_INLINE Packet4cf pmul(const Packet8f& x, const Packet4cf& y) const - { return Packet4cf(Eigen::internal::pmul(x, y.v)); } -}; - -template<> struct conj_helper<Packet4cf, Packet8f, false,false> -{ - EIGEN_STRONG_INLINE Packet4cf pmadd(const Packet4cf& x, const Packet8f& y, const Packet4cf& c) const - { return padd(c, pmul(x,y)); } - - EIGEN_STRONG_INLINE Packet4cf pmul(const Packet4cf& x, const Packet8f& y) const - { return Packet4cf(Eigen::internal::pmul(x.v, y)); } -}; +EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet4cf,Packet8f) template<> EIGEN_STRONG_INLINE Packet4cf pdiv<Packet4cf>(const Packet4cf& a, const Packet4cf& b) { @@ -400,23 +384,7 @@ template<> struct conj_helper<Packet2cd, Packet2cd, true,true> } }; -template<> struct conj_helper<Packet4d, Packet2cd, false,false> -{ - EIGEN_STRONG_INLINE Packet2cd pmadd(const Packet4d& x, const Packet2cd& y, const Packet2cd& c) const - { return padd(c, pmul(x,y)); } - - EIGEN_STRONG_INLINE Packet2cd pmul(const Packet4d& x, const Packet2cd& y) const - { return Packet2cd(Eigen::internal::pmul(x, y.v)); } -}; - -template<> struct conj_helper<Packet2cd, Packet4d, false,false> -{ - EIGEN_STRONG_INLINE Packet2cd pmadd(const Packet2cd& x, const Packet4d& y, const Packet2cd& c) const - { return padd(c, pmul(x,y)); } - - EIGEN_STRONG_INLINE Packet2cd pmul(const Packet2cd& x, const Packet4d& y) const - { return Packet2cd(Eigen::internal::pmul(x.v, y)); } -}; +EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cd,Packet4d) template<> EIGEN_STRONG_INLINE Packet2cd pdiv<Packet2cd>(const Packet2cd& a, const Packet2cd& b) { diff --git a/eigen/Eigen/src/Core/arch/AVX/PacketMath.h b/eigen/Eigen/src/Core/arch/AVX/PacketMath.h index 195d40f..61c3dfc 100644 --- a/eigen/Eigen/src/Core/arch/AVX/PacketMath.h +++ b/eigen/Eigen/src/Core/arch/AVX/PacketMath.h @@ -308,9 +308,9 @@ template<> EIGEN_STRONG_INLINE void pstore1<Packet8i>(int* to, const int& a) } #ifndef EIGEN_VECTORIZE_AVX512 -template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); } -template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); } -template<> EIGEN_STRONG_INLINE void prefetch<int>(const int* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); } +template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); } +template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); } +template<> EIGEN_STRONG_INLINE void prefetch<int>(const int* addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); } #endif template<> EIGEN_STRONG_INLINE float pfirst<Packet8f>(const Packet8f& a) { @@ -333,9 +333,12 @@ template<> EIGEN_STRONG_INLINE Packet4d preverse(const Packet4d& a) { __m256d tmp = _mm256_shuffle_pd(a,a,5); return _mm256_permute2f128_pd(tmp, tmp, 1); - + #if 0 + // This version is unlikely to be faster as _mm256_shuffle_ps and _mm256_permute_pd + // exhibit the same latency/throughput, but it is here for future reference/benchmarking... __m256d swap_halves = _mm256_permute2f128_pd(a,a,1); return _mm256_permute_pd(swap_halves,5); + #endif } // pabs should be ok diff --git a/eigen/Eigen/src/Core/arch/AVX512/MathFunctions.h b/eigen/Eigen/src/Core/arch/AVX512/MathFunctions.h index 399be0e..9c1717f 100644 --- a/eigen/Eigen/src/Core/arch/AVX512/MathFunctions.h +++ b/eigen/Eigen/src/Core/arch/AVX512/MathFunctions.h @@ -88,9 +88,9 @@ plog<Packet16f>(const Packet16f& _x) { // x = x + x - 1.0; // } else { x = x - 1.0; } __mmask16 mask = _mm512_cmp_ps_mask(x, p16f_cephes_SQRTHF, _CMP_LT_OQ); - Packet16f tmp = _mm512_mask_blend_ps(mask, x, _mm512_setzero_ps()); + Packet16f tmp = _mm512_mask_blend_ps(mask, _mm512_setzero_ps(), x); x = psub(x, p16f_1); - e = psub(e, _mm512_mask_blend_ps(mask, p16f_1, _mm512_setzero_ps())); + e = psub(e, _mm512_mask_blend_ps(mask, _mm512_setzero_ps(), p16f_1)); x = padd(x, tmp); Packet16f x2 = pmul(x, x); @@ -119,8 +119,9 @@ plog<Packet16f>(const Packet16f& _x) { x = padd(x, y2); // Filter out invalid inputs, i.e. negative arg will be NAN, 0 will be -INF. - return _mm512_mask_blend_ps(iszero_mask, p16f_minus_inf, - _mm512_mask_blend_ps(invalid_mask, p16f_nan, x)); + return _mm512_mask_blend_ps(iszero_mask, + _mm512_mask_blend_ps(invalid_mask, x, p16f_nan), + p16f_minus_inf); } #endif @@ -266,8 +267,7 @@ psqrt<Packet16f>(const Packet16f& _x) { // select only the inverse sqrt of positive normal inputs (denormals are // flushed to zero and cause infs as well). __mmask16 non_zero_mask = _mm512_cmp_ps_mask(_x, p16f_flt_min, _CMP_GE_OQ); - Packet16f x = _mm512_mask_blend_ps(non_zero_mask, _mm512_rsqrt14_ps(_x), - _mm512_setzero_ps()); + Packet16f x = _mm512_mask_blend_ps(non_zero_mask, _mm512_setzero_ps(), _mm512_rsqrt14_ps(_x)); // Do a single step of Newton's iteration. x = pmul(x, pmadd(neg_half, pmul(x, x), p16f_one_point_five)); @@ -289,8 +289,7 @@ psqrt<Packet8d>(const Packet8d& _x) { // select only the inverse sqrt of positive normal inputs (denormals are // flushed to zero and cause infs as well). __mmask8 non_zero_mask = _mm512_cmp_pd_mask(_x, p8d_dbl_min, _CMP_GE_OQ); - Packet8d x = _mm512_mask_blend_pd(non_zero_mask, _mm512_rsqrt14_pd(_x), - _mm512_setzero_pd()); + Packet8d x = _mm512_mask_blend_pd(non_zero_mask, _mm512_setzero_pd(), _mm512_rsqrt14_pd(_x)); // Do a first step of Newton's iteration. x = pmul(x, pmadd(neg_half, pmul(x, x), p8d_one_point_five)); @@ -333,20 +332,18 @@ prsqrt<Packet16f>(const Packet16f& _x) { // select only the inverse sqrt of positive normal inputs (denormals are // flushed to zero and cause infs as well). __mmask16 le_zero_mask = _mm512_cmp_ps_mask(_x, p16f_flt_min, _CMP_LT_OQ); - Packet16f x = _mm512_mask_blend_ps(le_zero_mask, _mm512_setzero_ps(), - _mm512_rsqrt14_ps(_x)); + Packet16f x = _mm512_mask_blend_ps(le_zero_mask, _mm512_rsqrt14_ps(_x), _mm512_setzero_ps()); // Fill in NaNs and Infs for the negative/zero entries. __mmask16 neg_mask = _mm512_cmp_ps_mask(_x, _mm512_setzero_ps(), _CMP_LT_OQ); Packet16f infs_and_nans = _mm512_mask_blend_ps( - neg_mask, p16f_nan, - _mm512_mask_blend_ps(le_zero_mask, p16f_inf, _mm512_setzero_ps())); + neg_mask, _mm512_mask_blend_ps(le_zero_mask, _mm512_setzero_ps(), p16f_inf), p16f_nan); // Do a single step of Newton's iteration. x = pmul(x, pmadd(neg_half, pmul(x, x), p16f_one_point_five)); // Insert NaNs and Infs in all the right places. - return _mm512_mask_blend_ps(le_zero_mask, infs_and_nans, x); + return _mm512_mask_blend_ps(le_zero_mask, x, infs_and_nans); } template <> @@ -363,14 +360,12 @@ prsqrt<Packet8d>(const Packet8d& _x) { // select only the inverse sqrt of positive normal inputs (denormals are // flushed to zero and cause infs as well). __mmask8 le_zero_mask = _mm512_cmp_pd_mask(_x, p8d_dbl_min, _CMP_LT_OQ); - Packet8d x = _mm512_mask_blend_pd(le_zero_mask, _mm512_setzero_pd(), - _mm512_rsqrt14_pd(_x)); + Packet8d x = _mm512_mask_blend_pd(le_zero_mask, _mm512_rsqrt14_pd(_x), _mm512_setzero_pd()); // Fill in NaNs and Infs for the negative/zero entries. __mmask8 neg_mask = _mm512_cmp_pd_mask(_x, _mm512_setzero_pd(), _CMP_LT_OQ); Packet8d infs_and_nans = _mm512_mask_blend_pd( - neg_mask, p8d_nan, - _mm512_mask_blend_pd(le_zero_mask, p8d_inf, _mm512_setzero_pd())); + neg_mask, _mm512_mask_blend_pd(le_zero_mask, _mm512_setzero_pd(), p8d_inf), p8d_nan); // Do a first step of Newton's iteration. x = pmul(x, pmadd(neg_half, pmul(x, x), p8d_one_point_five)); @@ -379,9 +374,9 @@ prsqrt<Packet8d>(const Packet8d& _x) { x = pmul(x, pmadd(neg_half, pmul(x, x), p8d_one_point_five)); // Insert NaNs and Infs in all the right places. - return _mm512_mask_blend_pd(le_zero_mask, infs_and_nans, x); + return _mm512_mask_blend_pd(le_zero_mask, x, infs_and_nans); } -#else +#elif defined(EIGEN_VECTORIZE_AVX512ER) template <> EIGEN_STRONG_INLINE Packet16f prsqrt<Packet16f>(const Packet16f& x) { return _mm512_rsqrt28_ps(x); diff --git a/eigen/Eigen/src/Core/arch/AVX512/PacketMath.h b/eigen/Eigen/src/Core/arch/AVX512/PacketMath.h index f6500a1..8970524 100644 --- a/eigen/Eigen/src/Core/arch/AVX512/PacketMath.h +++ b/eigen/Eigen/src/Core/arch/AVX512/PacketMath.h @@ -618,9 +618,9 @@ EIGEN_STRONG_INLINE void pstore1<Packet16i>(int* to, const int& a) { pstore(to, pa); } -template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); } -template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); } -template<> EIGEN_STRONG_INLINE void prefetch<int>(const int* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); } +template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); } +template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); } +template<> EIGEN_STRONG_INLINE void prefetch<int>(const int* addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); } template <> EIGEN_STRONG_INLINE float pfirst<Packet16f>(const Packet16f& a) { diff --git a/eigen/Eigen/src/Core/arch/AltiVec/Complex.h b/eigen/Eigen/src/Core/arch/AltiVec/Complex.h index 67db2f8..3e66573 100644 --- a/eigen/Eigen/src/Core/arch/AltiVec/Complex.h +++ b/eigen/Eigen/src/Core/arch/AltiVec/Complex.h @@ -224,23 +224,7 @@ template<> struct conj_helper<Packet2cf, Packet2cf, true,true> } }; -template<> struct conj_helper<Packet4f, Packet2cf, false,false> -{ - EIGEN_STRONG_INLINE Packet2cf pmadd(const Packet4f& x, const Packet2cf& y, const Packet2cf& c) const - { return padd(c, pmul(x,y)); } - - EIGEN_STRONG_INLINE Packet2cf pmul(const Packet4f& x, const Packet2cf& y) const - { return Packet2cf(internal::pmul<Packet4f>(x, y.v)); } -}; - -template<> struct conj_helper<Packet2cf, Packet4f, false,false> -{ - EIGEN_STRONG_INLINE Packet2cf pmadd(const Packet2cf& x, const Packet4f& y, const Packet2cf& c) const - { return padd(c, pmul(x,y)); } - - EIGEN_STRONG_INLINE Packet2cf pmul(const Packet2cf& x, const Packet4f& y) const - { return Packet2cf(internal::pmul<Packet4f>(x.v, y)); } -}; +EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f) template<> EIGEN_STRONG_INLINE Packet2cf pdiv<Packet2cf>(const Packet2cf& a, const Packet2cf& b) { @@ -416,23 +400,8 @@ template<> struct conj_helper<Packet1cd, Packet1cd, true,true> return pconj(internal::pmul(a, b)); } }; -template<> struct conj_helper<Packet2d, Packet1cd, false,false> -{ - EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet2d& x, const Packet1cd& y, const Packet1cd& c) const - { return padd(c, pmul(x,y)); } - - EIGEN_STRONG_INLINE Packet1cd pmul(const Packet2d& x, const Packet1cd& y) const - { return Packet1cd(internal::pmul<Packet2d>(x, y.v)); } -}; -template<> struct conj_helper<Packet1cd, Packet2d, false,false> -{ - EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet2d& y, const Packet1cd& c) const - { return padd(c, pmul(x,y)); } - - EIGEN_STRONG_INLINE Packet1cd pmul(const Packet1cd& x, const Packet2d& y) const - { return Packet1cd(internal::pmul<Packet2d>(x.v, y)); } -}; +EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d) template<> EIGEN_STRONG_INLINE Packet1cd pdiv<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { diff --git a/eigen/Eigen/src/Core/arch/AltiVec/PacketMath.h b/eigen/Eigen/src/Core/arch/AltiVec/PacketMath.h index b3f1ea1..08a27d1 100644 --- a/eigen/Eigen/src/Core/arch/AltiVec/PacketMath.h +++ b/eigen/Eigen/src/Core/arch/AltiVec/PacketMath.h @@ -103,7 +103,7 @@ static Packet16uc p16uc_PSET32_WODD = vec_sld((Packet16uc) vec_splat((Packet4u static Packet16uc p16uc_PSET32_WEVEN = vec_sld(p16uc_DUPLICATE32_HI, (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 3), 8);//{ 4,5,6,7, 4,5,6,7, 12,13,14,15, 12,13,14,15 }; static Packet16uc p16uc_HALF64_0_16 = vec_sld((Packet16uc)p4i_ZERO, vec_splat((Packet16uc) vec_abs(p4i_MINUS16), 3), 8); //{ 0,0,0,0, 0,0,0,0, 16,16,16,16, 16,16,16,16}; #else -static Packet16uc p16uc_FORWARD = p16uc_REVERSE32; +static Packet16uc p16uc_FORWARD = p16uc_REVERSE32; static Packet16uc p16uc_REVERSE64 = { 8,9,10,11, 12,13,14,15, 0,1,2,3, 4,5,6,7 }; static Packet16uc p16uc_PSET32_WODD = vec_sld((Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 1), (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 3), 8);//{ 0,1,2,3, 0,1,2,3, 8,9,10,11, 8,9,10,11 }; static Packet16uc p16uc_PSET32_WEVEN = vec_sld((Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 0), (Packet16uc) vec_splat((Packet4ui)p16uc_FORWARD, 2), 8);//{ 4,5,6,7, 4,5,6,7, 12,13,14,15, 12,13,14,15 }; @@ -388,10 +388,28 @@ template<> EIGEN_STRONG_INLINE Packet4i pdiv<Packet4i>(const Packet4i& /*a*/, co template<> EIGEN_STRONG_INLINE Packet4f pmadd(const Packet4f& a, const Packet4f& b, const Packet4f& c) { return vec_madd(a,b,c); } template<> EIGEN_STRONG_INLINE Packet4i pmadd(const Packet4i& a, const Packet4i& b, const Packet4i& c) { return a*b + c; } -template<> EIGEN_STRONG_INLINE Packet4f pmin<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_min(a, b); } +template<> EIGEN_STRONG_INLINE Packet4f pmin<Packet4f>(const Packet4f& a, const Packet4f& b) +{ + #ifdef __VSX__ + Packet4f ret; + __asm__ ("xvcmpgesp %x0,%x1,%x2\n\txxsel %x0,%x1,%x2,%x0" : "=&wa" (ret) : "wa" (a), "wa" (b)); + return ret; + #else + return vec_min(a, b); + #endif +} template<> EIGEN_STRONG_INLINE Packet4i pmin<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_min(a, b); } -template<> EIGEN_STRONG_INLINE Packet4f pmax<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_max(a, b); } +template<> EIGEN_STRONG_INLINE Packet4f pmax<Packet4f>(const Packet4f& a, const Packet4f& b) +{ + #ifdef __VSX__ + Packet4f ret; + __asm__ ("xvcmpgtsp %x0,%x2,%x1\n\txxsel %x0,%x1,%x2,%x0" : "=&wa" (ret) : "wa" (a), "wa" (b)); + return ret; + #else + return vec_max(a, b); + #endif +} template<> EIGEN_STRONG_INLINE Packet4i pmax<Packet4i>(const Packet4i& a, const Packet4i& b) { return vec_max(a, b); } template<> EIGEN_STRONG_INLINE Packet4f pand<Packet4f>(const Packet4f& a, const Packet4f& b) { return vec_and(a, b); } @@ -764,7 +782,7 @@ typedef __vector __bool long Packet2bl; static Packet2l p2l_ONE = { 1, 1 }; static Packet2l p2l_ZERO = reinterpret_cast<Packet2l>(p4i_ZERO); -static Packet2d p2d_ONE = { 1.0, 1.0 }; +static Packet2d p2d_ONE = { 1.0, 1.0 }; static Packet2d p2d_ZERO = reinterpret_cast<Packet2d>(p4f_ZERO); static Packet2d p2d_MZERO = { -0.0, -0.0 }; @@ -910,9 +928,19 @@ template<> EIGEN_STRONG_INLINE Packet2d pdiv<Packet2d>(const Packet2d& a, const // for some weird raisons, it has to be overloaded for packet of integers template<> EIGEN_STRONG_INLINE Packet2d pmadd(const Packet2d& a, const Packet2d& b, const Packet2d& c) { return vec_madd(a, b, c); } -template<> EIGEN_STRONG_INLINE Packet2d pmin<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_min(a, b); } +template<> EIGEN_STRONG_INLINE Packet2d pmin<Packet2d>(const Packet2d& a, const Packet2d& b) +{ + Packet2d ret; + __asm__ ("xvcmpgedp %x0,%x1,%x2\n\txxsel %x0,%x1,%x2,%x0" : "=&wa" (ret) : "wa" (a), "wa" (b)); + return ret; + } -template<> EIGEN_STRONG_INLINE Packet2d pmax<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_max(a, b); } +template<> EIGEN_STRONG_INLINE Packet2d pmax<Packet2d>(const Packet2d& a, const Packet2d& b) +{ + Packet2d ret; + __asm__ ("xvcmpgtdp %x0,%x2,%x1\n\txxsel %x0,%x1,%x2,%x0" : "=&wa" (ret) : "wa" (a), "wa" (b)); + return ret; +} template<> EIGEN_STRONG_INLINE Packet2d pand<Packet2d>(const Packet2d& a, const Packet2d& b) { return vec_and(a, b); } @@ -969,7 +997,7 @@ template<> EIGEN_STRONG_INLINE Packet2d preduxp<Packet2d>(const Packet2d* vecs) Packet2d v[2], sum; v[0] = vecs[0] + reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4f>(vecs[0]), reinterpret_cast<Packet4f>(vecs[0]), 8)); v[1] = vecs[1] + reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4f>(vecs[1]), reinterpret_cast<Packet4f>(vecs[1]), 8)); - + #ifdef _BIG_ENDIAN sum = reinterpret_cast<Packet2d>(vec_sld(reinterpret_cast<Packet4f>(v[0]), reinterpret_cast<Packet4f>(v[1]), 8)); #else @@ -1022,7 +1050,7 @@ ptranspose(PacketBlock<Packet2d,2>& kernel) { template<> EIGEN_STRONG_INLINE Packet2d pblend(const Selector<2>& ifPacket, const Packet2d& thenPacket, const Packet2d& elsePacket) { Packet2l select = { ifPacket.select[0], ifPacket.select[1] }; - Packet2bl mask = vec_cmpeq(reinterpret_cast<Packet2d>(select), reinterpret_cast<Packet2d>(p2l_ONE)); + Packet2bl mask = reinterpret_cast<Packet2bl>( vec_cmpeq(reinterpret_cast<Packet2d>(select), reinterpret_cast<Packet2d>(p2l_ONE)) ); return vec_sel(elsePacket, thenPacket, mask); } #endif // __VSX__ diff --git a/eigen/Eigen/src/Core/arch/CUDA/Half.h b/eigen/Eigen/src/Core/arch/CUDA/Half.h index 294c517..02ac0c2 100644 --- a/eigen/Eigen/src/Core/arch/CUDA/Half.h +++ b/eigen/Eigen/src/Core/arch/CUDA/Half.h @@ -147,55 +147,55 @@ namespace half_impl { // versions to get the ALU speed increased), but you do save the // conversion steps back and forth. -__device__ half operator + (const half& a, const half& b) { +EIGEN_STRONG_INLINE __device__ half operator + (const half& a, const half& b) { return __hadd(a, b); } -__device__ half operator * (const half& a, const half& b) { +EIGEN_STRONG_INLINE __device__ half operator * (const half& a, const half& b) { return __hmul(a, b); } -__device__ half operator - (const half& a, const half& b) { +EIGEN_STRONG_INLINE __device__ half operator - (const half& a, const half& b) { return __hsub(a, b); } -__device__ half operator / (const half& a, const half& b) { +EIGEN_STRONG_INLINE __device__ half operator / (const half& a, const half& b) { float num = __half2float(a); float denom = __half2float(b); return __float2half(num / denom); } -__device__ half operator - (const half& a) { +EIGEN_STRONG_INLINE __device__ half operator - (const half& a) { return __hneg(a); } -__device__ half& operator += (half& a, const half& b) { +EIGEN_STRONG_INLINE __device__ half& operator += (half& a, const half& b) { a = a + b; return a; } -__device__ half& operator *= (half& a, const half& b) { +EIGEN_STRONG_INLINE __device__ half& operator *= (half& a, const half& b) { a = a * b; return a; } -__device__ half& operator -= (half& a, const half& b) { +EIGEN_STRONG_INLINE __device__ half& operator -= (half& a, const half& b) { a = a - b; return a; } -__device__ half& operator /= (half& a, const half& b) { +EIGEN_STRONG_INLINE __device__ half& operator /= (half& a, const half& b) { a = a / b; return a; } -__device__ bool operator == (const half& a, const half& b) { +EIGEN_STRONG_INLINE __device__ bool operator == (const half& a, const half& b) { return __heq(a, b); } -__device__ bool operator != (const half& a, const half& b) { +EIGEN_STRONG_INLINE __device__ bool operator != (const half& a, const half& b) { return __hne(a, b); } -__device__ bool operator < (const half& a, const half& b) { +EIGEN_STRONG_INLINE __device__ bool operator < (const half& a, const half& b) { return __hlt(a, b); } -__device__ bool operator <= (const half& a, const half& b) { +EIGEN_STRONG_INLINE __device__ bool operator <= (const half& a, const half& b) { return __hle(a, b); } -__device__ bool operator > (const half& a, const half& b) { +EIGEN_STRONG_INLINE __device__ bool operator > (const half& a, const half& b) { return __hgt(a, b); } -__device__ bool operator >= (const half& a, const half& b) { +EIGEN_STRONG_INLINE __device__ bool operator >= (const half& a, const half& b) { return __hge(a, b); } @@ -238,10 +238,10 @@ EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half& operator /= (half& a, const half& b) return a; } EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool operator == (const half& a, const half& b) { - return float(a) == float(b); + return numext::equal_strict(float(a),float(b)); } EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool operator != (const half& a, const half& b) { - return float(a) != float(b); + return numext::not_equal_strict(float(a), float(b)); } EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC bool operator < (const half& a, const half& b) { return float(a) < float(b); @@ -386,11 +386,15 @@ EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half abs(const half& a) { return result; } EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half exp(const half& a) { - return half(::expf(float(a))); +#if EIGEN_CUDACC_VER >= 80000 && defined EIGEN_CUDA_ARCH && EIGEN_CUDA_ARCH >= 530 + return half(hexp(a)); +#else + return half(::expf(float(a))); +#endif } EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half log(const half& a) { -#if defined(EIGEN_HAS_CUDA_FP16) && defined __CUDACC_VER__ && __CUDACC_VER__ >= 80000 && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530 - return Eigen::half(::hlog(a)); +#if defined(EIGEN_HAS_CUDA_FP16) && EIGEN_CUDACC_VER >= 80000 && defined(EIGEN_CUDA_ARCH) && EIGEN_CUDA_ARCH >= 530 + return half(::hlog(a)); #else return half(::logf(float(a))); #endif @@ -402,7 +406,11 @@ EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half log10(const half& a) { return half(::log10f(float(a))); } EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half sqrt(const half& a) { - return half(::sqrtf(float(a))); +#if EIGEN_CUDACC_VER >= 80000 && defined EIGEN_CUDA_ARCH && EIGEN_CUDA_ARCH >= 530 + return half(hsqrt(a)); +#else + return half(::sqrtf(float(a))); +#endif } EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half pow(const half& a, const half& b) { return half(::powf(float(a), float(b))); @@ -420,10 +428,18 @@ EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half tanh(const half& a) { return half(::tanhf(float(a))); } EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half floor(const half& a) { +#if EIGEN_CUDACC_VER >= 80000 && defined EIGEN_CUDA_ARCH && EIGEN_CUDA_ARCH >= 300 + return half(hfloor(a)); +#else return half(::floorf(float(a))); +#endif } EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half ceil(const half& a) { +#if EIGEN_CUDACC_VER >= 80000 && defined EIGEN_CUDA_ARCH && EIGEN_CUDA_ARCH >= 300 + return half(hceil(a)); +#else return half(::ceilf(float(a))); +#endif } EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC half (min)(const half& a, const half& b) { @@ -493,8 +509,8 @@ struct numeric_limits<Eigen::half> { static const bool is_bounded = false; static const bool is_modulo = false; static const int digits = 11; - static const int digits10 = 2; - //static const int max_digits10 = ; + static const int digits10 = 3; // according to http://half.sourceforge.net/structstd_1_1numeric__limits_3_01half__float_1_1half_01_4.html + static const int max_digits10 = 5; // according to http://half.sourceforge.net/structstd_1_1numeric__limits_3_01half__float_1_1half_01_4.html static const int radix = 2; static const int min_exponent = -13; static const int min_exponent10 = -4; @@ -557,7 +573,7 @@ EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half exph(const Eigen::half& a) { return Eigen::half(::expf(float(a))); } EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Eigen::half logh(const Eigen::half& a) { -#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 80000 && defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530 +#if EIGEN_CUDACC_VER >= 80000 && defined(EIGEN_CUDA_ARCH) && EIGEN_CUDA_ARCH >= 530 return Eigen::half(::hlog(a)); #else return Eigen::half(::logf(float(a))); diff --git a/eigen/Eigen/src/Core/arch/CUDA/PacketMathHalf.h b/eigen/Eigen/src/Core/arch/CUDA/PacketMathHalf.h index ae54225..943e0b0 100644 --- a/eigen/Eigen/src/Core/arch/CUDA/PacketMathHalf.h +++ b/eigen/Eigen/src/Core/arch/CUDA/PacketMathHalf.h @@ -275,7 +275,7 @@ template<> __device__ EIGEN_STRONG_INLINE half2 plog1p<half2>(const half2& a) { return __floats2half2_rn(r1, r2); } -#if defined __CUDACC_VER__ && __CUDACC_VER__ >= 80000 && defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 530 +#if EIGEN_CUDACC_VER >= 80000 && defined EIGEN_CUDA_ARCH && EIGEN_CUDA_ARCH >= 530 template<> __device__ EIGEN_STRONG_INLINE half2 plog<half2>(const half2& a) { diff --git a/eigen/Eigen/src/Core/arch/NEON/Complex.h b/eigen/Eigen/src/Core/arch/NEON/Complex.h index 57e9b43..306a309 100644 --- a/eigen/Eigen/src/Core/arch/NEON/Complex.h +++ b/eigen/Eigen/src/Core/arch/NEON/Complex.h @@ -67,7 +67,7 @@ template<> struct unpacket_traits<Packet2cf> { typedef std::complex<float> type; template<> EIGEN_STRONG_INLINE Packet2cf pset1<Packet2cf>(const std::complex<float>& from) { float32x2_t r64; - r64 = vld1_f32((float *)&from); + r64 = vld1_f32((const float *)&from); return Packet2cf(vcombine_f32(r64, r64)); } @@ -142,7 +142,7 @@ template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet2cf to[stride*1] = std::complex<float>(vgetq_lane_f32(from.v, 2), vgetq_lane_f32(from.v, 3)); } -template<> EIGEN_STRONG_INLINE void prefetch<std::complex<float> >(const std::complex<float> * addr) { EIGEN_ARM_PREFETCH((float *)addr); } +template<> EIGEN_STRONG_INLINE void prefetch<std::complex<float> >(const std::complex<float> * addr) { EIGEN_ARM_PREFETCH((const float *)addr); } template<> EIGEN_STRONG_INLINE std::complex<float> pfirst<Packet2cf>(const Packet2cf& a) { @@ -265,6 +265,8 @@ template<> struct conj_helper<Packet2cf, Packet2cf, true,true> } }; +EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f) + template<> EIGEN_STRONG_INLINE Packet2cf pdiv<Packet2cf>(const Packet2cf& a, const Packet2cf& b) { // TODO optimize it for NEON @@ -275,7 +277,7 @@ template<> EIGEN_STRONG_INLINE Packet2cf pdiv<Packet2cf>(const Packet2cf& a, con s = vmulq_f32(b.v, b.v); rev_s = vrev64q_f32(s); - return Packet2cf(pdiv(res.v, vaddq_f32(s,rev_s))); + return Packet2cf(pdiv<Packet4f>(res.v, vaddq_f32(s,rev_s))); } EIGEN_DEVICE_FUNC inline void @@ -381,7 +383,7 @@ template<> EIGEN_STRONG_INLINE Packet1cd ploaddup<Packet1cd>(const std::complex< template<> EIGEN_STRONG_INLINE void pstore <std::complex<double> >(std::complex<double> * to, const Packet1cd& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((double*)to, from.v); } template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<double> >(std::complex<double> * to, const Packet1cd& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((double*)to, from.v); } -template<> EIGEN_STRONG_INLINE void prefetch<std::complex<double> >(const std::complex<double> * addr) { EIGEN_ARM_PREFETCH((double *)addr); } +template<> EIGEN_STRONG_INLINE void prefetch<std::complex<double> >(const std::complex<double> * addr) { EIGEN_ARM_PREFETCH((const double *)addr); } template<> EIGEN_DEVICE_FUNC inline Packet1cd pgather<std::complex<double>, Packet1cd>(const std::complex<double>* from, Index stride) { @@ -456,6 +458,8 @@ template<> struct conj_helper<Packet1cd, Packet1cd, true,true> } }; +EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d) + template<> EIGEN_STRONG_INLINE Packet1cd pdiv<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { // TODO optimize it for NEON diff --git a/eigen/Eigen/src/Core/arch/NEON/PacketMath.h b/eigen/Eigen/src/Core/arch/NEON/PacketMath.h index 836fbc0..3d5ed0d 100644 --- a/eigen/Eigen/src/Core/arch/NEON/PacketMath.h +++ b/eigen/Eigen/src/Core/arch/NEON/PacketMath.h @@ -36,12 +36,43 @@ namespace internal { #endif #endif +#if EIGEN_COMP_MSVC + +// In MSVC's arm_neon.h header file, all NEON vector types +// are aliases to the same underlying type __n128. +// We thus have to wrap them to make them different C++ types. +// (See also bug 1428) + +template<typename T,int unique_id> +struct eigen_packet_wrapper +{ + operator T&() { return m_val; } + operator const T&() const { return m_val; } + eigen_packet_wrapper() {} + eigen_packet_wrapper(const T &v) : m_val(v) {} + eigen_packet_wrapper& operator=(const T &v) { + m_val = v; + return *this; + } + + T m_val; +}; +typedef eigen_packet_wrapper<float32x2_t,0> Packet2f; +typedef eigen_packet_wrapper<float32x4_t,1> Packet4f; +typedef eigen_packet_wrapper<int32x4_t ,2> Packet4i; +typedef eigen_packet_wrapper<int32x2_t ,3> Packet2i; +typedef eigen_packet_wrapper<uint32x4_t ,4> Packet4ui; + +#else + typedef float32x2_t Packet2f; typedef float32x4_t Packet4f; typedef int32x4_t Packet4i; typedef int32x2_t Packet2i; typedef uint32x4_t Packet4ui; +#endif // EIGEN_COMP_MSVC + #define _EIGEN_DECLARE_CONST_Packet4f(NAME,X) \ const Packet4f p4f_##NAME = pset1<Packet4f>(X) diff --git a/eigen/Eigen/src/Core/arch/SSE/Complex.h b/eigen/Eigen/src/Core/arch/SSE/Complex.h index 5607fe0..d075043 100644 --- a/eigen/Eigen/src/Core/arch/SSE/Complex.h +++ b/eigen/Eigen/src/Core/arch/SSE/Complex.h @@ -128,7 +128,7 @@ template<> EIGEN_DEVICE_FUNC inline void pscatter<std::complex<float>, Packet2cf _mm_cvtss_f32(_mm_shuffle_ps(from.v, from.v, 3))); } -template<> EIGEN_STRONG_INLINE void prefetch<std::complex<float> >(const std::complex<float> * addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); } +template<> EIGEN_STRONG_INLINE void prefetch<std::complex<float> >(const std::complex<float> * addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); } template<> EIGEN_STRONG_INLINE std::complex<float> pfirst<Packet2cf>(const Packet2cf& a) { @@ -229,23 +229,7 @@ template<> struct conj_helper<Packet2cf, Packet2cf, true,true> } }; -template<> struct conj_helper<Packet4f, Packet2cf, false,false> -{ - EIGEN_STRONG_INLINE Packet2cf pmadd(const Packet4f& x, const Packet2cf& y, const Packet2cf& c) const - { return padd(c, pmul(x,y)); } - - EIGEN_STRONG_INLINE Packet2cf pmul(const Packet4f& x, const Packet2cf& y) const - { return Packet2cf(Eigen::internal::pmul<Packet4f>(x, y.v)); } -}; - -template<> struct conj_helper<Packet2cf, Packet4f, false,false> -{ - EIGEN_STRONG_INLINE Packet2cf pmadd(const Packet2cf& x, const Packet4f& y, const Packet2cf& c) const - { return padd(c, pmul(x,y)); } - - EIGEN_STRONG_INLINE Packet2cf pmul(const Packet2cf& x, const Packet4f& y) const - { return Packet2cf(Eigen::internal::pmul<Packet4f>(x.v, y)); } -}; +EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f) template<> EIGEN_STRONG_INLINE Packet2cf pdiv<Packet2cf>(const Packet2cf& a, const Packet2cf& b) { @@ -340,7 +324,7 @@ template<> EIGEN_STRONG_INLINE Packet1cd ploaddup<Packet1cd>(const std::complex< template<> EIGEN_STRONG_INLINE void pstore <std::complex<double> >(std::complex<double> * to, const Packet1cd& from) { EIGEN_DEBUG_ALIGNED_STORE pstore((double*)to, Packet2d(from.v)); } template<> EIGEN_STRONG_INLINE void pstoreu<std::complex<double> >(std::complex<double> * to, const Packet1cd& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((double*)to, Packet2d(from.v)); } -template<> EIGEN_STRONG_INLINE void prefetch<std::complex<double> >(const std::complex<double> * addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); } +template<> EIGEN_STRONG_INLINE void prefetch<std::complex<double> >(const std::complex<double> * addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); } template<> EIGEN_STRONG_INLINE std::complex<double> pfirst<Packet1cd>(const Packet1cd& a) { @@ -430,23 +414,7 @@ template<> struct conj_helper<Packet1cd, Packet1cd, true,true> } }; -template<> struct conj_helper<Packet2d, Packet1cd, false,false> -{ - EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet2d& x, const Packet1cd& y, const Packet1cd& c) const - { return padd(c, pmul(x,y)); } - - EIGEN_STRONG_INLINE Packet1cd pmul(const Packet2d& x, const Packet1cd& y) const - { return Packet1cd(Eigen::internal::pmul<Packet2d>(x, y.v)); } -}; - -template<> struct conj_helper<Packet1cd, Packet2d, false,false> -{ - EIGEN_STRONG_INLINE Packet1cd pmadd(const Packet1cd& x, const Packet2d& y, const Packet1cd& c) const - { return padd(c, pmul(x,y)); } - - EIGEN_STRONG_INLINE Packet1cd pmul(const Packet1cd& x, const Packet2d& y) const - { return Packet1cd(Eigen::internal::pmul<Packet2d>(x.v, y)); } -}; +EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d) template<> EIGEN_STRONG_INLINE Packet1cd pdiv<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { diff --git a/eigen/Eigen/src/Core/arch/SSE/PacketMath.h b/eigen/Eigen/src/Core/arch/SSE/PacketMath.h index 3832de1..5e652cc 100644 --- a/eigen/Eigen/src/Core/arch/SSE/PacketMath.h +++ b/eigen/Eigen/src/Core/arch/SSE/PacketMath.h @@ -409,10 +409,16 @@ template<> EIGEN_STRONG_INLINE void pstore1<Packet2d>(double* to, const double& pstore(to, Packet2d(vec2d_swizzle1(pa,0,0))); } +#if EIGEN_COMP_PGI +typedef const void * SsePrefetchPtrType; +#else +typedef const char * SsePrefetchPtrType; +#endif + #ifndef EIGEN_VECTORIZE_AVX -template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); } -template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); } -template<> EIGEN_STRONG_INLINE void prefetch<int>(const int* addr) { _mm_prefetch((const char*)(addr), _MM_HINT_T0); } +template<> EIGEN_STRONG_INLINE void prefetch<float>(const float* addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); } +template<> EIGEN_STRONG_INLINE void prefetch<double>(const double* addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); } +template<> EIGEN_STRONG_INLINE void prefetch<int>(const int* addr) { _mm_prefetch((SsePrefetchPtrType)(addr), _MM_HINT_T0); } #endif #if EIGEN_COMP_MSVC_STRICT && EIGEN_OS_WIN64 @@ -876,4 +882,14 @@ template<> EIGEN_STRONG_INLINE double pmadd(const double& a, const double& b, co } // end namespace Eigen +#if EIGEN_COMP_PGI +// PGI++ does not define the following intrinsics in C++ mode. +static inline __m128 _mm_castpd_ps (__m128d x) { return reinterpret_cast<__m128&>(x); } +static inline __m128i _mm_castpd_si128(__m128d x) { return reinterpret_cast<__m128i&>(x); } +static inline __m128d _mm_castps_pd (__m128 x) { return reinterpret_cast<__m128d&>(x); } +static inline __m128i _mm_castps_si128(__m128 x) { return reinterpret_cast<__m128i&>(x); } +static inline __m128 _mm_castsi128_ps(__m128i x) { return reinterpret_cast<__m128&>(x); } +static inline __m128d _mm_castsi128_pd(__m128i x) { return reinterpret_cast<__m128d&>(x); } +#endif + #endif // EIGEN_PACKET_MATH_SSE_H diff --git a/eigen/Eigen/src/Core/arch/SSE/TypeCasting.h b/eigen/Eigen/src/Core/arch/SSE/TypeCasting.h index c848932..c6ca8c7 100644 --- a/eigen/Eigen/src/Core/arch/SSE/TypeCasting.h +++ b/eigen/Eigen/src/Core/arch/SSE/TypeCasting.h @@ -14,6 +14,7 @@ namespace Eigen { namespace internal { +#ifndef EIGEN_VECTORIZE_AVX template <> struct type_casting_traits<float, int> { enum { @@ -23,11 +24,6 @@ struct type_casting_traits<float, int> { }; }; -template<> EIGEN_STRONG_INLINE Packet4i pcast<Packet4f, Packet4i>(const Packet4f& a) { - return _mm_cvttps_epi32(a); -} - - template <> struct type_casting_traits<int, float> { enum { @@ -37,11 +33,6 @@ struct type_casting_traits<int, float> { }; }; -template<> EIGEN_STRONG_INLINE Packet4f pcast<Packet4i, Packet4f>(const Packet4i& a) { - return _mm_cvtepi32_ps(a); -} - - template <> struct type_casting_traits<double, float> { enum { @@ -51,10 +42,6 @@ struct type_casting_traits<double, float> { }; }; -template<> EIGEN_STRONG_INLINE Packet4f pcast<Packet2d, Packet4f>(const Packet2d& a, const Packet2d& b) { - return _mm_shuffle_ps(_mm_cvtpd_ps(a), _mm_cvtpd_ps(b), (1 << 2) | (1 << 6)); -} - template <> struct type_casting_traits<float, double> { enum { @@ -63,6 +50,19 @@ struct type_casting_traits<float, double> { TgtCoeffRatio = 2 }; }; +#endif + +template<> EIGEN_STRONG_INLINE Packet4i pcast<Packet4f, Packet4i>(const Packet4f& a) { + return _mm_cvttps_epi32(a); +} + +template<> EIGEN_STRONG_INLINE Packet4f pcast<Packet4i, Packet4f>(const Packet4i& a) { + return _mm_cvtepi32_ps(a); +} + +template<> EIGEN_STRONG_INLINE Packet4f pcast<Packet2d, Packet4f>(const Packet2d& a, const Packet2d& b) { + return _mm_shuffle_ps(_mm_cvtpd_ps(a), _mm_cvtpd_ps(b), (1 << 2) | (1 << 6)); +} template<> EIGEN_STRONG_INLINE Packet2d pcast<Packet4f, Packet2d>(const Packet4f& a) { // Simply discard the second half of the input diff --git a/eigen/Eigen/src/Core/arch/ZVector/Complex.h b/eigen/Eigen/src/Core/arch/ZVector/Complex.h index d39d2d1..1bfb733 100644 --- a/eigen/Eigen/src/Core/arch/ZVector/Complex.h +++ b/eigen/Eigen/src/Core/arch/ZVector/Complex.h @@ -336,6 +336,9 @@ template<> struct conj_helper<Packet2cf, Packet2cf, true,true> } }; +EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cf,Packet4f) +EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet1cd,Packet2d) + template<> EIGEN_STRONG_INLINE Packet1cd pdiv<Packet1cd>(const Packet1cd& a, const Packet1cd& b) { // TODO optimize it for AltiVec diff --git a/eigen/Eigen/src/Core/functors/BinaryFunctors.h b/eigen/Eigen/src/Core/functors/BinaryFunctors.h index 96747ba..3eae6b8 100644 --- a/eigen/Eigen/src/Core/functors/BinaryFunctors.h +++ b/eigen/Eigen/src/Core/functors/BinaryFunctors.h @@ -255,7 +255,7 @@ struct scalar_cmp_op<LhsScalar,RhsScalar, cmp_NEQ> : binary_op_base<LhsScalar,Rh /** \internal - * \brief Template functor to compute the hypot of two scalars + * \brief Template functor to compute the hypot of two \b positive \b and \b real scalars * * \sa MatrixBase::stableNorm(), class Redux */ @@ -263,22 +263,15 @@ template<typename Scalar> struct scalar_hypot_op<Scalar,Scalar> : binary_op_base<Scalar,Scalar> { EIGEN_EMPTY_STRUCT_CTOR(scalar_hypot_op) -// typedef typename NumTraits<Scalar>::Real result_type; - EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& _x, const Scalar& _y) const + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar &x, const Scalar &y) const { - EIGEN_USING_STD_MATH(sqrt) - Scalar p, qp; - if(_x>_y) - { - p = _x; - qp = _y / p; - } - else - { - p = _y; - qp = _x / p; - } - return p * sqrt(Scalar(1) + qp*qp); + // This functor is used by hypotNorm only for which it is faster to first apply abs + // on all coefficients prior to reduction through hypot. + // This way we avoid calling abs on positive and real entries, and this also permits + // to seamlessly handle complexes. Otherwise we would have to handle both real and complexes + // through the same functor... + return internal::positive_real_hypot(x,y); } }; template<typename Scalar> diff --git a/eigen/Eigen/src/Core/functors/StlFunctors.h b/eigen/Eigen/src/Core/functors/StlFunctors.h index 6df3fa5..9c1d758 100644 --- a/eigen/Eigen/src/Core/functors/StlFunctors.h +++ b/eigen/Eigen/src/Core/functors/StlFunctors.h @@ -83,13 +83,17 @@ struct functor_traits<std::binder1st<T> > { enum { Cost = functor_traits<T>::Cost, PacketAccess = false }; }; #endif +#if (__cplusplus < 201703L) && (EIGEN_COMP_MSVC < 1910) +// std::unary_negate is deprecated since c++17 and will be removed in c++20 template<typename T> struct functor_traits<std::unary_negate<T> > { enum { Cost = 1 + functor_traits<T>::Cost, PacketAccess = false }; }; +// std::binary_negate is deprecated since c++17 and will be removed in c++20 template<typename T> struct functor_traits<std::binary_negate<T> > { enum { Cost = 1 + functor_traits<T>::Cost, PacketAccess = false }; }; +#endif #ifdef EIGEN_STDEXT_SUPPORT diff --git a/eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_BLAS.h b/eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_BLAS.h index 41e18ff..9176a13 100644 --- a/eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_BLAS.h +++ b/eigen/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_BLAS.h @@ -88,7 +88,7 @@ struct general_matrix_matrix_rankupdate<Index,EIGTYPE,AStorageOrder,ConjugateA,C BlasIndex lda=convert_index<BlasIndex>(lhsStride), ldc=convert_index<BlasIndex>(resStride), n=convert_index<BlasIndex>(size), k=convert_index<BlasIndex>(depth); \ char uplo=((IsLower) ? 'L' : 'U'), trans=((AStorageOrder==RowMajor) ? 'T':'N'); \ EIGTYPE beta(1); \ - BLASFUNC(&uplo, &trans, &n, &k, &numext::real_ref(alpha), lhs, &lda, &numext::real_ref(beta), res, &ldc); \ + BLASFUNC(&uplo, &trans, &n, &k, (const BLASTYPE*)&numext::real_ref(alpha), lhs, &lda, (const BLASTYPE*)&numext::real_ref(beta), res, &ldc); \ } \ }; @@ -125,9 +125,13 @@ struct general_matrix_matrix_rankupdate<Index,EIGTYPE,AStorageOrder,ConjugateA,C } \ }; - +#ifdef EIGEN_USE_MKL +EIGEN_BLAS_RANKUPDATE_R(double, double, dsyrk) +EIGEN_BLAS_RANKUPDATE_R(float, float, ssyrk) +#else EIGEN_BLAS_RANKUPDATE_R(double, double, dsyrk_) EIGEN_BLAS_RANKUPDATE_R(float, float, ssyrk_) +#endif // TODO hanlde complex cases // EIGEN_BLAS_RANKUPDATE_C(dcomplex, double, double, zherk_) diff --git a/eigen/Eigen/src/Core/products/GeneralMatrixMatrix_BLAS.h b/eigen/Eigen/src/Core/products/GeneralMatrixMatrix_BLAS.h index 7a3bdbf..b0f6b0d 100644 --- a/eigen/Eigen/src/Core/products/GeneralMatrixMatrix_BLAS.h +++ b/eigen/Eigen/src/Core/products/GeneralMatrixMatrix_BLAS.h @@ -46,7 +46,7 @@ namespace internal { // gemm specialization -#define GEMM_SPECIALIZATION(EIGTYPE, EIGPREFIX, BLASTYPE, BLASPREFIX) \ +#define GEMM_SPECIALIZATION(EIGTYPE, EIGPREFIX, BLASTYPE, BLASFUNC) \ template< \ typename Index, \ int LhsStorageOrder, bool ConjugateLhs, \ @@ -100,13 +100,20 @@ static void run(Index rows, Index cols, Index depth, \ ldb = convert_index<BlasIndex>(b_tmp.outerStride()); \ } else b = _rhs; \ \ - BLASPREFIX##gemm_(&transa, &transb, &m, &n, &k, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, &numext::real_ref(beta), (BLASTYPE*)res, &ldc); \ + BLASFUNC(&transa, &transb, &m, &n, &k, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, (const BLASTYPE*)&numext::real_ref(beta), (BLASTYPE*)res, &ldc); \ }}; -GEMM_SPECIALIZATION(double, d, double, d) -GEMM_SPECIALIZATION(float, f, float, s) -GEMM_SPECIALIZATION(dcomplex, cd, double, z) -GEMM_SPECIALIZATION(scomplex, cf, float, c) +#ifdef EIGEN_USE_MKL +GEMM_SPECIALIZATION(double, d, double, dgemm) +GEMM_SPECIALIZATION(float, f, float, sgemm) +GEMM_SPECIALIZATION(dcomplex, cd, MKL_Complex16, zgemm) +GEMM_SPECIALIZATION(scomplex, cf, MKL_Complex8, cgemm) +#else +GEMM_SPECIALIZATION(double, d, double, dgemm_) +GEMM_SPECIALIZATION(float, f, float, sgemm_) +GEMM_SPECIALIZATION(dcomplex, cd, double, zgemm_) +GEMM_SPECIALIZATION(scomplex, cf, float, cgemm_) +#endif } // end namespase internal diff --git a/eigen/Eigen/src/Core/products/GeneralMatrixVector.h b/eigen/Eigen/src/Core/products/GeneralMatrixVector.h index 3c1a7fc..a597c1f 100644 --- a/eigen/Eigen/src/Core/products/GeneralMatrixVector.h +++ b/eigen/Eigen/src/Core/products/GeneralMatrixVector.h @@ -183,8 +183,8 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,LhsMapper,C alignmentPattern = AllAligned; } - const Index offset1 = (FirstAligned && alignmentStep==1)?3:1; - const Index offset3 = (FirstAligned && alignmentStep==1)?1:3; + const Index offset1 = (alignmentPattern==FirstAligned && alignmentStep==1)?3:1; + const Index offset3 = (alignmentPattern==FirstAligned && alignmentStep==1)?1:3; Index columnBound = ((cols-skipColumns)/columnsAtOnce)*columnsAtOnce + skipColumns; for (Index i=skipColumns; i<columnBound; i+=columnsAtOnce) @@ -457,8 +457,8 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,LhsMapper,R alignmentPattern = AllAligned; } - const Index offset1 = (FirstAligned && alignmentStep==1)?3:1; - const Index offset3 = (FirstAligned && alignmentStep==1)?1:3; + const Index offset1 = (alignmentPattern==FirstAligned && alignmentStep==1)?3:1; + const Index offset3 = (alignmentPattern==FirstAligned && alignmentStep==1)?1:3; Index rowBound = ((rows-skipRows)/rowsAtOnce)*rowsAtOnce + skipRows; for (Index i=skipRows; i<rowBound; i+=rowsAtOnce) diff --git a/eigen/Eigen/src/Core/products/GeneralMatrixVector_BLAS.h b/eigen/Eigen/src/Core/products/GeneralMatrixVector_BLAS.h index e3a5d58..6e36c2b 100644 --- a/eigen/Eigen/src/Core/products/GeneralMatrixVector_BLAS.h +++ b/eigen/Eigen/src/Core/products/GeneralMatrixVector_BLAS.h @@ -85,7 +85,7 @@ EIGEN_BLAS_GEMV_SPECIALIZE(float) EIGEN_BLAS_GEMV_SPECIALIZE(dcomplex) EIGEN_BLAS_GEMV_SPECIALIZE(scomplex) -#define EIGEN_BLAS_GEMV_SPECIALIZATION(EIGTYPE,BLASTYPE,BLASPREFIX) \ +#define EIGEN_BLAS_GEMV_SPECIALIZATION(EIGTYPE,BLASTYPE,BLASFUNC) \ template<typename Index, int LhsStorageOrder, bool ConjugateLhs, bool ConjugateRhs> \ struct general_matrix_vector_product_gemv<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,ConjugateRhs> \ { \ @@ -113,14 +113,21 @@ static void run( \ x_ptr=x_tmp.data(); \ incx=1; \ } else x_ptr=rhs; \ - BLASPREFIX##gemv_(&trans, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)lhs, &lda, (const BLASTYPE*)x_ptr, &incx, &numext::real_ref(beta), (BLASTYPE*)res, &incy); \ + BLASFUNC(&trans, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)lhs, &lda, (const BLASTYPE*)x_ptr, &incx, (const BLASTYPE*)&numext::real_ref(beta), (BLASTYPE*)res, &incy); \ }\ }; -EIGEN_BLAS_GEMV_SPECIALIZATION(double, double, d) -EIGEN_BLAS_GEMV_SPECIALIZATION(float, float, s) -EIGEN_BLAS_GEMV_SPECIALIZATION(dcomplex, double, z) -EIGEN_BLAS_GEMV_SPECIALIZATION(scomplex, float, c) +#ifdef EIGEN_USE_MKL +EIGEN_BLAS_GEMV_SPECIALIZATION(double, double, dgemv) +EIGEN_BLAS_GEMV_SPECIALIZATION(float, float, sgemv) +EIGEN_BLAS_GEMV_SPECIALIZATION(dcomplex, MKL_Complex16, zgemv) +EIGEN_BLAS_GEMV_SPECIALIZATION(scomplex, MKL_Complex8 , cgemv) +#else +EIGEN_BLAS_GEMV_SPECIALIZATION(double, double, dgemv_) +EIGEN_BLAS_GEMV_SPECIALIZATION(float, float, sgemv_) +EIGEN_BLAS_GEMV_SPECIALIZATION(dcomplex, double, zgemv_) +EIGEN_BLAS_GEMV_SPECIALIZATION(scomplex, float, cgemv_) +#endif } // end namespase internal diff --git a/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix_BLAS.h b/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix_BLAS.h index a45238d..9a53185 100644 --- a/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix_BLAS.h +++ b/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix_BLAS.h @@ -40,7 +40,7 @@ namespace internal { /* Optimized selfadjoint matrix * matrix (?SYMM/?HEMM) product */ -#define EIGEN_BLAS_SYMM_L(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \ +#define EIGEN_BLAS_SYMM_L(EIGTYPE, BLASTYPE, EIGPREFIX, BLASFUNC) \ template <typename Index, \ int LhsStorageOrder, bool ConjugateLhs, \ int RhsStorageOrder, bool ConjugateRhs> \ @@ -81,13 +81,13 @@ struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,true,ConjugateLh ldb = convert_index<BlasIndex>(b_tmp.outerStride()); \ } else b = _rhs; \ \ - BLASPREFIX##symm_(&side, &uplo, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, &numext::real_ref(beta), (BLASTYPE*)res, &ldc); \ + BLASFUNC(&side, &uplo, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, (const BLASTYPE*)&numext::real_ref(beta), (BLASTYPE*)res, &ldc); \ \ } \ }; -#define EIGEN_BLAS_HEMM_L(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \ +#define EIGEN_BLAS_HEMM_L(EIGTYPE, BLASTYPE, EIGPREFIX, BLASFUNC) \ template <typename Index, \ int LhsStorageOrder, bool ConjugateLhs, \ int RhsStorageOrder, bool ConjugateRhs> \ @@ -144,20 +144,26 @@ struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,true,ConjugateLh ldb = convert_index<BlasIndex>(b_tmp.outerStride()); \ } \ \ - BLASPREFIX##hemm_(&side, &uplo, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, &numext::real_ref(beta), (BLASTYPE*)res, &ldc); \ + BLASFUNC(&side, &uplo, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, (const BLASTYPE*)&numext::real_ref(beta), (BLASTYPE*)res, &ldc); \ \ } \ }; -EIGEN_BLAS_SYMM_L(double, double, d, d) -EIGEN_BLAS_SYMM_L(float, float, f, s) -EIGEN_BLAS_HEMM_L(dcomplex, double, cd, z) -EIGEN_BLAS_HEMM_L(scomplex, float, cf, c) - +#ifdef EIGEN_USE_MKL +EIGEN_BLAS_SYMM_L(double, double, d, dsymm) +EIGEN_BLAS_SYMM_L(float, float, f, ssymm) +EIGEN_BLAS_HEMM_L(dcomplex, MKL_Complex16, cd, zhemm) +EIGEN_BLAS_HEMM_L(scomplex, MKL_Complex8, cf, chemm) +#else +EIGEN_BLAS_SYMM_L(double, double, d, dsymm_) +EIGEN_BLAS_SYMM_L(float, float, f, ssymm_) +EIGEN_BLAS_HEMM_L(dcomplex, double, cd, zhemm_) +EIGEN_BLAS_HEMM_L(scomplex, float, cf, chemm_) +#endif /* Optimized matrix * selfadjoint matrix (?SYMM/?HEMM) product */ -#define EIGEN_BLAS_SYMM_R(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \ +#define EIGEN_BLAS_SYMM_R(EIGTYPE, BLASTYPE, EIGPREFIX, BLASFUNC) \ template <typename Index, \ int LhsStorageOrder, bool ConjugateLhs, \ int RhsStorageOrder, bool ConjugateRhs> \ @@ -197,13 +203,13 @@ struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,false,ConjugateL ldb = convert_index<BlasIndex>(b_tmp.outerStride()); \ } else b = _lhs; \ \ - BLASPREFIX##symm_(&side, &uplo, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, &numext::real_ref(beta), (BLASTYPE*)res, &ldc); \ + BLASFUNC(&side, &uplo, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, (const BLASTYPE*)&numext::real_ref(beta), (BLASTYPE*)res, &ldc); \ \ } \ }; -#define EIGEN_BLAS_HEMM_R(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \ +#define EIGEN_BLAS_HEMM_R(EIGTYPE, BLASTYPE, EIGPREFIX, BLASFUNC) \ template <typename Index, \ int LhsStorageOrder, bool ConjugateLhs, \ int RhsStorageOrder, bool ConjugateRhs> \ @@ -259,15 +265,21 @@ struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,false,ConjugateL ldb = convert_index<BlasIndex>(b_tmp.outerStride()); \ } \ \ - BLASPREFIX##hemm_(&side, &uplo, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, &numext::real_ref(beta), (BLASTYPE*)res, &ldc); \ + BLASFUNC(&side, &uplo, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)b, &ldb, (const BLASTYPE*)&numext::real_ref(beta), (BLASTYPE*)res, &ldc); \ } \ }; -EIGEN_BLAS_SYMM_R(double, double, d, d) -EIGEN_BLAS_SYMM_R(float, float, f, s) -EIGEN_BLAS_HEMM_R(dcomplex, double, cd, z) -EIGEN_BLAS_HEMM_R(scomplex, float, cf, c) - +#ifdef EIGEN_USE_MKL +EIGEN_BLAS_SYMM_R(double, double, d, dsymm) +EIGEN_BLAS_SYMM_R(float, float, f, ssymm) +EIGEN_BLAS_HEMM_R(dcomplex, MKL_Complex16, cd, zhemm) +EIGEN_BLAS_HEMM_R(scomplex, MKL_Complex8, cf, chemm) +#else +EIGEN_BLAS_SYMM_R(double, double, d, dsymm_) +EIGEN_BLAS_SYMM_R(float, float, f, ssymm_) +EIGEN_BLAS_HEMM_R(dcomplex, double, cd, zhemm_) +EIGEN_BLAS_HEMM_R(scomplex, float, cf, chemm_) +#endif } // end namespace internal } // end namespace Eigen diff --git a/eigen/Eigen/src/Core/products/SelfadjointMatrixVector_BLAS.h b/eigen/Eigen/src/Core/products/SelfadjointMatrixVector_BLAS.h index 38f23ac..1238345 100644 --- a/eigen/Eigen/src/Core/products/SelfadjointMatrixVector_BLAS.h +++ b/eigen/Eigen/src/Core/products/SelfadjointMatrixVector_BLAS.h @@ -95,14 +95,21 @@ const EIGTYPE* _rhs, EIGTYPE* res, EIGTYPE alpha) \ x_tmp=map_x.conjugate(); \ x_ptr=x_tmp.data(); \ } else x_ptr=_rhs; \ - BLASFUNC(&uplo, &n, &numext::real_ref(alpha), (const BLASTYPE*)lhs, &lda, (const BLASTYPE*)x_ptr, &incx, &numext::real_ref(beta), (BLASTYPE*)res, &incy); \ + BLASFUNC(&uplo, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)lhs, &lda, (const BLASTYPE*)x_ptr, &incx, (const BLASTYPE*)&numext::real_ref(beta), (BLASTYPE*)res, &incy); \ }\ }; +#ifdef EIGEN_USE_MKL +EIGEN_BLAS_SYMV_SPECIALIZATION(double, double, dsymv) +EIGEN_BLAS_SYMV_SPECIALIZATION(float, float, ssymv) +EIGEN_BLAS_SYMV_SPECIALIZATION(dcomplex, MKL_Complex16, zhemv) +EIGEN_BLAS_SYMV_SPECIALIZATION(scomplex, MKL_Complex8, chemv) +#else EIGEN_BLAS_SYMV_SPECIALIZATION(double, double, dsymv_) EIGEN_BLAS_SYMV_SPECIALIZATION(float, float, ssymv_) EIGEN_BLAS_SYMV_SPECIALIZATION(dcomplex, double, zhemv_) EIGEN_BLAS_SYMV_SPECIALIZATION(scomplex, float, chemv_) +#endif } // end namespace internal diff --git a/eigen/Eigen/src/Core/products/TriangularMatrixMatrix.h b/eigen/Eigen/src/Core/products/TriangularMatrixMatrix.h index 6ec5a8a..f784507 100644 --- a/eigen/Eigen/src/Core/products/TriangularMatrixMatrix.h +++ b/eigen/Eigen/src/Core/products/TriangularMatrixMatrix.h @@ -137,7 +137,13 @@ EIGEN_DONT_INLINE void product_triangular_matrix_matrix<Scalar,Index,Mode,true, ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA()); ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB()); - Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,LhsStorageOrder> triangularBuffer((internal::constructor_without_unaligned_array_assert())); + // To work around an "error: member reference base type 'Matrix<...> + // (Eigen::internal::constructor_without_unaligned_array_assert (*)())' is + // not a structure or union" compilation error in nvcc (tested V8.0.61), + // create a dummy internal::constructor_without_unaligned_array_assert + // object to pass to the Matrix constructor. + internal::constructor_without_unaligned_array_assert a; + Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,LhsStorageOrder> triangularBuffer(a); triangularBuffer.setZero(); if((Mode&ZeroDiag)==ZeroDiag) triangularBuffer.diagonal().setZero(); @@ -284,7 +290,8 @@ EIGEN_DONT_INLINE void product_triangular_matrix_matrix<Scalar,Index,Mode,false, ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA()); ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB()); - Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,RhsStorageOrder> triangularBuffer((internal::constructor_without_unaligned_array_assert())); + internal::constructor_without_unaligned_array_assert a; + Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,RhsStorageOrder> triangularBuffer(a); triangularBuffer.setZero(); if((Mode&ZeroDiag)==ZeroDiag) triangularBuffer.diagonal().setZero(); @@ -393,7 +400,9 @@ struct triangular_product_impl<Mode,LhsIsTriangular,Lhs,false,Rhs,false> { template<typename Dest> static void run(Dest& dst, const Lhs &a_lhs, const Rhs &a_rhs, const typename Dest::Scalar& alpha) { - typedef typename Dest::Scalar Scalar; + typedef typename Lhs::Scalar LhsScalar; + typedef typename Rhs::Scalar RhsScalar; + typedef typename Dest::Scalar Scalar; typedef internal::blas_traits<Lhs> LhsBlasTraits; typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType; @@ -405,8 +414,9 @@ struct triangular_product_impl<Mode,LhsIsTriangular,Lhs,false,Rhs,false> typename internal::add_const_on_value_type<ActualLhsType>::type lhs = LhsBlasTraits::extract(a_lhs); typename internal::add_const_on_value_type<ActualRhsType>::type rhs = RhsBlasTraits::extract(a_rhs); - Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(a_lhs) - * RhsBlasTraits::extractScalarFactor(a_rhs); + LhsScalar lhs_alpha = LhsBlasTraits::extractScalarFactor(a_lhs); + RhsScalar rhs_alpha = RhsBlasTraits::extractScalarFactor(a_rhs); + Scalar actualAlpha = alpha * lhs_alpha * rhs_alpha; typedef internal::gemm_blocking_space<(Dest::Flags&RowMajorBit) ? RowMajor : ColMajor,Scalar,Scalar, Lhs::MaxRowsAtCompileTime, Rhs::MaxColsAtCompileTime, Lhs::MaxColsAtCompileTime,4> BlockingType; @@ -431,6 +441,21 @@ struct triangular_product_impl<Mode,LhsIsTriangular,Lhs,false,Rhs,false> &dst.coeffRef(0,0), dst.outerStride(), // result info actualAlpha, blocking ); + + // Apply correction if the diagonal is unit and a scalar factor was nested: + if ((Mode&UnitDiag)==UnitDiag) + { + if (LhsIsTriangular && lhs_alpha!=LhsScalar(1)) + { + Index diagSize = (std::min)(lhs.rows(),lhs.cols()); + dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize); + } + else if ((!LhsIsTriangular) && rhs_alpha!=RhsScalar(1)) + { + Index diagSize = (std::min)(rhs.rows(),rhs.cols()); + dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); + } + } } }; diff --git a/eigen/Eigen/src/Core/products/TriangularMatrixMatrix_BLAS.h b/eigen/Eigen/src/Core/products/TriangularMatrixMatrix_BLAS.h index aecded6..a25197a 100644 --- a/eigen/Eigen/src/Core/products/TriangularMatrixMatrix_BLAS.h +++ b/eigen/Eigen/src/Core/products/TriangularMatrixMatrix_BLAS.h @@ -75,7 +75,7 @@ EIGEN_BLAS_TRMM_SPECIALIZE(scomplex, true) EIGEN_BLAS_TRMM_SPECIALIZE(scomplex, false) // implements col-major += alpha * op(triangular) * op(general) -#define EIGEN_BLAS_TRMM_L(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \ +#define EIGEN_BLAS_TRMM_L(EIGTYPE, BLASTYPE, EIGPREFIX, BLASFUNC) \ template <typename Index, int Mode, \ int LhsStorageOrder, bool ConjugateLhs, \ int RhsStorageOrder, bool ConjugateRhs> \ @@ -172,7 +172,7 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,true, \ } \ /*std::cout << "TRMM_L: A is square! Go to BLAS TRMM implementation! \n";*/ \ /* call ?trmm*/ \ - BLASPREFIX##trmm_(&side, &uplo, &transa, &diag, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)b, &ldb); \ + BLASFUNC(&side, &uplo, &transa, &diag, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)b, &ldb); \ \ /* Add op(a_triangular)*b into res*/ \ Map<MatrixX##EIGPREFIX, 0, OuterStride<> > res_tmp(res,rows,cols,OuterStride<>(resStride)); \ @@ -180,13 +180,20 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,true, \ } \ }; -EIGEN_BLAS_TRMM_L(double, double, d, d) -EIGEN_BLAS_TRMM_L(dcomplex, double, cd, z) -EIGEN_BLAS_TRMM_L(float, float, f, s) -EIGEN_BLAS_TRMM_L(scomplex, float, cf, c) +#ifdef EIGEN_USE_MKL +EIGEN_BLAS_TRMM_L(double, double, d, dtrmm) +EIGEN_BLAS_TRMM_L(dcomplex, MKL_Complex16, cd, ztrmm) +EIGEN_BLAS_TRMM_L(float, float, f, strmm) +EIGEN_BLAS_TRMM_L(scomplex, MKL_Complex8, cf, ctrmm) +#else +EIGEN_BLAS_TRMM_L(double, double, d, dtrmm_) +EIGEN_BLAS_TRMM_L(dcomplex, double, cd, ztrmm_) +EIGEN_BLAS_TRMM_L(float, float, f, strmm_) +EIGEN_BLAS_TRMM_L(scomplex, float, cf, ctrmm_) +#endif // implements col-major += alpha * op(general) * op(triangular) -#define EIGEN_BLAS_TRMM_R(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \ +#define EIGEN_BLAS_TRMM_R(EIGTYPE, BLASTYPE, EIGPREFIX, BLASFUNC) \ template <typename Index, int Mode, \ int LhsStorageOrder, bool ConjugateLhs, \ int RhsStorageOrder, bool ConjugateRhs> \ @@ -282,7 +289,7 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,false, \ } \ /*std::cout << "TRMM_R: A is square! Go to BLAS TRMM implementation! \n";*/ \ /* call ?trmm*/ \ - BLASPREFIX##trmm_(&side, &uplo, &transa, &diag, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)b, &ldb); \ + BLASFUNC(&side, &uplo, &transa, &diag, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)b, &ldb); \ \ /* Add op(a_triangular)*b into res*/ \ Map<MatrixX##EIGPREFIX, 0, OuterStride<> > res_tmp(res,rows,cols,OuterStride<>(resStride)); \ @@ -290,11 +297,17 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,false, \ } \ }; -EIGEN_BLAS_TRMM_R(double, double, d, d) -EIGEN_BLAS_TRMM_R(dcomplex, double, cd, z) -EIGEN_BLAS_TRMM_R(float, float, f, s) -EIGEN_BLAS_TRMM_R(scomplex, float, cf, c) - +#ifdef EIGEN_USE_MKL +EIGEN_BLAS_TRMM_R(double, double, d, dtrmm) +EIGEN_BLAS_TRMM_R(dcomplex, MKL_Complex16, cd, ztrmm) +EIGEN_BLAS_TRMM_R(float, float, f, strmm) +EIGEN_BLAS_TRMM_R(scomplex, MKL_Complex8, cf, ctrmm) +#else +EIGEN_BLAS_TRMM_R(double, double, d, dtrmm_) +EIGEN_BLAS_TRMM_R(dcomplex, double, cd, ztrmm_) +EIGEN_BLAS_TRMM_R(float, float, f, strmm_) +EIGEN_BLAS_TRMM_R(scomplex, float, cf, ctrmm_) +#endif } // end namespace internal } // end namespace Eigen diff --git a/eigen/Eigen/src/Core/products/TriangularMatrixVector.h b/eigen/Eigen/src/Core/products/TriangularMatrixVector.h index 4b292e7..76bfa15 100644 --- a/eigen/Eigen/src/Core/products/TriangularMatrixVector.h +++ b/eigen/Eigen/src/Core/products/TriangularMatrixVector.h @@ -221,8 +221,9 @@ template<int Mode> struct trmv_selector<Mode,ColMajor> typename internal::add_const_on_value_type<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(lhs); typename internal::add_const_on_value_type<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(rhs); - ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(lhs) - * RhsBlasTraits::extractScalarFactor(rhs); + LhsScalar lhs_alpha = LhsBlasTraits::extractScalarFactor(lhs); + RhsScalar rhs_alpha = RhsBlasTraits::extractScalarFactor(rhs); + ResScalar actualAlpha = alpha * lhs_alpha * rhs_alpha; enum { // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1 @@ -274,6 +275,12 @@ template<int Mode> struct trmv_selector<Mode,ColMajor> else dest = MappedDest(actualDestPtr, dest.size()); } + + if ( ((Mode&UnitDiag)==UnitDiag) && (lhs_alpha!=LhsScalar(1)) ) + { + Index diagSize = (std::min)(lhs.rows(),lhs.cols()); + dest.head(diagSize) -= (lhs_alpha-LhsScalar(1))*rhs.head(diagSize); + } } }; @@ -295,8 +302,9 @@ template<int Mode> struct trmv_selector<Mode,RowMajor> typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(lhs); typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(rhs); - ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(lhs) - * RhsBlasTraits::extractScalarFactor(rhs); + LhsScalar lhs_alpha = LhsBlasTraits::extractScalarFactor(lhs); + RhsScalar rhs_alpha = RhsBlasTraits::extractScalarFactor(rhs); + ResScalar actualAlpha = alpha * lhs_alpha * rhs_alpha; enum { DirectlyUseRhs = ActualRhsTypeCleaned::InnerStrideAtCompileTime==1 @@ -326,6 +334,12 @@ template<int Mode> struct trmv_selector<Mode,RowMajor> actualRhsPtr,1, dest.data(),dest.innerStride(), actualAlpha); + + if ( ((Mode&UnitDiag)==UnitDiag) && (lhs_alpha!=LhsScalar(1)) ) + { + Index diagSize = (std::min)(lhs.rows(),lhs.cols()); + dest.head(diagSize) -= (lhs_alpha-LhsScalar(1))*rhs.head(diagSize); + } } }; diff --git a/eigen/Eigen/src/Core/products/TriangularMatrixVector_BLAS.h b/eigen/Eigen/src/Core/products/TriangularMatrixVector_BLAS.h index 07bf26c..3d47a2b 100644 --- a/eigen/Eigen/src/Core/products/TriangularMatrixVector_BLAS.h +++ b/eigen/Eigen/src/Core/products/TriangularMatrixVector_BLAS.h @@ -71,7 +71,7 @@ EIGEN_BLAS_TRMV_SPECIALIZE(dcomplex) EIGEN_BLAS_TRMV_SPECIALIZE(scomplex) // implements col-major: res += alpha * op(triangular) * vector -#define EIGEN_BLAS_TRMV_CM(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \ +#define EIGEN_BLAS_TRMV_CM(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX, BLASPOSTFIX) \ template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \ struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,ColMajor> { \ enum { \ @@ -121,10 +121,10 @@ struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE, diag = IsUnitDiag ? 'U' : 'N'; \ \ /* call ?TRMV*/ \ - BLASPREFIX##trmv_(&uplo, &trans, &diag, &n, (const BLASTYPE*)_lhs, &lda, (BLASTYPE*)x, &incx); \ + BLASPREFIX##trmv##BLASPOSTFIX(&uplo, &trans, &diag, &n, (const BLASTYPE*)_lhs, &lda, (BLASTYPE*)x, &incx); \ \ /* Add op(a_tr)rhs into res*/ \ - BLASPREFIX##axpy_(&n, &numext::real_ref(alpha),(const BLASTYPE*)x, &incx, (BLASTYPE*)_res, &incy); \ + BLASPREFIX##axpy##BLASPOSTFIX(&n, (const BLASTYPE*)&numext::real_ref(alpha),(const BLASTYPE*)x, &incx, (BLASTYPE*)_res, &incy); \ /* Non-square case - doesn't fit to BLAS ?TRMV. Fall to default triangular product*/ \ if (size<(std::max)(rows,cols)) { \ if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \ @@ -142,18 +142,25 @@ struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE, m = convert_index<BlasIndex>(size); \ n = convert_index<BlasIndex>(cols-size); \ } \ - BLASPREFIX##gemv_(&trans, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)x, &incx, &numext::real_ref(beta), (BLASTYPE*)y, &incy); \ + BLASPREFIX##gemv##BLASPOSTFIX(&trans, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)x, &incx, (const BLASTYPE*)&numext::real_ref(beta), (BLASTYPE*)y, &incy); \ } \ } \ }; -EIGEN_BLAS_TRMV_CM(double, double, d, d) -EIGEN_BLAS_TRMV_CM(dcomplex, double, cd, z) -EIGEN_BLAS_TRMV_CM(float, float, f, s) -EIGEN_BLAS_TRMV_CM(scomplex, float, cf, c) +#ifdef EIGEN_USE_MKL +EIGEN_BLAS_TRMV_CM(double, double, d, d,) +EIGEN_BLAS_TRMV_CM(dcomplex, MKL_Complex16, cd, z,) +EIGEN_BLAS_TRMV_CM(float, float, f, s,) +EIGEN_BLAS_TRMV_CM(scomplex, MKL_Complex8, cf, c,) +#else +EIGEN_BLAS_TRMV_CM(double, double, d, d, _) +EIGEN_BLAS_TRMV_CM(dcomplex, double, cd, z, _) +EIGEN_BLAS_TRMV_CM(float, float, f, s, _) +EIGEN_BLAS_TRMV_CM(scomplex, float, cf, c, _) +#endif // implements row-major: res += alpha * op(triangular) * vector -#define EIGEN_BLAS_TRMV_RM(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX) \ +#define EIGEN_BLAS_TRMV_RM(EIGTYPE, BLASTYPE, EIGPREFIX, BLASPREFIX, BLASPOSTFIX) \ template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \ struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,RowMajor> { \ enum { \ @@ -203,10 +210,10 @@ struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE, diag = IsUnitDiag ? 'U' : 'N'; \ \ /* call ?TRMV*/ \ - BLASPREFIX##trmv_(&uplo, &trans, &diag, &n, (const BLASTYPE*)_lhs, &lda, (BLASTYPE*)x, &incx); \ + BLASPREFIX##trmv##BLASPOSTFIX(&uplo, &trans, &diag, &n, (const BLASTYPE*)_lhs, &lda, (BLASTYPE*)x, &incx); \ \ /* Add op(a_tr)rhs into res*/ \ - BLASPREFIX##axpy_(&n, &numext::real_ref(alpha),(const BLASTYPE*)x, &incx, (BLASTYPE*)_res, &incy); \ + BLASPREFIX##axpy##BLASPOSTFIX(&n, (const BLASTYPE*)&numext::real_ref(alpha),(const BLASTYPE*)x, &incx, (BLASTYPE*)_res, &incy); \ /* Non-square case - doesn't fit to BLAS ?TRMV. Fall to default triangular product*/ \ if (size<(std::max)(rows,cols)) { \ if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \ @@ -224,15 +231,22 @@ struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE, m = convert_index<BlasIndex>(size); \ n = convert_index<BlasIndex>(cols-size); \ } \ - BLASPREFIX##gemv_(&trans, &n, &m, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)x, &incx, &numext::real_ref(beta), (BLASTYPE*)y, &incy); \ + BLASPREFIX##gemv##BLASPOSTFIX(&trans, &n, &m, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (const BLASTYPE*)x, &incx, (const BLASTYPE*)&numext::real_ref(beta), (BLASTYPE*)y, &incy); \ } \ } \ }; -EIGEN_BLAS_TRMV_RM(double, double, d, d) -EIGEN_BLAS_TRMV_RM(dcomplex, double, cd, z) -EIGEN_BLAS_TRMV_RM(float, float, f, s) -EIGEN_BLAS_TRMV_RM(scomplex, float, cf, c) +#ifdef EIGEN_USE_MKL +EIGEN_BLAS_TRMV_RM(double, double, d, d,) +EIGEN_BLAS_TRMV_RM(dcomplex, MKL_Complex16, cd, z,) +EIGEN_BLAS_TRMV_RM(float, float, f, s,) +EIGEN_BLAS_TRMV_RM(scomplex, MKL_Complex8, cf, c,) +#else +EIGEN_BLAS_TRMV_RM(double, double, d, d,_) +EIGEN_BLAS_TRMV_RM(dcomplex, double, cd, z,_) +EIGEN_BLAS_TRMV_RM(float, float, f, s,_) +EIGEN_BLAS_TRMV_RM(scomplex, float, cf, c,_) +#endif } // end namespase internal diff --git a/eigen/Eigen/src/Core/products/TriangularSolverMatrix_BLAS.h b/eigen/Eigen/src/Core/products/TriangularSolverMatrix_BLAS.h index 88c0fb7..f077511 100644 --- a/eigen/Eigen/src/Core/products/TriangularSolverMatrix_BLAS.h +++ b/eigen/Eigen/src/Core/products/TriangularSolverMatrix_BLAS.h @@ -38,7 +38,7 @@ namespace Eigen { namespace internal { // implements LeftSide op(triangular)^-1 * general -#define EIGEN_BLAS_TRSM_L(EIGTYPE, BLASTYPE, BLASPREFIX) \ +#define EIGEN_BLAS_TRSM_L(EIGTYPE, BLASTYPE, BLASFUNC) \ template <typename Index, int Mode, bool Conjugate, int TriStorageOrder> \ struct triangular_solve_matrix<EIGTYPE,Index,OnTheLeft,Mode,Conjugate,TriStorageOrder,ColMajor> \ { \ @@ -80,18 +80,24 @@ struct triangular_solve_matrix<EIGTYPE,Index,OnTheLeft,Mode,Conjugate,TriStorage } \ if (IsUnitDiag) diag='U'; \ /* call ?trsm*/ \ - BLASPREFIX##trsm_(&side, &uplo, &transa, &diag, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)_other, &ldb); \ + BLASFUNC(&side, &uplo, &transa, &diag, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)_other, &ldb); \ } \ }; -EIGEN_BLAS_TRSM_L(double, double, d) -EIGEN_BLAS_TRSM_L(dcomplex, double, z) -EIGEN_BLAS_TRSM_L(float, float, s) -EIGEN_BLAS_TRSM_L(scomplex, float, c) - +#ifdef EIGEN_USE_MKL +EIGEN_BLAS_TRSM_L(double, double, dtrsm) +EIGEN_BLAS_TRSM_L(dcomplex, MKL_Complex16, ztrsm) +EIGEN_BLAS_TRSM_L(float, float, strsm) +EIGEN_BLAS_TRSM_L(scomplex, MKL_Complex8, ctrsm) +#else +EIGEN_BLAS_TRSM_L(double, double, dtrsm_) +EIGEN_BLAS_TRSM_L(dcomplex, double, ztrsm_) +EIGEN_BLAS_TRSM_L(float, float, strsm_) +EIGEN_BLAS_TRSM_L(scomplex, float, ctrsm_) +#endif // implements RightSide general * op(triangular)^-1 -#define EIGEN_BLAS_TRSM_R(EIGTYPE, BLASTYPE, BLASPREFIX) \ +#define EIGEN_BLAS_TRSM_R(EIGTYPE, BLASTYPE, BLASFUNC) \ template <typename Index, int Mode, bool Conjugate, int TriStorageOrder> \ struct triangular_solve_matrix<EIGTYPE,Index,OnTheRight,Mode,Conjugate,TriStorageOrder,ColMajor> \ { \ @@ -133,16 +139,22 @@ struct triangular_solve_matrix<EIGTYPE,Index,OnTheRight,Mode,Conjugate,TriStorag } \ if (IsUnitDiag) diag='U'; \ /* call ?trsm*/ \ - BLASPREFIX##trsm_(&side, &uplo, &transa, &diag, &m, &n, &numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)_other, &ldb); \ + BLASFUNC(&side, &uplo, &transa, &diag, &m, &n, (const BLASTYPE*)&numext::real_ref(alpha), (const BLASTYPE*)a, &lda, (BLASTYPE*)_other, &ldb); \ /*std::cout << "TRMS_L specialization!\n";*/ \ } \ }; -EIGEN_BLAS_TRSM_R(double, double, d) -EIGEN_BLAS_TRSM_R(dcomplex, double, z) -EIGEN_BLAS_TRSM_R(float, float, s) -EIGEN_BLAS_TRSM_R(scomplex, float, c) - +#ifdef EIGEN_USE_MKL +EIGEN_BLAS_TRSM_R(double, double, dtrsm) +EIGEN_BLAS_TRSM_R(dcomplex, MKL_Complex16, ztrsm) +EIGEN_BLAS_TRSM_R(float, float, strsm) +EIGEN_BLAS_TRSM_R(scomplex, MKL_Complex8, ctrsm) +#else +EIGEN_BLAS_TRSM_R(double, double, dtrsm_) +EIGEN_BLAS_TRSM_R(dcomplex, double, ztrsm_) +EIGEN_BLAS_TRSM_R(float, float, strsm_) +EIGEN_BLAS_TRSM_R(scomplex, float, ctrsm_) +#endif } // end namespace internal diff --git a/eigen/Eigen/src/Core/util/MKL_support.h b/eigen/Eigen/src/Core/util/MKL_support.h index 26b5966..b7d6ecc 100644 --- a/eigen/Eigen/src/Core/util/MKL_support.h +++ b/eigen/Eigen/src/Core/util/MKL_support.h @@ -49,10 +49,11 @@ #define EIGEN_USE_LAPACKE #endif -#if defined(EIGEN_USE_MKL_VML) +#if defined(EIGEN_USE_MKL_VML) && !defined(EIGEN_USE_MKL) #define EIGEN_USE_MKL #endif + #if defined EIGEN_USE_MKL # include <mkl.h> /*Check IMKL version for compatibility: < 10.3 is not usable with Eigen*/ @@ -108,6 +109,10 @@ #endif #endif +#if defined(EIGEN_USE_BLAS) && !defined(EIGEN_USE_MKL) +#include "../../misc/blas.h" +#endif + namespace Eigen { typedef std::complex<double> dcomplex; @@ -121,8 +126,5 @@ typedef int BlasIndex; } // end namespace Eigen -#if defined(EIGEN_USE_BLAS) -#include "../../misc/blas.h" -#endif #endif // EIGEN_MKL_SUPPORT_H diff --git a/eigen/Eigen/src/Core/util/Macros.h b/eigen/Eigen/src/Core/util/Macros.h index 38d6ddb..02d21d2 100644 --- a/eigen/Eigen/src/Core/util/Macros.h +++ b/eigen/Eigen/src/Core/util/Macros.h @@ -13,7 +13,7 @@ #define EIGEN_WORLD_VERSION 3 #define EIGEN_MAJOR_VERSION 3 -#define EIGEN_MINOR_VERSION 4 +#define EIGEN_MINOR_VERSION 5 #define EIGEN_VERSION_AT_LEAST(x,y,z) (EIGEN_WORLD_VERSION>x || (EIGEN_WORLD_VERSION>=x && \ (EIGEN_MAJOR_VERSION>y || (EIGEN_MAJOR_VERSION>=y && \ @@ -399,7 +399,7 @@ // Does the compiler support variadic templates? #ifndef EIGEN_HAS_VARIADIC_TEMPLATES #if EIGEN_MAX_CPP_VER>=11 && (__cplusplus > 199711L || EIGEN_COMP_MSVC >= 1900) \ - && ( !defined(__NVCC__) || !EIGEN_ARCH_ARM_OR_ARM64 || (defined __CUDACC_VER__ && __CUDACC_VER__ >= 80000) ) + && (!defined(__NVCC__) || !EIGEN_ARCH_ARM_OR_ARM64 || (EIGEN_CUDACC_VER >= 80000) ) // ^^ Disable the use of variadic templates when compiling with versions of nvcc older than 8.0 on ARM devices: // this prevents nvcc from crashing when compiling Eigen on Tegra X1 #define EIGEN_HAS_VARIADIC_TEMPLATES 1 @@ -413,7 +413,7 @@ #ifdef __CUDACC__ // Const expressions are supported provided that c++11 is enabled and we're using either clang or nvcc 7.5 or above -#if EIGEN_MAX_CPP_VER>=14 && (__cplusplus > 199711L && defined(__CUDACC_VER__) && (EIGEN_COMP_CLANG || __CUDACC_VER__ >= 70500)) +#if EIGEN_MAX_CPP_VER>=14 && (__cplusplus > 199711L && (EIGEN_COMP_CLANG || EIGEN_CUDACC_VER >= 70500)) #define EIGEN_HAS_CONSTEXPR 1 #endif #elif EIGEN_MAX_CPP_VER>=14 && (__has_feature(cxx_relaxed_constexpr) || (defined(__cplusplus) && __cplusplus >= 201402L) || \ @@ -487,11 +487,13 @@ // EIGEN_STRONG_INLINE is a stronger version of the inline, using __forceinline on MSVC, // but it still doesn't use GCC's always_inline. This is useful in (common) situations where MSVC needs forceinline // but GCC is still doing fine with just inline. +#ifndef EIGEN_STRONG_INLINE #if EIGEN_COMP_MSVC || EIGEN_COMP_ICC #define EIGEN_STRONG_INLINE __forceinline #else #define EIGEN_STRONG_INLINE inline #endif +#endif // EIGEN_ALWAYS_INLINE is the stronget, it has the effect of making the function inline and adding every possible // attribute to maximize inlining. This should only be used when really necessary: in particular, @@ -812,7 +814,8 @@ namespace Eigen { // just an empty macro ! #define EIGEN_EMPTY -#if EIGEN_COMP_MSVC_STRICT && (EIGEN_COMP_MSVC < 1900 || defined(__CUDACC_VER__)) // for older MSVC versions, as well as 1900 && CUDA 8, using the base operator is sufficient (cf Bugs 1000, 1324) +#if EIGEN_COMP_MSVC_STRICT && (EIGEN_COMP_MSVC < 1900 || EIGEN_CUDACC_VER>0) + // for older MSVC versions, as well as 1900 && CUDA 8, using the base operator is sufficient (cf Bugs 1000, 1324) #define EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived) \ using Base::operator =; #elif EIGEN_COMP_CLANG // workaround clang bug (see http://forum.kde.org/viewtopic.php?f=74&t=102653) @@ -986,7 +989,13 @@ namespace Eigen { # define EIGEN_NOEXCEPT # define EIGEN_NOEXCEPT_IF(x) # define EIGEN_NO_THROW throw() -# define EIGEN_EXCEPTION_SPEC(X) throw(X) +# if EIGEN_COMP_MSVC + // MSVC does not support exception specifications (warning C4290), + // and they are deprecated in c++11 anyway. +# define EIGEN_EXCEPTION_SPEC(X) throw() +# else +# define EIGEN_EXCEPTION_SPEC(X) throw(X) +# endif #endif #endif // EIGEN_MACROS_H diff --git a/eigen/Eigen/src/Core/util/Memory.h b/eigen/Eigen/src/Core/util/Memory.h index c634d7e..66cdbd8 100644 --- a/eigen/Eigen/src/Core/util/Memory.h +++ b/eigen/Eigen/src/Core/util/Memory.h @@ -70,7 +70,7 @@ inline void throw_std_bad_alloc() throw std::bad_alloc(); #else std::size_t huge = static_cast<std::size_t>(-1); - new int[huge]; + ::operator new(huge); #endif } @@ -493,7 +493,7 @@ template<typename T> struct smart_copy_helper<T,true> { IntPtr size = IntPtr(end)-IntPtr(start); if(size==0) return; eigen_internal_assert(start!=0 && end!=0 && target!=0); - memcpy(target, start, size); + std::memcpy(target, start, size); } }; @@ -696,7 +696,15 @@ template<typename T> void swap(scoped_array<T> &a,scoped_array<T> &b) /** \class aligned_allocator * \ingroup Core_Module * -* \brief STL compatible allocator to use with with 16 byte aligned types +* \brief STL compatible allocator to use with types requiring a non standrad alignment. +* +* The memory is aligned as for dynamically aligned matrix/array types such as MatrixXd. +* By default, it will thus provide at least 16 bytes alignment and more in following cases: +* - 32 bytes alignment if AVX is enabled. +* - 64 bytes alignment if AVX512 is enabled. +* +* This can be controled using the \c EIGEN_MAX_ALIGN_BYTES macro as documented +* \link TopicPreprocessorDirectivesPerformance there \endlink. * * Example: * \code diff --git a/eigen/Eigen/src/Core/util/Meta.h b/eigen/Eigen/src/Core/util/Meta.h index 7f63707..1d73f05 100644 --- a/eigen/Eigen/src/Core/util/Meta.h +++ b/eigen/Eigen/src/Core/util/Meta.h @@ -485,6 +485,26 @@ T div_ceil(const T &a, const T &b) return (a+b-1) / b; } +// The aim of the following functions is to bypass -Wfloat-equal warnings +// when we really want a strict equality comparison on floating points. +template<typename X, typename Y> EIGEN_STRONG_INLINE +bool equal_strict(const X& x,const Y& y) { return x == y; } + +template<> EIGEN_STRONG_INLINE +bool equal_strict(const float& x,const float& y) { return std::equal_to<float>()(x,y); } + +template<> EIGEN_STRONG_INLINE +bool equal_strict(const double& x,const double& y) { return std::equal_to<double>()(x,y); } + +template<typename X, typename Y> EIGEN_STRONG_INLINE +bool not_equal_strict(const X& x,const Y& y) { return x != y; } + +template<> EIGEN_STRONG_INLINE +bool not_equal_strict(const float& x,const float& y) { return std::not_equal_to<float>()(x,y); } + +template<> EIGEN_STRONG_INLINE +bool not_equal_strict(const double& x,const double& y) { return std::not_equal_to<double>()(x,y); } + } // end namespace numext } // end namespace Eigen diff --git a/eigen/Eigen/src/Core/util/StaticAssert.h b/eigen/Eigen/src/Core/util/StaticAssert.h index 983361a..500e477 100644 --- a/eigen/Eigen/src/Core/util/StaticAssert.h +++ b/eigen/Eigen/src/Core/util/StaticAssert.h @@ -24,6 +24,7 @@ * */ +#ifndef EIGEN_STATIC_ASSERT #ifndef EIGEN_NO_STATIC_ASSERT #if EIGEN_MAX_CPP_VER>=11 && (__has_feature(cxx_static_assert) || (defined(__cplusplus) && __cplusplus >= 201103L) || (EIGEN_COMP_MSVC >= 1600)) @@ -44,64 +45,65 @@ struct static_assertion<true> { enum { - YOU_TRIED_CALLING_A_VECTOR_METHOD_ON_A_MATRIX, - YOU_MIXED_VECTORS_OF_DIFFERENT_SIZES, - YOU_MIXED_MATRICES_OF_DIFFERENT_SIZES, - THIS_METHOD_IS_ONLY_FOR_VECTORS_OF_A_SPECIFIC_SIZE, - THIS_METHOD_IS_ONLY_FOR_MATRICES_OF_A_SPECIFIC_SIZE, - THIS_METHOD_IS_ONLY_FOR_OBJECTS_OF_A_SPECIFIC_SIZE, - OUT_OF_RANGE_ACCESS, - YOU_MADE_A_PROGRAMMING_MISTAKE, - EIGEN_INTERNAL_ERROR_PLEASE_FILE_A_BUG_REPORT, - EIGEN_INTERNAL_COMPILATION_ERROR_OR_YOU_MADE_A_PROGRAMMING_MISTAKE, - YOU_CALLED_A_FIXED_SIZE_METHOD_ON_A_DYNAMIC_SIZE_MATRIX_OR_VECTOR, - YOU_CALLED_A_DYNAMIC_SIZE_METHOD_ON_A_FIXED_SIZE_MATRIX_OR_VECTOR, - UNALIGNED_LOAD_AND_STORE_OPERATIONS_UNIMPLEMENTED_ON_ALTIVEC, - THIS_FUNCTION_IS_NOT_FOR_INTEGER_NUMERIC_TYPES, - FLOATING_POINT_ARGUMENT_PASSED__INTEGER_WAS_EXPECTED, - NUMERIC_TYPE_MUST_BE_REAL, - COEFFICIENT_WRITE_ACCESS_TO_SELFADJOINT_NOT_SUPPORTED, - WRITING_TO_TRIANGULAR_PART_WITH_UNIT_DIAGONAL_IS_NOT_SUPPORTED, - THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE, - INVALID_MATRIX_PRODUCT, - INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS, - INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION, - YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY, - THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES, - THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES, - INVALID_MATRIX_TEMPLATE_PARAMETERS, - INVALID_MATRIXBASE_TEMPLATE_PARAMETERS, - BOTH_MATRICES_MUST_HAVE_THE_SAME_STORAGE_ORDER, - THIS_METHOD_IS_ONLY_FOR_DIAGONAL_MATRIX, - THE_MATRIX_OR_EXPRESSION_THAT_YOU_PASSED_DOES_NOT_HAVE_THE_EXPECTED_TYPE, - THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_WITH_DIRECT_MEMORY_ACCESS_SUCH_AS_MAP_OR_PLAIN_MATRICES, - YOU_ALREADY_SPECIFIED_THIS_STRIDE, - INVALID_STORAGE_ORDER_FOR_THIS_VECTOR_EXPRESSION, - THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD, - PACKET_ACCESS_REQUIRES_TO_HAVE_INNER_STRIDE_FIXED_TO_1, - THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS, - YOU_CANNOT_MIX_ARRAYS_AND_MATRICES, - YOU_PERFORMED_AN_INVALID_TRANSFORMATION_CONVERSION, - THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY, - YOU_ARE_TRYING_TO_USE_AN_INDEX_BASED_ACCESSOR_ON_AN_EXPRESSION_THAT_DOES_NOT_SUPPORT_THAT, - THIS_METHOD_IS_ONLY_FOR_1x1_EXPRESSIONS, - THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS, - THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_OF_BOOL, - THIS_METHOD_IS_ONLY_FOR_ARRAYS_NOT_MATRICES, - YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED, - YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED, - THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE, - THE_STORAGE_ORDER_OF_BOTH_SIDES_MUST_MATCH, - OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG, - IMPLICIT_CONVERSION_TO_SCALAR_IS_FOR_INNER_PRODUCT_ONLY, - STORAGE_LAYOUT_DOES_NOT_MATCH, - EIGEN_INTERNAL_ERROR_PLEASE_FILE_A_BUG_REPORT__INVALID_COST_VALUE, - THIS_COEFFICIENT_ACCESSOR_TAKING_ONE_ACCESS_IS_ONLY_FOR_EXPRESSIONS_ALLOWING_LINEAR_ACCESS, - MATRIX_FREE_CONJUGATE_GRADIENT_IS_COMPATIBLE_WITH_UPPER_UNION_LOWER_MODE_ONLY, - THIS_TYPE_IS_NOT_SUPPORTED, - STORAGE_KIND_MUST_MATCH, - STORAGE_INDEX_MUST_MATCH, - CHOLMOD_SUPPORTS_DOUBLE_PRECISION_ONLY + YOU_TRIED_CALLING_A_VECTOR_METHOD_ON_A_MATRIX=1, + YOU_MIXED_VECTORS_OF_DIFFERENT_SIZES=1, + YOU_MIXED_MATRICES_OF_DIFFERENT_SIZES=1, + THIS_METHOD_IS_ONLY_FOR_VECTORS_OF_A_SPECIFIC_SIZE=1, + THIS_METHOD_IS_ONLY_FOR_MATRICES_OF_A_SPECIFIC_SIZE=1, + THIS_METHOD_IS_ONLY_FOR_OBJECTS_OF_A_SPECIFIC_SIZE=1, + OUT_OF_RANGE_ACCESS=1, + YOU_MADE_A_PROGRAMMING_MISTAKE=1, + EIGEN_INTERNAL_ERROR_PLEASE_FILE_A_BUG_REPORT=1, + EIGEN_INTERNAL_COMPILATION_ERROR_OR_YOU_MADE_A_PROGRAMMING_MISTAKE=1, + YOU_CALLED_A_FIXED_SIZE_METHOD_ON_A_DYNAMIC_SIZE_MATRIX_OR_VECTOR=1, + YOU_CALLED_A_DYNAMIC_SIZE_METHOD_ON_A_FIXED_SIZE_MATRIX_OR_VECTOR=1, + UNALIGNED_LOAD_AND_STORE_OPERATIONS_UNIMPLEMENTED_ON_ALTIVEC=1, + THIS_FUNCTION_IS_NOT_FOR_INTEGER_NUMERIC_TYPES=1, + FLOATING_POINT_ARGUMENT_PASSED__INTEGER_WAS_EXPECTED=1, + NUMERIC_TYPE_MUST_BE_REAL=1, + COEFFICIENT_WRITE_ACCESS_TO_SELFADJOINT_NOT_SUPPORTED=1, + WRITING_TO_TRIANGULAR_PART_WITH_UNIT_DIAGONAL_IS_NOT_SUPPORTED=1, + THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE=1, + INVALID_MATRIX_PRODUCT=1, + INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS=1, + INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION=1, + YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY=1, + THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES=1, + THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES=1, + INVALID_MATRIX_TEMPLATE_PARAMETERS=1, + INVALID_MATRIXBASE_TEMPLATE_PARAMETERS=1, + BOTH_MATRICES_MUST_HAVE_THE_SAME_STORAGE_ORDER=1, + THIS_METHOD_IS_ONLY_FOR_DIAGONAL_MATRIX=1, + THE_MATRIX_OR_EXPRESSION_THAT_YOU_PASSED_DOES_NOT_HAVE_THE_EXPECTED_TYPE=1, + THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_WITH_DIRECT_MEMORY_ACCESS_SUCH_AS_MAP_OR_PLAIN_MATRICES=1, + YOU_ALREADY_SPECIFIED_THIS_STRIDE=1, + INVALID_STORAGE_ORDER_FOR_THIS_VECTOR_EXPRESSION=1, + THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD=1, + PACKET_ACCESS_REQUIRES_TO_HAVE_INNER_STRIDE_FIXED_TO_1=1, + THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS=1, + YOU_CANNOT_MIX_ARRAYS_AND_MATRICES=1, + YOU_PERFORMED_AN_INVALID_TRANSFORMATION_CONVERSION=1, + THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY=1, + YOU_ARE_TRYING_TO_USE_AN_INDEX_BASED_ACCESSOR_ON_AN_EXPRESSION_THAT_DOES_NOT_SUPPORT_THAT=1, + THIS_METHOD_IS_ONLY_FOR_1x1_EXPRESSIONS=1, + THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS=1, + THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_OF_BOOL=1, + THIS_METHOD_IS_ONLY_FOR_ARRAYS_NOT_MATRICES=1, + YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED=1, + YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED=1, + THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE=1, + THE_STORAGE_ORDER_OF_BOTH_SIDES_MUST_MATCH=1, + OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG=1, + IMPLICIT_CONVERSION_TO_SCALAR_IS_FOR_INNER_PRODUCT_ONLY=1, + STORAGE_LAYOUT_DOES_NOT_MATCH=1, + EIGEN_INTERNAL_ERROR_PLEASE_FILE_A_BUG_REPORT__INVALID_COST_VALUE=1, + THIS_COEFFICIENT_ACCESSOR_TAKING_ONE_ACCESS_IS_ONLY_FOR_EXPRESSIONS_ALLOWING_LINEAR_ACCESS=1, + MATRIX_FREE_CONJUGATE_GRADIENT_IS_COMPATIBLE_WITH_UPPER_UNION_LOWER_MODE_ONLY=1, + THIS_TYPE_IS_NOT_SUPPORTED=1, + STORAGE_KIND_MUST_MATCH=1, + STORAGE_INDEX_MUST_MATCH=1, + CHOLMOD_SUPPORTS_DOUBLE_PRECISION_ONLY=1, + SELFADJOINTVIEW_ACCEPTS_UPPER_AND_LOWER_MODE_ONLY=1 }; }; @@ -131,7 +133,7 @@ #define EIGEN_STATIC_ASSERT(CONDITION,MSG) eigen_assert((CONDITION) && #MSG); #endif // EIGEN_NO_STATIC_ASSERT - +#endif // EIGEN_STATIC_ASSERT // static assertion failing if the type \a TYPE is not a vector type #define EIGEN_STATIC_ASSERT_VECTOR_ONLY(TYPE) \ diff --git a/eigen/Eigen/src/Eigenvalues/GeneralizedEigenSolver.h b/eigen/Eigen/src/Eigenvalues/GeneralizedEigenSolver.h index 36a91df..87d789b 100644 --- a/eigen/Eigen/src/Eigenvalues/GeneralizedEigenSolver.h +++ b/eigen/Eigen/src/Eigenvalues/GeneralizedEigenSolver.h @@ -311,7 +311,6 @@ GeneralizedEigenSolver<MatrixType>::compute(const MatrixType& A, const MatrixTyp // Aliases: Map<VectorType> v(reinterpret_cast<Scalar*>(m_tmp.data()), size); ComplexVectorType &cv = m_tmp; - const MatrixType &mZ = m_realQZ.matrixZ(); const MatrixType &mS = m_realQZ.matrixS(); const MatrixType &mT = m_realQZ.matrixT(); @@ -351,7 +350,7 @@ GeneralizedEigenSolver<MatrixType>::compute(const MatrixType& A, const MatrixTyp } } } - m_eivec.col(i).real().noalias() = mZ.transpose() * v; + m_eivec.col(i).real().noalias() = m_realQZ.matrixZ().transpose() * v; m_eivec.col(i).real().normalize(); m_eivec.col(i).imag().setConstant(0); } @@ -400,7 +399,7 @@ GeneralizedEigenSolver<MatrixType>::compute(const MatrixType& A, const MatrixTyp / (alpha*mT.coeffRef(j,j) - static_cast<Scalar>(beta*mS.coeffRef(j,j))); } } - m_eivec.col(i+1).noalias() = (mZ.transpose() * cv); + m_eivec.col(i+1).noalias() = (m_realQZ.matrixZ().transpose() * cv); m_eivec.col(i+1).normalize(); m_eivec.col(i) = m_eivec.col(i+1).conjugate(); } diff --git a/eigen/Eigen/src/Eigenvalues/RealSchur.h b/eigen/Eigen/src/Eigenvalues/RealSchur.h index f5c8604..17ea903 100644 --- a/eigen/Eigen/src/Eigenvalues/RealSchur.h +++ b/eigen/Eigen/src/Eigenvalues/RealSchur.h @@ -303,7 +303,7 @@ RealSchur<MatrixType>& RealSchur<MatrixType>::computeFromHessenberg(const HessMa Scalar exshift(0); // sum of exceptional shifts Scalar norm = computeNormOfT(); - if(norm!=0) + if(norm!=Scalar(0)) { while (iu >= 0) { @@ -327,7 +327,7 @@ RealSchur<MatrixType>& RealSchur<MatrixType>::computeFromHessenberg(const HessMa else // No convergence yet { // The firstHouseholderVector vector has to be initialized to something to get rid of a silly GCC warning (-O1 -Wall -DNDEBUG ) - Vector3s firstHouseholderVector(0,0,0), shiftInfo; + Vector3s firstHouseholderVector = Vector3s::Zero(), shiftInfo; computeShift(iu, iter, exshift, shiftInfo); iter = iter + 1; totalIter = totalIter + 1; diff --git a/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_LAPACKE.h b/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_LAPACKE.h index 3891cf8..b0c947d 100644 --- a/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_LAPACKE.h +++ b/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_LAPACKE.h @@ -37,7 +37,7 @@ namespace Eigen { /** \internal Specialization for the data types supported by LAPACKe */ -#define EIGEN_LAPACKE_EIG_SELFADJ(EIGTYPE, LAPACKE_TYPE, LAPACKE_RTYPE, LAPACKE_NAME, EIGCOLROW, LAPACKE_COLROW ) \ +#define EIGEN_LAPACKE_EIG_SELFADJ_2(EIGTYPE, LAPACKE_TYPE, LAPACKE_RTYPE, LAPACKE_NAME, EIGCOLROW ) \ template<> template<typename InputType> inline \ SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \ SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const EigenBase<InputType>& matrix, int options) \ @@ -47,7 +47,7 @@ SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(c && (options&EigVecMask)!=EigVecMask \ && "invalid option parameter"); \ bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors; \ - lapack_int n = internal::convert_index<lapack_int>(matrix.cols()), lda, matrix_order, info; \ + lapack_int n = internal::convert_index<lapack_int>(matrix.cols()), lda, info; \ m_eivalues.resize(n,1); \ m_subdiag.resize(n-1); \ m_eivec = matrix; \ @@ -63,27 +63,24 @@ SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(c } \ \ lda = internal::convert_index<lapack_int>(m_eivec.outerStride()); \ - matrix_order=LAPACKE_COLROW; \ char jobz, uplo='L'/*, range='A'*/; \ jobz = computeEigenvectors ? 'V' : 'N'; \ \ - info = LAPACKE_##LAPACKE_NAME( matrix_order, jobz, uplo, n, (LAPACKE_TYPE*)m_eivec.data(), lda, (LAPACKE_RTYPE*)m_eivalues.data() ); \ + info = LAPACKE_##LAPACKE_NAME( LAPACK_COL_MAJOR, jobz, uplo, n, (LAPACKE_TYPE*)m_eivec.data(), lda, (LAPACKE_RTYPE*)m_eivalues.data() ); \ m_info = (info==0) ? Success : NoConvergence; \ m_isInitialized = true; \ m_eigenvectorsOk = computeEigenvectors; \ return *this; \ } +#define EIGEN_LAPACKE_EIG_SELFADJ(EIGTYPE, LAPACKE_TYPE, LAPACKE_RTYPE, LAPACKE_NAME ) \ + EIGEN_LAPACKE_EIG_SELFADJ_2(EIGTYPE, LAPACKE_TYPE, LAPACKE_RTYPE, LAPACKE_NAME, ColMajor ) \ + EIGEN_LAPACKE_EIG_SELFADJ_2(EIGTYPE, LAPACKE_TYPE, LAPACKE_RTYPE, LAPACKE_NAME, RowMajor ) -EIGEN_LAPACKE_EIG_SELFADJ(double, double, double, dsyev, ColMajor, LAPACK_COL_MAJOR) -EIGEN_LAPACKE_EIG_SELFADJ(float, float, float, ssyev, ColMajor, LAPACK_COL_MAJOR) -EIGEN_LAPACKE_EIG_SELFADJ(dcomplex, lapack_complex_double, double, zheev, ColMajor, LAPACK_COL_MAJOR) -EIGEN_LAPACKE_EIG_SELFADJ(scomplex, lapack_complex_float, float, cheev, ColMajor, LAPACK_COL_MAJOR) - -EIGEN_LAPACKE_EIG_SELFADJ(double, double, double, dsyev, RowMajor, LAPACK_ROW_MAJOR) -EIGEN_LAPACKE_EIG_SELFADJ(float, float, float, ssyev, RowMajor, LAPACK_ROW_MAJOR) -EIGEN_LAPACKE_EIG_SELFADJ(dcomplex, lapack_complex_double, double, zheev, RowMajor, LAPACK_ROW_MAJOR) -EIGEN_LAPACKE_EIG_SELFADJ(scomplex, lapack_complex_float, float, cheev, RowMajor, LAPACK_ROW_MAJOR) +EIGEN_LAPACKE_EIG_SELFADJ(double, double, double, dsyev) +EIGEN_LAPACKE_EIG_SELFADJ(float, float, float, ssyev) +EIGEN_LAPACKE_EIG_SELFADJ(dcomplex, lapack_complex_double, double, zheev) +EIGEN_LAPACKE_EIG_SELFADJ(scomplex, lapack_complex_float, float, cheev) } // end namespace Eigen diff --git a/eigen/Eigen/src/Geometry/AngleAxis.h b/eigen/Eigen/src/Geometry/AngleAxis.h index 0af3c1b..83ee1be 100644 --- a/eigen/Eigen/src/Geometry/AngleAxis.h +++ b/eigen/Eigen/src/Geometry/AngleAxis.h @@ -178,7 +178,7 @@ EIGEN_DEVICE_FUNC AngleAxis<Scalar>& AngleAxis<Scalar>::operator=(const Quaterni if (n != Scalar(0)) { m_angle = Scalar(2)*atan2(n, abs(q.w())); - if(q.w() < 0) + if(q.w() < Scalar(0)) n = -n; m_axis = q.vec() / n; } diff --git a/eigen/Eigen/src/Geometry/Quaternion.h b/eigen/Eigen/src/Geometry/Quaternion.h index 3e5a9ba..c3fd8c3 100644 --- a/eigen/Eigen/src/Geometry/Quaternion.h +++ b/eigen/Eigen/src/Geometry/Quaternion.h @@ -43,6 +43,11 @@ class QuaternionBase : public RotationBase<Derived, 3> typedef typename internal::traits<Derived>::Scalar Scalar; typedef typename NumTraits<Scalar>::Real RealScalar; typedef typename internal::traits<Derived>::Coefficients Coefficients; + typedef typename Coefficients::CoeffReturnType CoeffReturnType; + typedef typename internal::conditional<bool(internal::traits<Derived>::Flags&LvalueBit), + Scalar&, CoeffReturnType>::type NonConstCoeffReturnType; + + enum { Flags = Eigen::internal::traits<Derived>::Flags }; @@ -58,22 +63,22 @@ class QuaternionBase : public RotationBase<Derived, 3> /** \returns the \c x coefficient */ - EIGEN_DEVICE_FUNC inline Scalar x() const { return this->derived().coeffs().coeff(0); } + EIGEN_DEVICE_FUNC inline CoeffReturnType x() const { return this->derived().coeffs().coeff(0); } /** \returns the \c y coefficient */ - EIGEN_DEVICE_FUNC inline Scalar y() const { return this->derived().coeffs().coeff(1); } + EIGEN_DEVICE_FUNC inline CoeffReturnType y() const { return this->derived().coeffs().coeff(1); } /** \returns the \c z coefficient */ - EIGEN_DEVICE_FUNC inline Scalar z() const { return this->derived().coeffs().coeff(2); } + EIGEN_DEVICE_FUNC inline CoeffReturnType z() const { return this->derived().coeffs().coeff(2); } /** \returns the \c w coefficient */ - EIGEN_DEVICE_FUNC inline Scalar w() const { return this->derived().coeffs().coeff(3); } - - /** \returns a reference to the \c x coefficient */ - EIGEN_DEVICE_FUNC inline Scalar& x() { return this->derived().coeffs().coeffRef(0); } - /** \returns a reference to the \c y coefficient */ - EIGEN_DEVICE_FUNC inline Scalar& y() { return this->derived().coeffs().coeffRef(1); } - /** \returns a reference to the \c z coefficient */ - EIGEN_DEVICE_FUNC inline Scalar& z() { return this->derived().coeffs().coeffRef(2); } - /** \returns a reference to the \c w coefficient */ - EIGEN_DEVICE_FUNC inline Scalar& w() { return this->derived().coeffs().coeffRef(3); } + EIGEN_DEVICE_FUNC inline CoeffReturnType w() const { return this->derived().coeffs().coeff(3); } + + /** \returns a reference to the \c x coefficient (if Derived is a non-const lvalue) */ + EIGEN_DEVICE_FUNC inline NonConstCoeffReturnType x() { return this->derived().coeffs().x(); } + /** \returns a reference to the \c y coefficient (if Derived is a non-const lvalue) */ + EIGEN_DEVICE_FUNC inline NonConstCoeffReturnType y() { return this->derived().coeffs().y(); } + /** \returns a reference to the \c z coefficient (if Derived is a non-const lvalue) */ + EIGEN_DEVICE_FUNC inline NonConstCoeffReturnType z() { return this->derived().coeffs().z(); } + /** \returns a reference to the \c w coefficient (if Derived is a non-const lvalue) */ + EIGEN_DEVICE_FUNC inline NonConstCoeffReturnType w() { return this->derived().coeffs().w(); } /** \returns a read-only vector expression of the imaginary part (x,y,z) */ EIGEN_DEVICE_FUNC inline const VectorBlock<const Coefficients,3> vec() const { return coeffs().template head<3>(); } diff --git a/eigen/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h b/eigen/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h index facdaf8..f66c846 100644 --- a/eigen/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h +++ b/eigen/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h @@ -168,7 +168,7 @@ class LeastSquareDiagonalPreconditioner : public DiagonalPreconditioner<_Scalar> { for(Index j=0; j<mat.outerSize(); ++j) { - RealScalar sum = mat.innerVector(j).squaredNorm(); + RealScalar sum = mat.col(j).squaredNorm(); if(sum>RealScalar(0)) m_invdiag(j) = RealScalar(1)/sum; else diff --git a/eigen/Eigen/src/Jacobi/Jacobi.h b/eigen/Eigen/src/Jacobi/Jacobi.h index c30326e..437e666 100644 --- a/eigen/Eigen/src/Jacobi/Jacobi.h +++ b/eigen/Eigen/src/Jacobi/Jacobi.h @@ -298,61 +298,119 @@ inline void MatrixBase<Derived>::applyOnTheRight(Index p, Index q, const JacobiR } namespace internal { -template<typename VectorX, typename VectorY, typename OtherScalar> -void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(DenseBase<VectorX>& xpr_x, DenseBase<VectorY>& xpr_y, const JacobiRotation<OtherScalar>& j) + +template<typename Scalar, typename OtherScalar, + int SizeAtCompileTime, int MinAlignment, bool Vectorizable> +struct apply_rotation_in_the_plane_selector { - typedef typename VectorX::Scalar Scalar; - enum { - PacketSize = packet_traits<Scalar>::size, - OtherPacketSize = packet_traits<OtherScalar>::size - }; - typedef typename packet_traits<Scalar>::type Packet; - typedef typename packet_traits<OtherScalar>::type OtherPacket; - eigen_assert(xpr_x.size() == xpr_y.size()); - Index size = xpr_x.size(); - Index incrx = xpr_x.derived().innerStride(); - Index incry = xpr_y.derived().innerStride(); + static inline void run(Scalar *x, Index incrx, Scalar *y, Index incry, Index size, OtherScalar c, OtherScalar s) + { + for(Index i=0; i<size; ++i) + { + Scalar xi = *x; + Scalar yi = *y; + *x = c * xi + numext::conj(s) * yi; + *y = -s * xi + numext::conj(c) * yi; + x += incrx; + y += incry; + } + } +}; - Scalar* EIGEN_RESTRICT x = &xpr_x.derived().coeffRef(0); - Scalar* EIGEN_RESTRICT y = &xpr_y.derived().coeffRef(0); - - OtherScalar c = j.c(); - OtherScalar s = j.s(); - if (c==OtherScalar(1) && s==OtherScalar(0)) - return; +template<typename Scalar, typename OtherScalar, + int SizeAtCompileTime, int MinAlignment> +struct apply_rotation_in_the_plane_selector<Scalar,OtherScalar,SizeAtCompileTime,MinAlignment,true /* vectorizable */> +{ + static inline void run(Scalar *x, Index incrx, Scalar *y, Index incry, Index size, OtherScalar c, OtherScalar s) + { + enum { + PacketSize = packet_traits<Scalar>::size, + OtherPacketSize = packet_traits<OtherScalar>::size + }; + typedef typename packet_traits<Scalar>::type Packet; + typedef typename packet_traits<OtherScalar>::type OtherPacket; + + /*** dynamic-size vectorized paths ***/ + if(SizeAtCompileTime == Dynamic && ((incrx==1 && incry==1) || PacketSize == 1)) + { + // both vectors are sequentially stored in memory => vectorization + enum { Peeling = 2 }; - /*** dynamic-size vectorized paths ***/ + Index alignedStart = internal::first_default_aligned(y, size); + Index alignedEnd = alignedStart + ((size-alignedStart)/PacketSize)*PacketSize; - if(VectorX::SizeAtCompileTime == Dynamic && - (VectorX::Flags & VectorY::Flags & PacketAccessBit) && - (PacketSize == OtherPacketSize) && - ((incrx==1 && incry==1) || PacketSize == 1)) - { - // both vectors are sequentially stored in memory => vectorization - enum { Peeling = 2 }; + const OtherPacket pc = pset1<OtherPacket>(c); + const OtherPacket ps = pset1<OtherPacket>(s); + conj_helper<OtherPacket,Packet,NumTraits<OtherScalar>::IsComplex,false> pcj; + conj_helper<OtherPacket,Packet,false,false> pm; - Index alignedStart = internal::first_default_aligned(y, size); - Index alignedEnd = alignedStart + ((size-alignedStart)/PacketSize)*PacketSize; + for(Index i=0; i<alignedStart; ++i) + { + Scalar xi = x[i]; + Scalar yi = y[i]; + x[i] = c * xi + numext::conj(s) * yi; + y[i] = -s * xi + numext::conj(c) * yi; + } - const OtherPacket pc = pset1<OtherPacket>(c); - const OtherPacket ps = pset1<OtherPacket>(s); - conj_helper<OtherPacket,Packet,NumTraits<OtherScalar>::IsComplex,false> pcj; - conj_helper<OtherPacket,Packet,false,false> pm; + Scalar* EIGEN_RESTRICT px = x + alignedStart; + Scalar* EIGEN_RESTRICT py = y + alignedStart; - for(Index i=0; i<alignedStart; ++i) - { - Scalar xi = x[i]; - Scalar yi = y[i]; - x[i] = c * xi + numext::conj(s) * yi; - y[i] = -s * xi + numext::conj(c) * yi; - } + if(internal::first_default_aligned(x, size)==alignedStart) + { + for(Index i=alignedStart; i<alignedEnd; i+=PacketSize) + { + Packet xi = pload<Packet>(px); + Packet yi = pload<Packet>(py); + pstore(px, padd(pm.pmul(pc,xi),pcj.pmul(ps,yi))); + pstore(py, psub(pcj.pmul(pc,yi),pm.pmul(ps,xi))); + px += PacketSize; + py += PacketSize; + } + } + else + { + Index peelingEnd = alignedStart + ((size-alignedStart)/(Peeling*PacketSize))*(Peeling*PacketSize); + for(Index i=alignedStart; i<peelingEnd; i+=Peeling*PacketSize) + { + Packet xi = ploadu<Packet>(px); + Packet xi1 = ploadu<Packet>(px+PacketSize); + Packet yi = pload <Packet>(py); + Packet yi1 = pload <Packet>(py+PacketSize); + pstoreu(px, padd(pm.pmul(pc,xi),pcj.pmul(ps,yi))); + pstoreu(px+PacketSize, padd(pm.pmul(pc,xi1),pcj.pmul(ps,yi1))); + pstore (py, psub(pcj.pmul(pc,yi),pm.pmul(ps,xi))); + pstore (py+PacketSize, psub(pcj.pmul(pc,yi1),pm.pmul(ps,xi1))); + px += Peeling*PacketSize; + py += Peeling*PacketSize; + } + if(alignedEnd!=peelingEnd) + { + Packet xi = ploadu<Packet>(x+peelingEnd); + Packet yi = pload <Packet>(y+peelingEnd); + pstoreu(x+peelingEnd, padd(pm.pmul(pc,xi),pcj.pmul(ps,yi))); + pstore (y+peelingEnd, psub(pcj.pmul(pc,yi),pm.pmul(ps,xi))); + } + } - Scalar* EIGEN_RESTRICT px = x + alignedStart; - Scalar* EIGEN_RESTRICT py = y + alignedStart; + for(Index i=alignedEnd; i<size; ++i) + { + Scalar xi = x[i]; + Scalar yi = y[i]; + x[i] = c * xi + numext::conj(s) * yi; + y[i] = -s * xi + numext::conj(c) * yi; + } + } - if(internal::first_default_aligned(x, size)==alignedStart) + /*** fixed-size vectorized path ***/ + else if(SizeAtCompileTime != Dynamic && MinAlignment>0) // FIXME should be compared to the required alignment { - for(Index i=alignedStart; i<alignedEnd; i+=PacketSize) + const OtherPacket pc = pset1<OtherPacket>(c); + const OtherPacket ps = pset1<OtherPacket>(s); + conj_helper<OtherPacket,Packet,NumTraits<OtherPacket>::IsComplex,false> pcj; + conj_helper<OtherPacket,Packet,false,false> pm; + Scalar* EIGEN_RESTRICT px = x; + Scalar* EIGEN_RESTRICT py = y; + for(Index i=0; i<size; i+=PacketSize) { Packet xi = pload<Packet>(px); Packet yi = pload<Packet>(py); @@ -362,76 +420,40 @@ void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(DenseBase<VectorX>& xpr_x py += PacketSize; } } - else - { - Index peelingEnd = alignedStart + ((size-alignedStart)/(Peeling*PacketSize))*(Peeling*PacketSize); - for(Index i=alignedStart; i<peelingEnd; i+=Peeling*PacketSize) - { - Packet xi = ploadu<Packet>(px); - Packet xi1 = ploadu<Packet>(px+PacketSize); - Packet yi = pload <Packet>(py); - Packet yi1 = pload <Packet>(py+PacketSize); - pstoreu(px, padd(pm.pmul(pc,xi),pcj.pmul(ps,yi))); - pstoreu(px+PacketSize, padd(pm.pmul(pc,xi1),pcj.pmul(ps,yi1))); - pstore (py, psub(pcj.pmul(pc,yi),pm.pmul(ps,xi))); - pstore (py+PacketSize, psub(pcj.pmul(pc,yi1),pm.pmul(ps,xi1))); - px += Peeling*PacketSize; - py += Peeling*PacketSize; - } - if(alignedEnd!=peelingEnd) - { - Packet xi = ploadu<Packet>(x+peelingEnd); - Packet yi = pload <Packet>(y+peelingEnd); - pstoreu(x+peelingEnd, padd(pm.pmul(pc,xi),pcj.pmul(ps,yi))); - pstore (y+peelingEnd, psub(pcj.pmul(pc,yi),pm.pmul(ps,xi))); - } - } - for(Index i=alignedEnd; i<size; ++i) + /*** non-vectorized path ***/ + else { - Scalar xi = x[i]; - Scalar yi = y[i]; - x[i] = c * xi + numext::conj(s) * yi; - y[i] = -s * xi + numext::conj(c) * yi; + apply_rotation_in_the_plane_selector<Scalar,OtherScalar,SizeAtCompileTime,MinAlignment,false>::run(x,incrx,y,incry,size,c,s); } } +}; - /*** fixed-size vectorized path ***/ - else if(VectorX::SizeAtCompileTime != Dynamic && - (VectorX::Flags & VectorY::Flags & PacketAccessBit) && - (PacketSize == OtherPacketSize) && - (EIGEN_PLAIN_ENUM_MIN(evaluator<VectorX>::Alignment, evaluator<VectorY>::Alignment)>0)) // FIXME should be compared to the required alignment - { - const OtherPacket pc = pset1<OtherPacket>(c); - const OtherPacket ps = pset1<OtherPacket>(s); - conj_helper<OtherPacket,Packet,NumTraits<OtherPacket>::IsComplex,false> pcj; - conj_helper<OtherPacket,Packet,false,false> pm; - Scalar* EIGEN_RESTRICT px = x; - Scalar* EIGEN_RESTRICT py = y; - for(Index i=0; i<size; i+=PacketSize) - { - Packet xi = pload<Packet>(px); - Packet yi = pload<Packet>(py); - pstore(px, padd(pm.pmul(pc,xi),pcj.pmul(ps,yi))); - pstore(py, psub(pcj.pmul(pc,yi),pm.pmul(ps,xi))); - px += PacketSize; - py += PacketSize; - } - } +template<typename VectorX, typename VectorY, typename OtherScalar> +void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(DenseBase<VectorX>& xpr_x, DenseBase<VectorY>& xpr_y, const JacobiRotation<OtherScalar>& j) +{ + typedef typename VectorX::Scalar Scalar; + const bool Vectorizable = (VectorX::Flags & VectorY::Flags & PacketAccessBit) + && (int(packet_traits<Scalar>::size) == int(packet_traits<OtherScalar>::size)); - /*** non-vectorized path ***/ - else - { - for(Index i=0; i<size; ++i) - { - Scalar xi = *x; - Scalar yi = *y; - *x = c * xi + numext::conj(s) * yi; - *y = -s * xi + numext::conj(c) * yi; - x += incrx; - y += incry; - } - } + eigen_assert(xpr_x.size() == xpr_y.size()); + Index size = xpr_x.size(); + Index incrx = xpr_x.derived().innerStride(); + Index incry = xpr_y.derived().innerStride(); + + Scalar* EIGEN_RESTRICT x = &xpr_x.derived().coeffRef(0); + Scalar* EIGEN_RESTRICT y = &xpr_y.derived().coeffRef(0); + + OtherScalar c = j.c(); + OtherScalar s = j.s(); + if (c==OtherScalar(1) && s==OtherScalar(0)) + return; + + apply_rotation_in_the_plane_selector< + Scalar,OtherScalar, + VectorX::SizeAtCompileTime, + EIGEN_PLAIN_ENUM_MIN(evaluator<VectorX>::Alignment, evaluator<VectorY>::Alignment), + Vectorizable>::run(x,incrx,y,incry,size,c,s); } } // end namespace internal diff --git a/eigen/Eigen/src/LU/InverseImpl.h b/eigen/Eigen/src/LU/InverseImpl.h index 018f99b..f49f233 100644 --- a/eigen/Eigen/src/LU/InverseImpl.h +++ b/eigen/Eigen/src/LU/InverseImpl.h @@ -404,7 +404,7 @@ inline void MatrixBase<Derived>::computeInverseWithCheck( const RealScalar& absDeterminantThreshold ) const { - RealScalar determinant; + Scalar determinant; // i'd love to put some static assertions there, but SFINAE means that they have no effect... eigen_assert(rows() == cols()); computeInverseAndDetWithCheck(inverse,determinant,invertible,absDeterminantThreshold); diff --git a/eigen/Eigen/src/PaStiXSupport/PaStiXSupport.h b/eigen/Eigen/src/PaStiXSupport/PaStiXSupport.h index d2ebfd7..160d8a5 100644 --- a/eigen/Eigen/src/PaStiXSupport/PaStiXSupport.h +++ b/eigen/Eigen/src/PaStiXSupport/PaStiXSupport.h @@ -64,28 +64,28 @@ namespace internal typedef typename _MatrixType::StorageIndex StorageIndex; }; - void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, float *vals, int *perm, int * invp, float *x, int nbrhs, int *iparm, double *dparm) + inline void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, float *vals, int *perm, int * invp, float *x, int nbrhs, int *iparm, double *dparm) { if (n == 0) { ptr = NULL; idx = NULL; vals = NULL; } if (nbrhs == 0) {x = NULL; nbrhs=1;} s_pastix(pastix_data, pastix_comm, n, ptr, idx, vals, perm, invp, x, nbrhs, iparm, dparm); } - void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, double *vals, int *perm, int * invp, double *x, int nbrhs, int *iparm, double *dparm) + inline void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, double *vals, int *perm, int * invp, double *x, int nbrhs, int *iparm, double *dparm) { if (n == 0) { ptr = NULL; idx = NULL; vals = NULL; } if (nbrhs == 0) {x = NULL; nbrhs=1;} d_pastix(pastix_data, pastix_comm, n, ptr, idx, vals, perm, invp, x, nbrhs, iparm, dparm); } - void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, std::complex<float> *vals, int *perm, int * invp, std::complex<float> *x, int nbrhs, int *iparm, double *dparm) + inline void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, std::complex<float> *vals, int *perm, int * invp, std::complex<float> *x, int nbrhs, int *iparm, double *dparm) { if (n == 0) { ptr = NULL; idx = NULL; vals = NULL; } if (nbrhs == 0) {x = NULL; nbrhs=1;} c_pastix(pastix_data, pastix_comm, n, ptr, idx, reinterpret_cast<PASTIX_COMPLEX*>(vals), perm, invp, reinterpret_cast<PASTIX_COMPLEX*>(x), nbrhs, iparm, dparm); } - void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, std::complex<double> *vals, int *perm, int * invp, std::complex<double> *x, int nbrhs, int *iparm, double *dparm) + inline void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, std::complex<double> *vals, int *perm, int * invp, std::complex<double> *x, int nbrhs, int *iparm, double *dparm) { if (n == 0) { ptr = NULL; idx = NULL; vals = NULL; } if (nbrhs == 0) {x = NULL; nbrhs=1;} diff --git a/eigen/Eigen/src/SVD/BDCSVD.h b/eigen/Eigen/src/SVD/BDCSVD.h index d7a4271..1134d66 100644 --- a/eigen/Eigen/src/SVD/BDCSVD.h +++ b/eigen/Eigen/src/SVD/BDCSVD.h @@ -11,7 +11,7 @@ // Copyright (C) 2013 Jean Ceccato <jean.ceccato@ensimag.fr> // Copyright (C) 2013 Pierre Zoppitelli <pierre.zoppitelli@ensimag.fr> // Copyright (C) 2013 Jitse Niesen <jitse@maths.leeds.ac.uk> -// Copyright (C) 2014-2016 Gael Guennebaud <gael.guennebaud@inria.fr> +// Copyright (C) 2014-2017 Gael Guennebaud <gael.guennebaud@inria.fr> // // 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 @@ -696,7 +696,9 @@ typename BDCSVD<MatrixType>::RealScalar BDCSVD<MatrixType>::secularEq(RealScalar for(Index i=0; i<m; ++i) { Index j = perm(i); - res += numext::abs2(col0(j)) / ((diagShifted(j) - mu) * (diag(j) + shift + mu)); + // The following expression could be rewritten to involve only a single division, + // but this would make the expression more sensitive to overflow. + res += (col0(j) / (diagShifted(j) - mu)) * (col0(j) / (diag(j) + shift + mu)); } return res; @@ -708,9 +710,12 @@ void BDCSVD<MatrixType>::computeSingVals(const ArrayRef& col0, const ArrayRef& d { using std::abs; using std::swap; + using std::sqrt; Index n = col0.size(); Index actual_n = n; + // Note that here actual_n is computed based on col0(i)==0 instead of diag(i)==0 as above + // because 1) we have diag(i)==0 => col0(i)==0 and 2) if col0(i)==0, then diag(i) is already a singular value. while(actual_n>1 && col0(actual_n-1)==Literal(0)) --actual_n; for (Index k = 0; k < n; ++k) @@ -732,7 +737,9 @@ void BDCSVD<MatrixType>::computeSingVals(const ArrayRef& col0, const ArrayRef& d right = (diag(actual_n-1) + col0.matrix().norm()); else { - // Skip deflated singular values + // Skip deflated singular values, + // recall that at this stage we assume that z[j]!=0 and all entries for which z[j]==0 have been put aside. + // This should be equivalent to using perm[] Index l = k+1; while(col0(l)==Literal(0)) { ++l; eigen_internal_assert(l<actual_n); } right = diag(l); @@ -818,15 +825,23 @@ void BDCSVD<MatrixType>::computeSingVals(const ArrayRef& col0, const ArrayRef& d RealScalar leftShifted, rightShifted; if (shift == left) { - leftShifted = (std::numeric_limits<RealScalar>::min)(); + // to avoid overflow, we must have mu > max(real_min, |z(k)|/sqrt(real_max)), + // the factor 2 is to be more conservative + leftShifted = numext::maxi<RealScalar>( (std::numeric_limits<RealScalar>::min)(), Literal(2) * abs(col0(k)) / sqrt((std::numeric_limits<RealScalar>::max)()) ); + + // check that we did it right: + eigen_internal_assert( (numext::isfinite)( (col0(k)/leftShifted)*(col0(k)/(diag(k)+shift+leftShifted)) ) ); // I don't understand why the case k==0 would be special there: - // if (k == 0) rightShifted = right - left; else - rightShifted = (k==actual_n-1) ? right : ((right - left) * RealScalar(0.6)); // theoretically we can take 0.5, but let's be safe + // if (k == 0) rightShifted = right - left; else + rightShifted = (k==actual_n-1) ? right : ((right - left) * RealScalar(0.51)); // theoretically we can take 0.5, but let's be safe } else { - leftShifted = -(right - left) * RealScalar(0.6); - rightShifted = -(std::numeric_limits<RealScalar>::min)(); + leftShifted = -(right - left) * RealScalar(0.51); + if(k+1<n) + rightShifted = -numext::maxi<RealScalar>( (std::numeric_limits<RealScalar>::min)(), abs(col0(k+1)) / sqrt((std::numeric_limits<RealScalar>::max)()) ); + else + rightShifted = -(std::numeric_limits<RealScalar>::min)(); } RealScalar fLeft = secularEq(leftShifted, col0, diag, perm, diagShifted, shift); @@ -980,7 +995,7 @@ void BDCSVD<MatrixType>::deflation43(Index firstCol, Index shift, Index i, Index Index start = firstCol + shift; RealScalar c = m_computed(start, start); RealScalar s = m_computed(start+i, start); - RealScalar r = sqrt(numext::abs2(c) + numext::abs2(s)); + RealScalar r = numext::hypot(c,s); if (r == Literal(0)) { m_computed(start+i, start+i) = Literal(0); diff --git a/eigen/Eigen/src/SVD/JacobiSVD_LAPACKE.h b/eigen/Eigen/src/SVD/JacobiSVD_LAPACKE.h index 5027215..ff0516f 100644 --- a/eigen/Eigen/src/SVD/JacobiSVD_LAPACKE.h +++ b/eigen/Eigen/src/SVD/JacobiSVD_LAPACKE.h @@ -61,9 +61,10 @@ JacobiSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, ColPiv u = (LAPACKE_TYPE*)m_matrixU.data(); \ } else { ldu=1; u=&dummy; }\ MatrixType localV; \ - ldvt = (m_computeFullV) ? internal::convert_index<lapack_int>(m_cols) : (m_computeThinV) ? internal::convert_index<lapack_int>(m_diagSize) : 1; \ + lapack_int vt_rows = (m_computeFullV) ? internal::convert_index<lapack_int>(m_cols) : (m_computeThinV) ? internal::convert_index<lapack_int>(m_diagSize) : 1; \ if (computeV()) { \ - localV.resize(ldvt, m_cols); \ + localV.resize(vt_rows, m_cols); \ + ldvt = internal::convert_index<lapack_int>(localV.outerStride()); \ vt = (LAPACKE_TYPE*)localV.data(); \ } else { ldvt=1; vt=&dummy; }\ Matrix<LAPACKE_RTYPE, Dynamic, Dynamic> superb; superb.resize(m_diagSize, 1); \ diff --git a/eigen/Eigen/src/SparseCore/AmbiVector.h b/eigen/Eigen/src/SparseCore/AmbiVector.h index 8a5cc91..e0295f2 100644 --- a/eigen/Eigen/src/SparseCore/AmbiVector.h +++ b/eigen/Eigen/src/SparseCore/AmbiVector.h @@ -94,7 +94,7 @@ class AmbiVector Index allocSize = m_allocatedElements * sizeof(ListEl); allocSize = (allocSize + sizeof(Scalar) - 1)/sizeof(Scalar); Scalar* newBuffer = new Scalar[allocSize]; - memcpy(newBuffer, m_buffer, copyElements * sizeof(ListEl)); + std::memcpy(newBuffer, m_buffer, copyElements * sizeof(ListEl)); delete[] m_buffer; m_buffer = newBuffer; } diff --git a/eigen/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h b/eigen/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h index 492eb0a..9db119b 100644 --- a/eigen/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h +++ b/eigen/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h @@ -17,7 +17,9 @@ namespace internal { template<typename Lhs, typename Rhs, typename ResultType> static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res, bool sortedInsertion = false) { - typedef typename remove_all<Lhs>::type::Scalar Scalar; + typedef typename remove_all<Lhs>::type::Scalar LhsScalar; + typedef typename remove_all<Rhs>::type::Scalar RhsScalar; + typedef typename remove_all<ResultType>::type::Scalar ResScalar; // make sure to call innerSize/outerSize since we fake the storage order. Index rows = lhs.innerSize(); @@ -25,7 +27,7 @@ static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& r eigen_assert(lhs.outerSize() == rhs.innerSize()); ei_declare_aligned_stack_constructed_variable(bool, mask, rows, 0); - ei_declare_aligned_stack_constructed_variable(Scalar, values, rows, 0); + ei_declare_aligned_stack_constructed_variable(ResScalar, values, rows, 0); ei_declare_aligned_stack_constructed_variable(Index, indices, rows, 0); std::memset(mask,0,sizeof(bool)*rows); @@ -51,12 +53,12 @@ static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& r Index nnz = 0; for (typename evaluator<Rhs>::InnerIterator rhsIt(rhsEval, j); rhsIt; ++rhsIt) { - Scalar y = rhsIt.value(); + RhsScalar y = rhsIt.value(); Index k = rhsIt.index(); for (typename evaluator<Lhs>::InnerIterator lhsIt(lhsEval, k); lhsIt; ++lhsIt) { Index i = lhsIt.index(); - Scalar x = lhsIt.value(); + LhsScalar x = lhsIt.value(); if(!mask[i]) { mask[i] = true; @@ -166,11 +168,12 @@ struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,C { static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) { - typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::StorageIndex> RowMajorMatrix; - RowMajorMatrix rhsRow = rhs; - RowMajorMatrix resRow(lhs.rows(), rhs.cols()); - internal::conservative_sparse_sparse_product_impl<RowMajorMatrix,Lhs,RowMajorMatrix>(rhsRow, lhs, resRow); - res = resRow; + typedef SparseMatrix<typename Rhs::Scalar,RowMajor,typename ResultType::StorageIndex> RowMajorRhs; + typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::StorageIndex> RowMajorRes; + RowMajorRhs rhsRow = rhs; + RowMajorRes resRow(lhs.rows(), rhs.cols()); + internal::conservative_sparse_sparse_product_impl<RowMajorRhs,Lhs,RowMajorRes>(rhsRow, lhs, resRow); + res = resRow; } }; @@ -179,10 +182,11 @@ struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,R { static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) { - typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::StorageIndex> RowMajorMatrix; - RowMajorMatrix lhsRow = lhs; - RowMajorMatrix resRow(lhs.rows(), rhs.cols()); - internal::conservative_sparse_sparse_product_impl<Rhs,RowMajorMatrix,RowMajorMatrix>(rhs, lhsRow, resRow); + typedef SparseMatrix<typename Lhs::Scalar,RowMajor,typename ResultType::StorageIndex> RowMajorLhs; + typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename ResultType::StorageIndex> RowMajorRes; + RowMajorLhs lhsRow = lhs; + RowMajorRes resRow(lhs.rows(), rhs.cols()); + internal::conservative_sparse_sparse_product_impl<Rhs,RowMajorLhs,RowMajorRes>(rhs, lhsRow, resRow); res = resRow; } }; @@ -219,10 +223,11 @@ struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,C { static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) { - typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::StorageIndex> ColMajorMatrix; - ColMajorMatrix lhsCol = lhs; - ColMajorMatrix resCol(lhs.rows(), rhs.cols()); - internal::conservative_sparse_sparse_product_impl<ColMajorMatrix,Rhs,ColMajorMatrix>(lhsCol, rhs, resCol); + typedef SparseMatrix<typename Lhs::Scalar,ColMajor,typename ResultType::StorageIndex> ColMajorLhs; + typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::StorageIndex> ColMajorRes; + ColMajorLhs lhsCol = lhs; + ColMajorRes resCol(lhs.rows(), rhs.cols()); + internal::conservative_sparse_sparse_product_impl<ColMajorLhs,Rhs,ColMajorRes>(lhsCol, rhs, resCol); res = resCol; } }; @@ -232,10 +237,11 @@ struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,R { static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) { - typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::StorageIndex> ColMajorMatrix; - ColMajorMatrix rhsCol = rhs; - ColMajorMatrix resCol(lhs.rows(), rhs.cols()); - internal::conservative_sparse_sparse_product_impl<Lhs,ColMajorMatrix,ColMajorMatrix>(lhs, rhsCol, resCol); + typedef SparseMatrix<typename Rhs::Scalar,ColMajor,typename ResultType::StorageIndex> ColMajorRhs; + typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::StorageIndex> ColMajorRes; + ColMajorRhs rhsCol = rhs; + ColMajorRes resCol(lhs.rows(), rhs.cols()); + internal::conservative_sparse_sparse_product_impl<Lhs,ColMajorRhs,ColMajorRes>(lhs, rhsCol, resCol); res = resCol; } }; @@ -263,7 +269,8 @@ namespace internal { template<typename Lhs, typename Rhs, typename ResultType> static void sparse_sparse_to_dense_product_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res) { - typedef typename remove_all<Lhs>::type::Scalar Scalar; + typedef typename remove_all<Lhs>::type::Scalar LhsScalar; + typedef typename remove_all<Rhs>::type::Scalar RhsScalar; Index cols = rhs.outerSize(); eigen_assert(lhs.outerSize() == rhs.innerSize()); @@ -274,12 +281,12 @@ static void sparse_sparse_to_dense_product_impl(const Lhs& lhs, const Rhs& rhs, { for (typename evaluator<Rhs>::InnerIterator rhsIt(rhsEval, j); rhsIt; ++rhsIt) { - Scalar y = rhsIt.value(); + RhsScalar y = rhsIt.value(); Index k = rhsIt.index(); for (typename evaluator<Lhs>::InnerIterator lhsIt(lhsEval, k); lhsIt; ++lhsIt) { Index i = lhsIt.index(); - Scalar x = lhsIt.value(); + LhsScalar x = lhsIt.value(); res.coeffRef(i,j) += x * y; } } @@ -310,9 +317,9 @@ struct sparse_sparse_to_dense_product_selector<Lhs,Rhs,ResultType,RowMajor,ColMa { static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) { - typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::StorageIndex> ColMajorMatrix; - ColMajorMatrix lhsCol(lhs); - internal::sparse_sparse_to_dense_product_impl<ColMajorMatrix,Rhs,ResultType>(lhsCol, rhs, res); + typedef SparseMatrix<typename Lhs::Scalar,ColMajor,typename ResultType::StorageIndex> ColMajorLhs; + ColMajorLhs lhsCol(lhs); + internal::sparse_sparse_to_dense_product_impl<ColMajorLhs,Rhs,ResultType>(lhsCol, rhs, res); } }; @@ -321,9 +328,9 @@ struct sparse_sparse_to_dense_product_selector<Lhs,Rhs,ResultType,ColMajor,RowMa { static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res) { - typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::StorageIndex> ColMajorMatrix; - ColMajorMatrix rhsCol(rhs); - internal::sparse_sparse_to_dense_product_impl<Lhs,ColMajorMatrix,ResultType>(lhs, rhsCol, res); + typedef SparseMatrix<typename Rhs::Scalar,ColMajor,typename ResultType::StorageIndex> ColMajorRhs; + ColMajorRhs rhsCol(rhs); + internal::sparse_sparse_to_dense_product_impl<Lhs,ColMajorRhs,ResultType>(lhs, rhsCol, res); } }; diff --git a/eigen/Eigen/src/SparseCore/SparseSelfAdjointView.h b/eigen/Eigen/src/SparseCore/SparseSelfAdjointView.h index 5ab64f1..65611b3 100644 --- a/eigen/Eigen/src/SparseCore/SparseSelfAdjointView.h +++ b/eigen/Eigen/src/SparseCore/SparseSelfAdjointView.h @@ -311,7 +311,7 @@ inline void sparse_selfadjoint_time_dense_product(const SparseLhsType& lhs, cons while (i && i.index()<j) ++i; if(i && i.index()==j) { - res(j,k) += alpha * i.value() * rhs(j,k); + res.coeffRef(j,k) += alpha * i.value() * rhs.coeff(j,k); ++i; } } @@ -324,14 +324,14 @@ inline void sparse_selfadjoint_time_dense_product(const SparseLhsType& lhs, cons { LhsScalar lhs_ij = i.value(); if(!LhsIsRowMajor) lhs_ij = numext::conj(lhs_ij); - res_j += lhs_ij * rhs(i.index(),k); + res_j += lhs_ij * rhs.coeff(i.index(),k); res(i.index(),k) += numext::conj(lhs_ij) * rhs_j; } - res(j,k) += alpha * res_j; + res.coeffRef(j,k) += alpha * res_j; // handle diagonal coeff if (ProcessFirstHalf && i && (i.index()==j)) - res(j,k) += alpha * i.value() * rhs(j,k); + res.coeffRef(j,k) += alpha * i.value() * rhs.coeff(j,k); } } } diff --git a/eigen/Eigen/src/SparseCore/SparseSparseProductWithPruning.h b/eigen/Eigen/src/SparseCore/SparseSparseProductWithPruning.h index 21c4190..88820a4 100644 --- a/eigen/Eigen/src/SparseCore/SparseSparseProductWithPruning.h +++ b/eigen/Eigen/src/SparseCore/SparseSparseProductWithPruning.h @@ -21,7 +21,8 @@ static void sparse_sparse_product_with_pruning_impl(const Lhs& lhs, const Rhs& r { // return sparse_sparse_product_with_pruning_impl2(lhs,rhs,res); - typedef typename remove_all<Lhs>::type::Scalar Scalar; + typedef typename remove_all<Rhs>::type::Scalar RhsScalar; + typedef typename remove_all<ResultType>::type::Scalar ResScalar; typedef typename remove_all<Lhs>::type::StorageIndex StorageIndex; // make sure to call innerSize/outerSize since we fake the storage order. @@ -31,7 +32,7 @@ static void sparse_sparse_product_with_pruning_impl(const Lhs& lhs, const Rhs& r eigen_assert(lhs.outerSize() == rhs.innerSize()); // allocate a temporary buffer - AmbiVector<Scalar,StorageIndex> tempVector(rows); + AmbiVector<ResScalar,StorageIndex> tempVector(rows); // mimics a resizeByInnerOuter: if(ResultType::IsRowMajor) @@ -63,14 +64,14 @@ static void sparse_sparse_product_with_pruning_impl(const Lhs& lhs, const Rhs& r { // FIXME should be written like this: tmp += rhsIt.value() * lhs.col(rhsIt.index()) tempVector.restart(); - Scalar x = rhsIt.value(); + RhsScalar x = rhsIt.value(); for (typename evaluator<Lhs>::InnerIterator lhsIt(lhsEval, rhsIt.index()); lhsIt; ++lhsIt) { tempVector.coeffRef(lhsIt.index()) += lhsIt.value() * x; } } res.startVec(j); - for (typename AmbiVector<Scalar,StorageIndex>::Iterator it(tempVector,tolerance); it; ++it) + for (typename AmbiVector<ResScalar,StorageIndex>::Iterator it(tempVector,tolerance); it; ++it) res.insertBackByOuterInner(j,it.index()) = it.value(); } res.finalize(); @@ -85,7 +86,6 @@ struct sparse_sparse_product_with_pruning_selector; template<typename Lhs, typename Rhs, typename ResultType> struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,ColMajor,ColMajor,ColMajor> { - typedef typename traits<typename remove_all<Lhs>::type>::Scalar Scalar; typedef typename ResultType::RealScalar RealScalar; static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance) @@ -129,8 +129,8 @@ struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,RowMajor,R typedef typename ResultType::RealScalar RealScalar; static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance) { - typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename Lhs::StorageIndex> ColMajorMatrixLhs; - typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename Lhs::StorageIndex> ColMajorMatrixRhs; + typedef SparseMatrix<typename Lhs::Scalar,ColMajor,typename Lhs::StorageIndex> ColMajorMatrixLhs; + typedef SparseMatrix<typename Rhs::Scalar,ColMajor,typename Lhs::StorageIndex> ColMajorMatrixRhs; ColMajorMatrixLhs colLhs(lhs); ColMajorMatrixRhs colRhs(rhs); internal::sparse_sparse_product_with_pruning_impl<ColMajorMatrixLhs,ColMajorMatrixRhs,ResultType>(colLhs, colRhs, res, tolerance); @@ -149,7 +149,7 @@ struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,ColMajor,R typedef typename ResultType::RealScalar RealScalar; static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance) { - typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename Lhs::StorageIndex> RowMajorMatrixLhs; + typedef SparseMatrix<typename Lhs::Scalar,RowMajor,typename Lhs::StorageIndex> RowMajorMatrixLhs; RowMajorMatrixLhs rowLhs(lhs); sparse_sparse_product_with_pruning_selector<RowMajorMatrixLhs,Rhs,ResultType,RowMajor,RowMajor>(rowLhs,rhs,res,tolerance); } @@ -161,7 +161,7 @@ struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,RowMajor,C typedef typename ResultType::RealScalar RealScalar; static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance) { - typedef SparseMatrix<typename ResultType::Scalar,RowMajor,typename Lhs::StorageIndex> RowMajorMatrixRhs; + typedef SparseMatrix<typename Rhs::Scalar,RowMajor,typename Lhs::StorageIndex> RowMajorMatrixRhs; RowMajorMatrixRhs rowRhs(rhs); sparse_sparse_product_with_pruning_selector<Lhs,RowMajorMatrixRhs,ResultType,RowMajor,RowMajor,RowMajor>(lhs,rowRhs,res,tolerance); } @@ -173,7 +173,7 @@ struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,ColMajor,R typedef typename ResultType::RealScalar RealScalar; static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance) { - typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename Lhs::StorageIndex> ColMajorMatrixRhs; + typedef SparseMatrix<typename Rhs::Scalar,ColMajor,typename Lhs::StorageIndex> ColMajorMatrixRhs; ColMajorMatrixRhs colRhs(rhs); internal::sparse_sparse_product_with_pruning_impl<Lhs,ColMajorMatrixRhs,ResultType>(lhs, colRhs, res, tolerance); } @@ -185,7 +185,7 @@ struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,RowMajor,C typedef typename ResultType::RealScalar RealScalar; static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance) { - typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename Lhs::StorageIndex> ColMajorMatrixLhs; + typedef SparseMatrix<typename Lhs::Scalar,ColMajor,typename Lhs::StorageIndex> ColMajorMatrixLhs; ColMajorMatrixLhs colLhs(lhs); internal::sparse_sparse_product_with_pruning_impl<ColMajorMatrixLhs,Rhs,ResultType>(colLhs, rhs, res, tolerance); } diff --git a/eigen/Eigen/src/SparseQR/SparseQR.h b/eigen/Eigen/src/SparseQR/SparseQR.h index 2d4498b..7409fca 100644 --- a/eigen/Eigen/src/SparseQR/SparseQR.h +++ b/eigen/Eigen/src/SparseQR/SparseQR.h @@ -52,7 +52,7 @@ namespace internal { * rank-revealing permutations. Use colsPermutation() to get it. * * Q is the orthogonal matrix represented as products of Householder reflectors. - * Use matrixQ() to get an expression and matrixQ().transpose() to get the transpose. + * Use matrixQ() to get an expression and matrixQ().adjoint() to get the adjoint. * You can then apply it to a vector. * * R is the sparse triangular or trapezoidal matrix. The later occurs when A is rank-deficient. @@ -65,6 +65,7 @@ namespace internal { * \implsparsesolverconcept * * \warning The input sparse matrix A must be in compressed mode (see SparseMatrix::makeCompressed()). + * \warning For complex matrices matrixQ().transpose() will actually return the adjoint matrix. * */ template<typename _MatrixType, typename _OrderingType> @@ -196,9 +197,9 @@ class SparseQR : public SparseSolverBase<SparseQR<_MatrixType,_OrderingType> > Index rank = this->rank(); - // Compute Q^T * b; + // Compute Q^* * b; typename Dest::PlainObject y, b; - y = this->matrixQ().transpose() * B; + y = this->matrixQ().adjoint() * B; b = y; // Solve with the triangular matrix R @@ -604,7 +605,7 @@ struct SparseQR_QProduct : ReturnByValue<SparseQR_QProduct<SparseQRType, Derived // Get the references SparseQR_QProduct(const SparseQRType& qr, const Derived& other, bool transpose) : m_qr(qr),m_other(other),m_transpose(transpose) {} - inline Index rows() const { return m_transpose ? m_qr.rows() : m_qr.cols(); } + inline Index rows() const { return m_qr.matrixQ().rows(); } inline Index cols() const { return m_other.cols(); } // Assign to a vector @@ -632,7 +633,10 @@ struct SparseQR_QProduct : ReturnByValue<SparseQR_QProduct<SparseQRType, Derived } else { - eigen_assert(m_qr.m_Q.rows() == m_other.rows() && "Non conforming object sizes"); + eigen_assert(m_qr.matrixQ().cols() == m_other.rows() && "Non conforming object sizes"); + + res.conservativeResize(rows(), cols()); + // Compute res = Q * other column by column for(Index j = 0; j < res.cols(); j++) { @@ -641,7 +645,7 @@ struct SparseQR_QProduct : ReturnByValue<SparseQR_QProduct<SparseQRType, Derived Scalar tau = Scalar(0); tau = m_qr.m_Q.col(k).dot(res.col(j)); if(tau==Scalar(0)) continue; - tau = tau * m_qr.m_hcoeffs(k); + tau = tau * numext::conj(m_qr.m_hcoeffs(k)); res.col(j) -= tau * m_qr.m_Q.col(k); } } @@ -650,7 +654,7 @@ struct SparseQR_QProduct : ReturnByValue<SparseQR_QProduct<SparseQRType, Derived const SparseQRType& m_qr; const Derived& m_other; - bool m_transpose; + bool m_transpose; // TODO this actually means adjoint }; template<typename SparseQRType> @@ -668,13 +672,14 @@ struct SparseQRMatrixQReturnType : public EigenBase<SparseQRMatrixQReturnType<Sp { return SparseQR_QProduct<SparseQRType,Derived>(m_qr,other.derived(),false); } + // To use for operations with the adjoint of Q SparseQRMatrixQTransposeReturnType<SparseQRType> adjoint() const { return SparseQRMatrixQTransposeReturnType<SparseQRType>(m_qr); } inline Index rows() const { return m_qr.rows(); } - inline Index cols() const { return (std::min)(m_qr.rows(),m_qr.cols()); } - // To use for operations with the transpose of Q + inline Index cols() const { return m_qr.rows(); } + // To use for operations with the transpose of Q FIXME this is the same as adjoint at the moment SparseQRMatrixQTransposeReturnType<SparseQRType> transpose() const { return SparseQRMatrixQTransposeReturnType<SparseQRType>(m_qr); @@ -682,6 +687,7 @@ struct SparseQRMatrixQReturnType : public EigenBase<SparseQRMatrixQReturnType<Sp const SparseQRType& m_qr; }; +// TODO this actually represents the adjoint of Q template<typename SparseQRType> struct SparseQRMatrixQTransposeReturnType { @@ -712,7 +718,7 @@ struct Assignment<DstXprType, SparseQRMatrixQReturnType<SparseQRType>, internal: typedef typename DstXprType::StorageIndex StorageIndex; static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &/*func*/) { - typename DstXprType::PlainObject idMat(src.m_qr.rows(), src.m_qr.rows()); + typename DstXprType::PlainObject idMat(src.rows(), src.cols()); idMat.setIdentity(); // Sort the sparse householder reflectors if needed const_cast<SparseQRType *>(&src.m_qr)->_sort_matrix_Q(); |