summaryrefslogtreecommitdiff
path: root/runtimes/nn/depend/external/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix.h
diff options
context:
space:
mode:
Diffstat (limited to 'runtimes/nn/depend/external/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix.h')
-rw-r--r--runtimes/nn/depend/external/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix.h521
1 files changed, 521 insertions, 0 deletions
diff --git a/runtimes/nn/depend/external/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix.h b/runtimes/nn/depend/external/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix.h
new file mode 100644
index 000000000..da6f82abc
--- /dev/null
+++ b/runtimes/nn/depend/external/eigen/Eigen/src/Core/products/SelfadjointMatrixMatrix.h
@@ -0,0 +1,521 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SELFADJOINT_MATRIX_MATRIX_H
+#define EIGEN_SELFADJOINT_MATRIX_MATRIX_H
+
+namespace Eigen {
+
+namespace internal {
+
+// pack a selfadjoint block diagonal for use with the gebp_kernel
+template<typename Scalar, typename Index, int Pack1, int Pack2_dummy, int StorageOrder>
+struct symm_pack_lhs
+{
+ template<int BlockRows> inline
+ void pack(Scalar* blockA, const const_blas_data_mapper<Scalar,Index,StorageOrder>& lhs, Index cols, Index i, Index& count)
+ {
+ // normal copy
+ for(Index k=0; k<i; k++)
+ for(Index w=0; w<BlockRows; w++)
+ blockA[count++] = lhs(i+w,k); // normal
+ // symmetric copy
+ Index h = 0;
+ for(Index k=i; k<i+BlockRows; k++)
+ {
+ for(Index w=0; w<h; w++)
+ blockA[count++] = numext::conj(lhs(k, i+w)); // transposed
+
+ blockA[count++] = numext::real(lhs(k,k)); // real (diagonal)
+
+ for(Index w=h+1; w<BlockRows; w++)
+ blockA[count++] = lhs(i+w, k); // normal
+ ++h;
+ }
+ // transposed copy
+ for(Index k=i+BlockRows; k<cols; k++)
+ for(Index w=0; w<BlockRows; w++)
+ blockA[count++] = numext::conj(lhs(k, i+w)); // transposed
+ }
+ void operator()(Scalar* blockA, const Scalar* _lhs, Index lhsStride, Index cols, Index rows)
+ {
+ enum { PacketSize = packet_traits<Scalar>::size };
+ const_blas_data_mapper<Scalar,Index,StorageOrder> lhs(_lhs,lhsStride);
+ Index count = 0;
+ //Index peeled_mc3 = (rows/Pack1)*Pack1;
+
+ const Index peeled_mc3 = Pack1>=3*PacketSize ? (rows/(3*PacketSize))*(3*PacketSize) : 0;
+ const Index peeled_mc2 = Pack1>=2*PacketSize ? peeled_mc3+((rows-peeled_mc3)/(2*PacketSize))*(2*PacketSize) : 0;
+ const Index peeled_mc1 = Pack1>=1*PacketSize ? (rows/(1*PacketSize))*(1*PacketSize) : 0;
+
+ if(Pack1>=3*PacketSize)
+ for(Index i=0; i<peeled_mc3; i+=3*PacketSize)
+ pack<3*PacketSize>(blockA, lhs, cols, i, count);
+
+ if(Pack1>=2*PacketSize)
+ for(Index i=peeled_mc3; i<peeled_mc2; i+=2*PacketSize)
+ pack<2*PacketSize>(blockA, lhs, cols, i, count);
+
+ if(Pack1>=1*PacketSize)
+ for(Index i=peeled_mc2; i<peeled_mc1; i+=1*PacketSize)
+ pack<1*PacketSize>(blockA, lhs, cols, i, count);
+
+ // do the same with mr==1
+ for(Index i=peeled_mc1; i<rows; i++)
+ {
+ for(Index k=0; k<i; k++)
+ blockA[count++] = lhs(i, k); // normal
+
+ blockA[count++] = numext::real(lhs(i, i)); // real (diagonal)
+
+ for(Index k=i+1; k<cols; k++)
+ blockA[count++] = numext::conj(lhs(k, i)); // transposed
+ }
+ }
+};
+
+template<typename Scalar, typename Index, int nr, int StorageOrder>
+struct symm_pack_rhs
+{
+ enum { PacketSize = packet_traits<Scalar>::size };
+ void operator()(Scalar* blockB, const Scalar* _rhs, Index rhsStride, Index rows, Index cols, Index k2)
+ {
+ Index end_k = k2 + rows;
+ Index count = 0;
+ const_blas_data_mapper<Scalar,Index,StorageOrder> rhs(_rhs,rhsStride);
+ Index packet_cols8 = nr>=8 ? (cols/8) * 8 : 0;
+ Index packet_cols4 = nr>=4 ? (cols/4) * 4 : 0;
+
+ // first part: normal case
+ for(Index j2=0; j2<k2; j2+=nr)
+ {
+ for(Index k=k2; k<end_k; k++)
+ {
+ blockB[count+0] = rhs(k,j2+0);
+ blockB[count+1] = rhs(k,j2+1);
+ if (nr>=4)
+ {
+ blockB[count+2] = rhs(k,j2+2);
+ blockB[count+3] = rhs(k,j2+3);
+ }
+ if (nr>=8)
+ {
+ blockB[count+4] = rhs(k,j2+4);
+ blockB[count+5] = rhs(k,j2+5);
+ blockB[count+6] = rhs(k,j2+6);
+ blockB[count+7] = rhs(k,j2+7);
+ }
+ count += nr;
+ }
+ }
+
+ // second part: diagonal block
+ Index end8 = nr>=8 ? (std::min)(k2+rows,packet_cols8) : k2;
+ if(nr>=8)
+ {
+ for(Index j2=k2; j2<end8; j2+=8)
+ {
+ // again we can split vertically in three different parts (transpose, symmetric, normal)
+ // transpose
+ for(Index k=k2; k<j2; k++)
+ {
+ blockB[count+0] = numext::conj(rhs(j2+0,k));
+ blockB[count+1] = numext::conj(rhs(j2+1,k));
+ blockB[count+2] = numext::conj(rhs(j2+2,k));
+ blockB[count+3] = numext::conj(rhs(j2+3,k));
+ blockB[count+4] = numext::conj(rhs(j2+4,k));
+ blockB[count+5] = numext::conj(rhs(j2+5,k));
+ blockB[count+6] = numext::conj(rhs(j2+6,k));
+ blockB[count+7] = numext::conj(rhs(j2+7,k));
+ count += 8;
+ }
+ // symmetric
+ Index h = 0;
+ for(Index k=j2; k<j2+8; k++)
+ {
+ // normal
+ for (Index w=0 ; w<h; ++w)
+ blockB[count+w] = rhs(k,j2+w);
+
+ blockB[count+h] = numext::real(rhs(k,k));
+
+ // transpose
+ for (Index w=h+1 ; w<8; ++w)
+ blockB[count+w] = numext::conj(rhs(j2+w,k));
+ count += 8;
+ ++h;
+ }
+ // normal
+ for(Index k=j2+8; k<end_k; k++)
+ {
+ blockB[count+0] = rhs(k,j2+0);
+ blockB[count+1] = rhs(k,j2+1);
+ blockB[count+2] = rhs(k,j2+2);
+ blockB[count+3] = rhs(k,j2+3);
+ blockB[count+4] = rhs(k,j2+4);
+ blockB[count+5] = rhs(k,j2+5);
+ blockB[count+6] = rhs(k,j2+6);
+ blockB[count+7] = rhs(k,j2+7);
+ count += 8;
+ }
+ }
+ }
+ if(nr>=4)
+ {
+ for(Index j2=end8; j2<(std::min)(k2+rows,packet_cols4); j2+=4)
+ {
+ // again we can split vertically in three different parts (transpose, symmetric, normal)
+ // transpose
+ for(Index k=k2; k<j2; k++)
+ {
+ blockB[count+0] = numext::conj(rhs(j2+0,k));
+ blockB[count+1] = numext::conj(rhs(j2+1,k));
+ blockB[count+2] = numext::conj(rhs(j2+2,k));
+ blockB[count+3] = numext::conj(rhs(j2+3,k));
+ count += 4;
+ }
+ // symmetric
+ Index h = 0;
+ for(Index k=j2; k<j2+4; k++)
+ {
+ // normal
+ for (Index w=0 ; w<h; ++w)
+ blockB[count+w] = rhs(k,j2+w);
+
+ blockB[count+h] = numext::real(rhs(k,k));
+
+ // transpose
+ for (Index w=h+1 ; w<4; ++w)
+ blockB[count+w] = numext::conj(rhs(j2+w,k));
+ count += 4;
+ ++h;
+ }
+ // normal
+ for(Index k=j2+4; k<end_k; k++)
+ {
+ blockB[count+0] = rhs(k,j2+0);
+ blockB[count+1] = rhs(k,j2+1);
+ blockB[count+2] = rhs(k,j2+2);
+ blockB[count+3] = rhs(k,j2+3);
+ count += 4;
+ }
+ }
+ }
+
+ // third part: transposed
+ if(nr>=8)
+ {
+ for(Index j2=k2+rows; j2<packet_cols8; j2+=8)
+ {
+ for(Index k=k2; k<end_k; k++)
+ {
+ blockB[count+0] = numext::conj(rhs(j2+0,k));
+ blockB[count+1] = numext::conj(rhs(j2+1,k));
+ blockB[count+2] = numext::conj(rhs(j2+2,k));
+ blockB[count+3] = numext::conj(rhs(j2+3,k));
+ blockB[count+4] = numext::conj(rhs(j2+4,k));
+ blockB[count+5] = numext::conj(rhs(j2+5,k));
+ blockB[count+6] = numext::conj(rhs(j2+6,k));
+ blockB[count+7] = numext::conj(rhs(j2+7,k));
+ count += 8;
+ }
+ }
+ }
+ if(nr>=4)
+ {
+ for(Index j2=(std::max)(packet_cols8,k2+rows); j2<packet_cols4; j2+=4)
+ {
+ for(Index k=k2; k<end_k; k++)
+ {
+ blockB[count+0] = numext::conj(rhs(j2+0,k));
+ blockB[count+1] = numext::conj(rhs(j2+1,k));
+ blockB[count+2] = numext::conj(rhs(j2+2,k));
+ blockB[count+3] = numext::conj(rhs(j2+3,k));
+ count += 4;
+ }
+ }
+ }
+
+ // copy the remaining columns one at a time (=> the same with nr==1)
+ for(Index j2=packet_cols4; j2<cols; ++j2)
+ {
+ // transpose
+ Index half = (std::min)(end_k,j2);
+ for(Index k=k2; k<half; k++)
+ {
+ blockB[count] = numext::conj(rhs(j2,k));
+ count += 1;
+ }
+
+ if(half==j2 && half<k2+rows)
+ {
+ blockB[count] = numext::real(rhs(j2,j2));
+ count += 1;
+ }
+ else
+ half--;
+
+ // normal
+ for(Index k=half+1; k<k2+rows; k++)
+ {
+ blockB[count] = rhs(k,j2);
+ count += 1;
+ }
+ }
+ }
+};
+
+/* Optimized selfadjoint matrix * matrix (_SYMM) product built on top of
+ * the general matrix matrix product.
+ */
+template <typename Scalar, typename Index,
+ int LhsStorageOrder, bool LhsSelfAdjoint, bool ConjugateLhs,
+ int RhsStorageOrder, bool RhsSelfAdjoint, bool ConjugateRhs,
+ int ResStorageOrder>
+struct product_selfadjoint_matrix;
+
+template <typename Scalar, typename Index,
+ int LhsStorageOrder, bool LhsSelfAdjoint, bool ConjugateLhs,
+ int RhsStorageOrder, bool RhsSelfAdjoint, bool ConjugateRhs>
+struct product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,LhsSelfAdjoint,ConjugateLhs, RhsStorageOrder,RhsSelfAdjoint,ConjugateRhs,RowMajor>
+{
+
+ static EIGEN_STRONG_INLINE void run(
+ Index rows, Index cols,
+ const Scalar* lhs, Index lhsStride,
+ const Scalar* rhs, Index rhsStride,
+ Scalar* res, Index resStride,
+ const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking)
+ {
+ product_selfadjoint_matrix<Scalar, Index,
+ EIGEN_LOGICAL_XOR(RhsSelfAdjoint,RhsStorageOrder==RowMajor) ? ColMajor : RowMajor,
+ RhsSelfAdjoint, NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(RhsSelfAdjoint,ConjugateRhs),
+ EIGEN_LOGICAL_XOR(LhsSelfAdjoint,LhsStorageOrder==RowMajor) ? ColMajor : RowMajor,
+ LhsSelfAdjoint, NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(LhsSelfAdjoint,ConjugateLhs),
+ ColMajor>
+ ::run(cols, rows, rhs, rhsStride, lhs, lhsStride, res, resStride, alpha, blocking);
+ }
+};
+
+template <typename Scalar, typename Index,
+ int LhsStorageOrder, bool ConjugateLhs,
+ int RhsStorageOrder, bool ConjugateRhs>
+struct product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,true,ConjugateLhs, RhsStorageOrder,false,ConjugateRhs,ColMajor>
+{
+
+ static EIGEN_DONT_INLINE void run(
+ Index rows, Index cols,
+ const Scalar* _lhs, Index lhsStride,
+ const Scalar* _rhs, Index rhsStride,
+ Scalar* res, Index resStride,
+ const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking);
+};
+
+template <typename Scalar, typename Index,
+ int LhsStorageOrder, bool ConjugateLhs,
+ int RhsStorageOrder, bool ConjugateRhs>
+EIGEN_DONT_INLINE void product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,true,ConjugateLhs, RhsStorageOrder,false,ConjugateRhs,ColMajor>::run(
+ Index rows, Index cols,
+ const Scalar* _lhs, Index lhsStride,
+ const Scalar* _rhs, Index rhsStride,
+ Scalar* _res, Index resStride,
+ const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking)
+ {
+ Index size = rows;
+
+ typedef gebp_traits<Scalar,Scalar> Traits;
+
+ typedef const_blas_data_mapper<Scalar, Index, LhsStorageOrder> LhsMapper;
+ typedef const_blas_data_mapper<Scalar, Index, (LhsStorageOrder == RowMajor) ? ColMajor : RowMajor> LhsTransposeMapper;
+ typedef const_blas_data_mapper<Scalar, Index, RhsStorageOrder> RhsMapper;
+ typedef blas_data_mapper<typename Traits::ResScalar, Index, ColMajor> ResMapper;
+ LhsMapper lhs(_lhs,lhsStride);
+ LhsTransposeMapper lhs_transpose(_lhs,lhsStride);
+ RhsMapper rhs(_rhs,rhsStride);
+ ResMapper res(_res, resStride);
+
+ Index kc = blocking.kc(); // cache block size along the K direction
+ Index mc = (std::min)(rows,blocking.mc()); // cache block size along the M direction
+ // kc must be smaller than mc
+ kc = (std::min)(kc,mc);
+ std::size_t sizeA = kc*mc;
+ std::size_t sizeB = kc*cols;
+ ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA());
+ ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB());
+
+ gebp_kernel<Scalar, Scalar, Index, ResMapper, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel;
+ symm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
+ gemm_pack_rhs<Scalar, Index, RhsMapper, Traits::nr,RhsStorageOrder> pack_rhs;
+ gemm_pack_lhs<Scalar, Index, LhsTransposeMapper, Traits::mr, Traits::LhsProgress, LhsStorageOrder==RowMajor?ColMajor:RowMajor, true> pack_lhs_transposed;
+
+ for(Index k2=0; k2<size; k2+=kc)
+ {
+ const Index actual_kc = (std::min)(k2+kc,size)-k2;
+
+ // we have selected one row panel of rhs and one column panel of lhs
+ // pack rhs's panel into a sequential chunk of memory
+ // and expand each coeff to a constant packet for further reuse
+ pack_rhs(blockB, rhs.getSubMapper(k2,0), actual_kc, cols);
+
+ // the select lhs's panel has to be split in three different parts:
+ // 1 - the transposed panel above the diagonal block => transposed packed copy
+ // 2 - the diagonal block => special packed copy
+ // 3 - the panel below the diagonal block => generic packed copy
+ for(Index i2=0; i2<k2; i2+=mc)
+ {
+ const Index actual_mc = (std::min)(i2+mc,k2)-i2;
+ // transposed packed copy
+ pack_lhs_transposed(blockA, lhs_transpose.getSubMapper(i2, k2), actual_kc, actual_mc);
+
+ gebp_kernel(res.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc, cols, alpha);
+ }
+ // the block diagonal
+ {
+ const Index actual_mc = (std::min)(k2+kc,size)-k2;
+ // symmetric packed copy
+ pack_lhs(blockA, &lhs(k2,k2), lhsStride, actual_kc, actual_mc);
+
+ gebp_kernel(res.getSubMapper(k2, 0), blockA, blockB, actual_mc, actual_kc, cols, alpha);
+ }
+
+ for(Index i2=k2+kc; i2<size; i2+=mc)
+ {
+ const Index actual_mc = (std::min)(i2+mc,size)-i2;
+ gemm_pack_lhs<Scalar, Index, LhsMapper, Traits::mr, Traits::LhsProgress, LhsStorageOrder,false>()
+ (blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc);
+
+ gebp_kernel(res.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc, cols, alpha);
+ }
+ }
+ }
+
+// matrix * selfadjoint product
+template <typename Scalar, typename Index,
+ int LhsStorageOrder, bool ConjugateLhs,
+ int RhsStorageOrder, bool ConjugateRhs>
+struct product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,false,ConjugateLhs, RhsStorageOrder,true,ConjugateRhs,ColMajor>
+{
+
+ static EIGEN_DONT_INLINE void run(
+ Index rows, Index cols,
+ const Scalar* _lhs, Index lhsStride,
+ const Scalar* _rhs, Index rhsStride,
+ Scalar* res, Index resStride,
+ const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking);
+};
+
+template <typename Scalar, typename Index,
+ int LhsStorageOrder, bool ConjugateLhs,
+ int RhsStorageOrder, bool ConjugateRhs>
+EIGEN_DONT_INLINE void product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,false,ConjugateLhs, RhsStorageOrder,true,ConjugateRhs,ColMajor>::run(
+ Index rows, Index cols,
+ const Scalar* _lhs, Index lhsStride,
+ const Scalar* _rhs, Index rhsStride,
+ Scalar* _res, Index resStride,
+ const Scalar& alpha, level3_blocking<Scalar,Scalar>& blocking)
+ {
+ Index size = cols;
+
+ typedef gebp_traits<Scalar,Scalar> Traits;
+
+ typedef const_blas_data_mapper<Scalar, Index, LhsStorageOrder> LhsMapper;
+ typedef blas_data_mapper<typename Traits::ResScalar, Index, ColMajor> ResMapper;
+ LhsMapper lhs(_lhs,lhsStride);
+ ResMapper res(_res,resStride);
+
+ Index kc = blocking.kc(); // cache block size along the K direction
+ Index mc = (std::min)(rows,blocking.mc()); // cache block size along the M direction
+ std::size_t sizeA = kc*mc;
+ std::size_t sizeB = kc*cols;
+ ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA());
+ ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB());
+
+ gebp_kernel<Scalar, Scalar, Index, ResMapper, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel;
+ gemm_pack_lhs<Scalar, Index, LhsMapper, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
+ symm_pack_rhs<Scalar, Index, Traits::nr,RhsStorageOrder> pack_rhs;
+
+ for(Index k2=0; k2<size; k2+=kc)
+ {
+ const Index actual_kc = (std::min)(k2+kc,size)-k2;
+
+ pack_rhs(blockB, _rhs, rhsStride, actual_kc, cols, k2);
+
+ // => GEPP
+ for(Index i2=0; i2<rows; i2+=mc)
+ {
+ const Index actual_mc = (std::min)(i2+mc,rows)-i2;
+ pack_lhs(blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc);
+
+ gebp_kernel(res.getSubMapper(i2, 0), blockA, blockB, actual_mc, actual_kc, cols, alpha);
+ }
+ }
+ }
+
+} // end namespace internal
+
+/***************************************************************************
+* Wrapper to product_selfadjoint_matrix
+***************************************************************************/
+
+namespace internal {
+
+template<typename Lhs, int LhsMode, typename Rhs, int RhsMode>
+struct selfadjoint_product_impl<Lhs,LhsMode,false,Rhs,RhsMode,false>
+{
+ typedef typename Product<Lhs,Rhs>::Scalar Scalar;
+
+ typedef internal::blas_traits<Lhs> LhsBlasTraits;
+ typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
+ typedef internal::blas_traits<Rhs> RhsBlasTraits;
+ typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
+
+ enum {
+ LhsIsUpper = (LhsMode&(Upper|Lower))==Upper,
+ LhsIsSelfAdjoint = (LhsMode&SelfAdjoint)==SelfAdjoint,
+ RhsIsUpper = (RhsMode&(Upper|Lower))==Upper,
+ RhsIsSelfAdjoint = (RhsMode&SelfAdjoint)==SelfAdjoint
+ };
+
+ template<typename Dest>
+ static void run(Dest &dst, const Lhs &a_lhs, const Rhs &a_rhs, const Scalar& alpha)
+ {
+ eigen_assert(dst.rows()==a_lhs.rows() && dst.cols()==a_rhs.cols());
+
+ 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);
+
+ typedef internal::gemm_blocking_space<(Dest::Flags&RowMajorBit) ? RowMajor : ColMajor,Scalar,Scalar,
+ Lhs::MaxRowsAtCompileTime, Rhs::MaxColsAtCompileTime, Lhs::MaxColsAtCompileTime,1> BlockingType;
+
+ BlockingType blocking(lhs.rows(), rhs.cols(), lhs.cols(), 1, false);
+
+ internal::product_selfadjoint_matrix<Scalar, Index,
+ EIGEN_LOGICAL_XOR(LhsIsUpper,internal::traits<Lhs>::Flags &RowMajorBit) ? RowMajor : ColMajor, LhsIsSelfAdjoint,
+ NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(LhsIsUpper,bool(LhsBlasTraits::NeedToConjugate)),
+ EIGEN_LOGICAL_XOR(RhsIsUpper,internal::traits<Rhs>::Flags &RowMajorBit) ? RowMajor : ColMajor, RhsIsSelfAdjoint,
+ NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(RhsIsUpper,bool(RhsBlasTraits::NeedToConjugate)),
+ internal::traits<Dest>::Flags&RowMajorBit ? RowMajor : ColMajor>
+ ::run(
+ lhs.rows(), rhs.cols(), // sizes
+ &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info
+ &rhs.coeffRef(0,0), rhs.outerStride(), // rhs info
+ &dst.coeffRef(0,0), dst.outerStride(), // result info
+ actualAlpha, blocking // alpha
+ );
+ }
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_SELFADJOINT_MATRIX_MATRIX_H