mirror of
https://gitlab.com/libeigen/eigen.git
synced 2025-04-18 07:39:37 +08:00
Add BDCSVD_LAPACKE binding
This commit is contained in:
Melven Roehrig-Zoellner
Rasmus Munk Larsen
parent
03c9b4738c
commit
273f803846
@ -36,14 +36,17 @@
|
||||
#include "src/SVD/SVDBase.h"
|
||||
#include "src/SVD/JacobiSVD.h"
|
||||
#include "src/SVD/BDCSVD.h"
|
||||
#if defined(EIGEN_USE_LAPACKE) && !defined(EIGEN_USE_LAPACKE_STRICT)
|
||||
#ifdef EIGEN_USE_LAPACKE
|
||||
#ifdef EIGEN_USE_MKL
|
||||
#include "mkl_lapacke.h"
|
||||
#else
|
||||
#include "src/misc/lapacke.h"
|
||||
#endif
|
||||
#ifndef EIGEN_USE_LAPACKE_STRICT
|
||||
#include "src/SVD/JacobiSVD_LAPACKE.h"
|
||||
#endif
|
||||
#include "src/SVD/BDCSVD_LAPACKE.h"
|
||||
#endif
|
||||
|
||||
#include "src/Core/util/ReenableStupidWarnings.h"
|
||||
|
||||
|
||||
@ -236,7 +236,6 @@ public:
|
||||
}
|
||||
|
||||
private:
|
||||
void allocate(Index rows, Index cols, unsigned int computationOptions);
|
||||
BDCSVD& compute_impl(const MatrixType& matrix, unsigned int computationOptions);
|
||||
void divide(Index firstCol, Index lastCol, Index firstRowW, Index firstColW, Index shift);
|
||||
void computeSVDofM(Index firstCol, Index n, MatrixXr& U, VectorType& singVals, MatrixXr& V);
|
||||
@ -254,6 +253,7 @@ private:
|
||||
void computeBaseCase(SVDType& svd, Index n, Index firstCol, Index firstRowW, Index firstColW, Index shift);
|
||||
|
||||
protected:
|
||||
void allocate(Index rows, Index cols, unsigned int computationOptions);
|
||||
MatrixXr m_naiveU, m_naiveV;
|
||||
MatrixXr m_computed;
|
||||
Index m_nRec;
|
||||
|
||||
163
Eigen/src/SVD/BDCSVD_LAPACKE.h
Normal file
163
Eigen/src/SVD/BDCSVD_LAPACKE.h
Normal file
@ -0,0 +1,163 @@
|
||||
// This file is part of Eigen, a lightweight C++ template library
|
||||
// for linear algebra.
|
||||
//
|
||||
// Copyright (C) 2022 Melven Roehrig-Zoellner <Melven.Roehrig-Zoellner@DLR.de>
|
||||
// Copyright (c) 2011, Intel Corporation. All rights reserved.
|
||||
//
|
||||
// This file is based on the JacobiSVD_LAPACKE.h originally from Intel -
|
||||
// see license notice below:
|
||||
/*
|
||||
Redistribution and use in source and binary forms, with or without modification,
|
||||
are permitted provided that the following conditions are met:
|
||||
|
||||
* Redistributions of source code must retain the above copyright notice, this
|
||||
list of conditions and the following disclaimer.
|
||||
* Redistributions in binary form must reproduce the above copyright notice,
|
||||
this list of conditions and the following disclaimer in the documentation
|
||||
and/or other materials provided with the distribution.
|
||||
* Neither the name of Intel Corporation nor the names of its contributors may
|
||||
be used to endorse or promote products derived from this software without
|
||||
specific prior written permission.
|
||||
|
||||
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
|
||||
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
|
||||
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
|
||||
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
|
||||
ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
|
||||
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
|
||||
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
|
||||
ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
|
||||
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
|
||||
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
||||
|
||||
********************************************************************************
|
||||
* Content : Eigen bindings to LAPACKe
|
||||
* Singular Value Decomposition - SVD (divide and conquer variant)
|
||||
********************************************************************************
|
||||
*/
|
||||
#ifndef EIGEN_BDCSVD_LAPACKE_H
|
||||
#define EIGEN_BDCSVD_LAPACKE_H
|
||||
|
||||
namespace Eigen {
|
||||
|
||||
namespace internal {
|
||||
|
||||
namespace lapacke_helpers {
|
||||
|
||||
/** \internal Specialization for the data types supported by LAPACKe */
|
||||
|
||||
// defining a derived class to allow access to protected members
|
||||
template <typename MatrixType_, int Options>
|
||||
class BDCSVD_LAPACKE : public BDCSVD<MatrixType_, Options> {
|
||||
typedef BDCSVD<MatrixType_, Options> SVD;
|
||||
typedef typename SVD::MatrixType MatrixType;
|
||||
typedef typename SVD::Scalar Scalar;
|
||||
typedef typename SVD::RealScalar RealScalar;
|
||||
|
||||
public:
|
||||
// construct this by moving from a parent object
|
||||
BDCSVD_LAPACKE(SVD&& svd) : SVD(std::move(svd)) {}
|
||||
|
||||
void compute_impl_lapacke(const MatrixType& matrix, unsigned int computationOptions) {
|
||||
|
||||
SVD::allocate(matrix.rows(), matrix.cols(), computationOptions);
|
||||
|
||||
SVD::m_nonzeroSingularValues = SVD::m_diagSize;
|
||||
|
||||
// prepare arguments to ?gesdd
|
||||
const lapack_int matrix_order = lapack_storage_of(matrix);
|
||||
const char jobz = (SVD::m_computeFullU || SVD::m_computeFullV) ? 'A' : (SVD::m_computeThinU || SVD::m_computeThinV) ? 'S' : 'N';
|
||||
const lapack_int u_cols = (jobz == 'A') ? to_lapack(SVD::m_rows) : (jobz == 'S') ? to_lapack(SVD::m_diagSize) : 1;
|
||||
const lapack_int vt_rows = (jobz == 'A') ? to_lapack(SVD::m_cols) : (jobz == 'S') ? to_lapack(SVD::m_diagSize) : 1;
|
||||
lapack_int ldu, ldvt;
|
||||
Scalar *u, *vt, dummy;
|
||||
MatrixType localU;
|
||||
if (SVD::computeU() && !(SVD::m_computeThinU && SVD::m_computeFullV) ) {
|
||||
ldu = to_lapack(SVD::m_matrixU.outerStride());
|
||||
u = SVD::m_matrixU.data();
|
||||
} else if (SVD::computeV()) {
|
||||
localU.resize(SVD::m_rows, u_cols);
|
||||
ldu = to_lapack(localU.outerStride());
|
||||
u = localU.data();
|
||||
} else { ldu=1; u=&dummy; }
|
||||
MatrixType localV;
|
||||
if (SVD::computeU() || SVD::computeV()) {
|
||||
localV.resize(vt_rows, SVD::m_cols);
|
||||
ldvt = to_lapack(localV.outerStride());
|
||||
vt = localV.data();
|
||||
} else { ldvt=1; vt=&dummy; }
|
||||
MatrixType temp; temp = matrix;
|
||||
|
||||
// actual call to ?gesdd
|
||||
lapack_int info = gesdd( matrix_order, jobz, to_lapack(SVD::m_rows), to_lapack(SVD::m_cols),
|
||||
to_lapack(temp.data()), to_lapack(temp.outerStride()), (RealScalar*)SVD::m_singularValues.data(),
|
||||
to_lapack(u), ldu, to_lapack(vt), ldvt);
|
||||
|
||||
// Check the result of the LAPACK call
|
||||
if (info < 0 || !SVD::m_singularValues.allFinite()) {
|
||||
// this includes info == -4 => NaN entry in A
|
||||
SVD::m_info = InvalidInput;
|
||||
} else if (info > 0 ) {
|
||||
SVD::m_info = NoConvergence;
|
||||
} else {
|
||||
SVD::m_info = Success;
|
||||
if (SVD::m_computeThinU && SVD::m_computeFullV) {
|
||||
SVD::m_matrixU = localU.leftCols(SVD::m_matrixU.cols());
|
||||
}
|
||||
if (SVD::computeV()) {
|
||||
SVD::m_matrixV = localV.adjoint().leftCols(SVD::m_matrixV.cols());
|
||||
}
|
||||
}
|
||||
SVD::m_isInitialized = true;
|
||||
}
|
||||
};
|
||||
|
||||
template<typename MatrixType_, int Options>
|
||||
BDCSVD<MatrixType_, Options>& BDCSVD_wrapper(BDCSVD<MatrixType_, Options>& svd, const MatrixType_& matrix, int computationOptions)
|
||||
{
|
||||
// we need to move to the wrapper type and back
|
||||
BDCSVD_LAPACKE<MatrixType_, Options> tmpSvd(std::move(svd));
|
||||
tmpSvd.compute_impl_lapacke(matrix, computationOptions);
|
||||
svd = std::move(tmpSvd);
|
||||
return svd;
|
||||
}
|
||||
|
||||
} // end namespace lapacke_helpers
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
#define EIGEN_LAPACKE_SDD(EIGTYPE, EIGCOLROW, OPTIONS) \
|
||||
template<> inline \
|
||||
BDCSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, OPTIONS>& \
|
||||
BDCSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, OPTIONS>::compute_impl(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>& matrix, unsigned int computationOptions) {\
|
||||
return internal::lapacke_helpers::BDCSVD_wrapper(*this, matrix, computationOptions); \
|
||||
}
|
||||
|
||||
#define EIGEN_LAPACK_SDD_OPTIONS(OPTIONS) \
|
||||
EIGEN_LAPACKE_SDD(double, ColMajor, OPTIONS) \
|
||||
EIGEN_LAPACKE_SDD(float, ColMajor, OPTIONS) \
|
||||
EIGEN_LAPACKE_SDD(dcomplex, ColMajor, OPTIONS) \
|
||||
EIGEN_LAPACKE_SDD(scomplex, ColMajor, OPTIONS) \
|
||||
\
|
||||
EIGEN_LAPACKE_SDD(double, RowMajor, OPTIONS) \
|
||||
EIGEN_LAPACKE_SDD(float, RowMajor, OPTIONS) \
|
||||
EIGEN_LAPACKE_SDD(dcomplex, RowMajor, OPTIONS) \
|
||||
EIGEN_LAPACKE_SDD(scomplex, RowMajor, OPTIONS)
|
||||
|
||||
EIGEN_LAPACK_SDD_OPTIONS(0)
|
||||
EIGEN_LAPACK_SDD_OPTIONS(ComputeThinU)
|
||||
EIGEN_LAPACK_SDD_OPTIONS(ComputeThinV)
|
||||
EIGEN_LAPACK_SDD_OPTIONS(ComputeFullU)
|
||||
EIGEN_LAPACK_SDD_OPTIONS(ComputeFullV)
|
||||
EIGEN_LAPACK_SDD_OPTIONS(ComputeThinU | ComputeThinV)
|
||||
EIGEN_LAPACK_SDD_OPTIONS(ComputeFullU | ComputeFullV)
|
||||
EIGEN_LAPACK_SDD_OPTIONS(ComputeThinU | ComputeFullV)
|
||||
EIGEN_LAPACK_SDD_OPTIONS(ComputeFullU | ComputeThinV)
|
||||
|
||||
#undef EIGEN_LAPACK_SDD_OPTIONS
|
||||
|
||||
#undef EIGEN_LAPACKE_SDD
|
||||
|
||||
} // end namespace Eigen
|
||||
|
||||
#endif // EIGEN_BDCSVD_LAPACKE_H
|
||||
@ -72,8 +72,16 @@ JacobiSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, OPTION
|
||||
} else { ldvt=1; vt=&dummy; }\
|
||||
Matrix<LAPACKE_RTYPE, Dynamic, Dynamic> superb; superb.resize(m_diagSize, 1); \
|
||||
MatrixType m_temp; m_temp = matrix; \
|
||||
LAPACKE_##LAPACKE_PREFIX##gesvd( matrix_order, jobu, jobvt, internal::convert_index<lapack_int>(m_rows), internal::convert_index<lapack_int>(m_cols), (LAPACKE_TYPE*)m_temp.data(), lda, (LAPACKE_RTYPE*)m_singularValues.data(), u, ldu, vt, ldvt, superb.data()); \
|
||||
if (computeV()) m_matrixV = localV.adjoint(); \
|
||||
lapack_int info = LAPACKE_##LAPACKE_PREFIX##gesvd( matrix_order, jobu, jobvt, internal::convert_index<lapack_int>(m_rows), internal::convert_index<lapack_int>(m_cols), (LAPACKE_TYPE*)m_temp.data(), lda, (LAPACKE_RTYPE*)m_singularValues.data(), u, ldu, vt, ldvt, superb.data()); \
|
||||
/* Check the result of the LAPACK call */ \
|
||||
if (info < 0 || !m_singularValues.allFinite()) { \
|
||||
m_info = InvalidInput; \
|
||||
} else if (info > 0 ) { \
|
||||
m_info = NoConvergence; \
|
||||
} else { \
|
||||
m_info = Success; \
|
||||
if (computeV()) m_matrixV = localV.adjoint(); \
|
||||
} \
|
||||
/* for(int i=0;i<m_diagSize;i++) if (m_singularValues.coeffRef(i) < precision) { m_nonzeroSingularValues--; m_singularValues.coeffRef(i)=RealScalar(0);}*/ \
|
||||
m_isInitialized = true; \
|
||||
return *this; \
|
||||
|
||||
@ -150,6 +150,7 @@ EIGEN_ALWAYS_INLINE auto FUNCTION(Args&&... args) { return call_wrapper(LAPACKE_
|
||||
EIGEN_MAKE_LAPACKE_WRAPPER(potrf)
|
||||
EIGEN_MAKE_LAPACKE_WRAPPER(getrf)
|
||||
EIGEN_MAKE_LAPACKE_WRAPPER(geqrf)
|
||||
EIGEN_MAKE_LAPACKE_WRAPPER(gesdd)
|
||||
|
||||
#undef EIGEN_MAKE_LAPACKE_WRAPPER
|
||||
}
|
||||
|
||||
@ -106,6 +106,12 @@ svd.compute(m1);
|
||||
\endcode</td><td>\code
|
||||
?gesvd
|
||||
\endcode</td></tr>
|
||||
<tr class="alt"><td>Singular value decomposition \n \c EIGEN_USE_LAPACKE \n \c EIGEN_USE_LAPACKE_STRICT </td><td>\code
|
||||
BDCSVD<MatrixXd> svd;
|
||||
svd.compute(m1);
|
||||
\endcode</td><td>\code
|
||||
?gesdd
|
||||
\endcode</td></tr>
|
||||
<tr><td>Eigen-value decompositions \n \c EIGEN_USE_LAPACKE \n \c EIGEN_USE_LAPACKE_STRICT </td><td>\code
|
||||
EigenSolver<MatrixXd> es(m1);
|
||||
ComplexEigenSolver<MatrixXcd> ces(m1);
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user