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// 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,
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and/or other materials provided with the distribution.
* Neither the name of Intel Corporation nor the names of its contributors may
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********************************************************************************
* 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