зеркало из https://github.com/microsoft/EdgeML.git
703 строки
37 KiB
C++
703 строки
37 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#include <iostream>
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#include "common.h"
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int EIGEN_BLAS_FUNC(gemm)(const char *opa, const char *opb, const int *m, const int *n, const int *k, const RealScalar *palpha,
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const RealScalar *pa, const int *lda, const RealScalar *pb, const int *ldb, const RealScalar *pbeta, RealScalar *pc, const int *ldc)
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{
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// std::cerr << "in gemm " << *opa << " " << *opb << " " << *m << " " << *n << " " << *k << " " << *lda << " " << *ldb << " " << *ldc << " " << *palpha << " " << *pbeta << "\n";
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typedef void (*functype)(DenseIndex, DenseIndex, DenseIndex, const Scalar *, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, Scalar, internal::level3_blocking<Scalar,Scalar>&, Eigen::internal::GemmParallelInfo<DenseIndex>*);
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static const functype func[12] = {
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// array index: NOTR | (NOTR << 2)
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(internal::general_matrix_matrix_product<DenseIndex,Scalar,ColMajor,false,Scalar,ColMajor,false,ColMajor>::run),
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// array index: TR | (NOTR << 2)
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(internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,false,Scalar,ColMajor,false,ColMajor>::run),
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// array index: ADJ | (NOTR << 2)
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(internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,false,ColMajor>::run),
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0,
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// array index: NOTR | (TR << 2)
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(internal::general_matrix_matrix_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,false,ColMajor>::run),
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// array index: TR | (TR << 2)
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(internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,false,Scalar,RowMajor,false,ColMajor>::run),
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// array index: ADJ | (TR << 2)
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(internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,RowMajor,false,ColMajor>::run),
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0,
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// array index: NOTR | (ADJ << 2)
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(internal::general_matrix_matrix_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,Conj, ColMajor>::run),
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// array index: TR | (ADJ << 2)
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(internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,false,Scalar,RowMajor,Conj, ColMajor>::run),
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// array index: ADJ | (ADJ << 2)
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(internal::general_matrix_matrix_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,RowMajor,Conj, ColMajor>::run),
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0
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};
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const Scalar* a = reinterpret_cast<const Scalar*>(pa);
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const Scalar* b = reinterpret_cast<const Scalar*>(pb);
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Scalar* c = reinterpret_cast<Scalar*>(pc);
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Scalar alpha = *reinterpret_cast<const Scalar*>(palpha);
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Scalar beta = *reinterpret_cast<const Scalar*>(pbeta);
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int info = 0;
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if(OP(*opa)==INVALID) info = 1;
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else if(OP(*opb)==INVALID) info = 2;
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else if(*m<0) info = 3;
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else if(*n<0) info = 4;
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else if(*k<0) info = 5;
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else if(*lda<std::max(1,(OP(*opa)==NOTR)?*m:*k)) info = 8;
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else if(*ldb<std::max(1,(OP(*opb)==NOTR)?*k:*n)) info = 10;
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else if(*ldc<std::max(1,*m)) info = 13;
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if(info)
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return xerbla_(SCALAR_SUFFIX_UP"GEMM ",&info,6);
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if (*m == 0 || *n == 0)
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return 0;
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if(beta!=Scalar(1))
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{
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if(beta==Scalar(0)) matrix(c, *m, *n, *ldc).setZero();
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else matrix(c, *m, *n, *ldc) *= beta;
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}
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if(*k == 0)
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return 0;
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internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic> blocking(*m,*n,*k,1,true);
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int code = OP(*opa) | (OP(*opb) << 2);
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func[code](*m, *n, *k, a, *lda, b, *ldb, c, *ldc, alpha, blocking, 0);
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return 0;
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}
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int EIGEN_BLAS_FUNC(trsm)(const char *side, const char *uplo, const char *opa, const char *diag, const int *m, const int *n,
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const RealScalar *palpha, const RealScalar *pa, const int *lda, RealScalar *pb, const int *ldb)
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{
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// std::cerr << "in trsm " << *side << " " << *uplo << " " << *opa << " " << *diag << " " << *m << "," << *n << " " << *palpha << " " << *lda << " " << *ldb<< "\n";
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typedef void (*functype)(DenseIndex, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, internal::level3_blocking<Scalar,Scalar>&);
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static const functype func[32] = {
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// array index: NOTR | (LEFT << 2) | (UP << 3) | (NUNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|0, false,ColMajor,ColMajor>::run),
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// array index: TR | (LEFT << 2) | (UP << 3) | (NUNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|0, false,RowMajor,ColMajor>::run),
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// array index: ADJ | (LEFT << 2) | (UP << 3) | (NUNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|0, Conj, RowMajor,ColMajor>::run),\
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0,
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// array index: NOTR | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|0, false,ColMajor,ColMajor>::run),
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// array index: TR | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|0, false,RowMajor,ColMajor>::run),
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// array index: ADJ | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|0, Conj, RowMajor,ColMajor>::run),
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0,
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// array index: NOTR | (LEFT << 2) | (LO << 3) | (NUNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|0, false,ColMajor,ColMajor>::run),
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// array index: TR | (LEFT << 2) | (LO << 3) | (NUNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|0, false,RowMajor,ColMajor>::run),
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// array index: ADJ | (LEFT << 2) | (LO << 3) | (NUNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|0, Conj, RowMajor,ColMajor>::run),
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0,
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// array index: NOTR | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|0, false,ColMajor,ColMajor>::run),
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// array index: TR | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|0, false,RowMajor,ColMajor>::run),
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// array index: ADJ | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|0, Conj, RowMajor,ColMajor>::run),
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0,
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// array index: NOTR | (LEFT << 2) | (UP << 3) | (UNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|UnitDiag,false,ColMajor,ColMajor>::run),
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// array index: TR | (LEFT << 2) | (UP << 3) | (UNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|UnitDiag,false,RowMajor,ColMajor>::run),
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// array index: ADJ | (LEFT << 2) | (UP << 3) | (UNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|UnitDiag,Conj, RowMajor,ColMajor>::run),
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0,
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// array index: NOTR | (RIGHT << 2) | (UP << 3) | (UNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|UnitDiag,false,ColMajor,ColMajor>::run),
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// array index: TR | (RIGHT << 2) | (UP << 3) | (UNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|UnitDiag,false,RowMajor,ColMajor>::run),
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// array index: ADJ | (RIGHT << 2) | (UP << 3) | (UNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|UnitDiag,Conj, RowMajor,ColMajor>::run),
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0,
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// array index: NOTR | (LEFT << 2) | (LO << 3) | (UNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Lower|UnitDiag,false,ColMajor,ColMajor>::run),
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// array index: TR | (LEFT << 2) | (LO << 3) | (UNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|UnitDiag,false,RowMajor,ColMajor>::run),
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// array index: ADJ | (LEFT << 2) | (LO << 3) | (UNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheLeft, Upper|UnitDiag,Conj, RowMajor,ColMajor>::run),
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0,
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// array index: NOTR | (RIGHT << 2) | (LO << 3) | (UNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Lower|UnitDiag,false,ColMajor,ColMajor>::run),
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// array index: TR | (RIGHT << 2) | (LO << 3) | (UNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|UnitDiag,false,RowMajor,ColMajor>::run),
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// array index: ADJ | (RIGHT << 2) | (LO << 3) | (UNIT << 4)
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(internal::triangular_solve_matrix<Scalar,DenseIndex,OnTheRight,Upper|UnitDiag,Conj, RowMajor,ColMajor>::run),
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0
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};
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const Scalar* a = reinterpret_cast<const Scalar*>(pa);
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Scalar* b = reinterpret_cast<Scalar*>(pb);
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Scalar alpha = *reinterpret_cast<const Scalar*>(palpha);
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int info = 0;
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if(SIDE(*side)==INVALID) info = 1;
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else if(UPLO(*uplo)==INVALID) info = 2;
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else if(OP(*opa)==INVALID) info = 3;
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else if(DIAG(*diag)==INVALID) info = 4;
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else if(*m<0) info = 5;
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else if(*n<0) info = 6;
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else if(*lda<std::max(1,(SIDE(*side)==LEFT)?*m:*n)) info = 9;
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else if(*ldb<std::max(1,*m)) info = 11;
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if(info)
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return xerbla_(SCALAR_SUFFIX_UP"TRSM ",&info,6);
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if(*m==0 || *n==0)
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return 0;
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int code = OP(*opa) | (SIDE(*side) << 2) | (UPLO(*uplo) << 3) | (DIAG(*diag) << 4);
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if(SIDE(*side)==LEFT)
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{
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internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic,4> blocking(*m,*n,*m,1,false);
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func[code](*m, *n, a, *lda, b, *ldb, blocking);
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}
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else
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{
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internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic,4> blocking(*m,*n,*n,1,false);
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func[code](*n, *m, a, *lda, b, *ldb, blocking);
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}
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if(alpha!=Scalar(1))
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matrix(b,*m,*n,*ldb) *= alpha;
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return 0;
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}
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// b = alpha*op(a)*b for side = 'L'or'l'
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// b = alpha*b*op(a) for side = 'R'or'r'
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int EIGEN_BLAS_FUNC(trmm)(const char *side, const char *uplo, const char *opa, const char *diag, const int *m, const int *n,
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const RealScalar *palpha, const RealScalar *pa, const int *lda, RealScalar *pb, const int *ldb)
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{
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// std::cerr << "in trmm " << *side << " " << *uplo << " " << *opa << " " << *diag << " " << *m << " " << *n << " " << *lda << " " << *ldb << " " << *palpha << "\n";
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typedef void (*functype)(DenseIndex, DenseIndex, DenseIndex, const Scalar *, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, const Scalar&, internal::level3_blocking<Scalar,Scalar>&);
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static const functype func[32] = {
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// array index: NOTR | (LEFT << 2) | (UP << 3) | (NUNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0, true, ColMajor,false,ColMajor,false,ColMajor>::run),
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// array index: TR | (LEFT << 2) | (UP << 3) | (NUNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0, true, RowMajor,false,ColMajor,false,ColMajor>::run),
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// array index: ADJ | (LEFT << 2) | (UP << 3) | (NUNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0, true, RowMajor,Conj, ColMajor,false,ColMajor>::run),
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0,
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// array index: NOTR | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0, false,ColMajor,false,ColMajor,false,ColMajor>::run),
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// array index: TR | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0, false,ColMajor,false,RowMajor,false,ColMajor>::run),
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// array index: ADJ | (RIGHT << 2) | (UP << 3) | (NUNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0, false,ColMajor,false,RowMajor,Conj, ColMajor>::run),
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0,
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// array index: NOTR | (LEFT << 2) | (LO << 3) | (NUNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0, true, ColMajor,false,ColMajor,false,ColMajor>::run),
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// array index: TR | (LEFT << 2) | (LO << 3) | (NUNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0, true, RowMajor,false,ColMajor,false,ColMajor>::run),
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// array index: ADJ | (LEFT << 2) | (LO << 3) | (NUNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0, true, RowMajor,Conj, ColMajor,false,ColMajor>::run),
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0,
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// array index: NOTR | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|0, false,ColMajor,false,ColMajor,false,ColMajor>::run),
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// array index: TR | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0, false,ColMajor,false,RowMajor,false,ColMajor>::run),
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// array index: ADJ | (RIGHT << 2) | (LO << 3) | (NUNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|0, false,ColMajor,false,RowMajor,Conj, ColMajor>::run),
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0,
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// array index: NOTR | (LEFT << 2) | (UP << 3) | (UNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,true, ColMajor,false,ColMajor,false,ColMajor>::run),
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// array index: TR | (LEFT << 2) | (UP << 3) | (UNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,true, RowMajor,false,ColMajor,false,ColMajor>::run),
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// array index: ADJ | (LEFT << 2) | (UP << 3) | (UNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,true, RowMajor,Conj, ColMajor,false,ColMajor>::run),
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0,
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// array index: NOTR | (RIGHT << 2) | (UP << 3) | (UNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,false,ColMajor,false,ColMajor,false,ColMajor>::run),
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// array index: TR | (RIGHT << 2) | (UP << 3) | (UNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,false,ColMajor,false,RowMajor,false,ColMajor>::run),
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// array index: ADJ | (RIGHT << 2) | (UP << 3) | (UNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,false,ColMajor,false,RowMajor,Conj, ColMajor>::run),
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0,
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// array index: NOTR | (LEFT << 2) | (LO << 3) | (UNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,true, ColMajor,false,ColMajor,false,ColMajor>::run),
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// array index: TR | (LEFT << 2) | (LO << 3) | (UNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,true, RowMajor,false,ColMajor,false,ColMajor>::run),
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// array index: ADJ | (LEFT << 2) | (LO << 3) | (UNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,true, RowMajor,Conj, ColMajor,false,ColMajor>::run),
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0,
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// array index: NOTR | (RIGHT << 2) | (LO << 3) | (UNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Lower|UnitDiag,false,ColMajor,false,ColMajor,false,ColMajor>::run),
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// array index: TR | (RIGHT << 2) | (LO << 3) | (UNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,false,ColMajor,false,RowMajor,false,ColMajor>::run),
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// array index: ADJ | (RIGHT << 2) | (LO << 3) | (UNIT << 4)
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(internal::product_triangular_matrix_matrix<Scalar,DenseIndex,Upper|UnitDiag,false,ColMajor,false,RowMajor,Conj, ColMajor>::run),
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0
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};
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const Scalar* a = reinterpret_cast<const Scalar*>(pa);
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Scalar* b = reinterpret_cast<Scalar*>(pb);
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Scalar alpha = *reinterpret_cast<const Scalar*>(palpha);
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int info = 0;
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if(SIDE(*side)==INVALID) info = 1;
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else if(UPLO(*uplo)==INVALID) info = 2;
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else if(OP(*opa)==INVALID) info = 3;
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else if(DIAG(*diag)==INVALID) info = 4;
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else if(*m<0) info = 5;
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else if(*n<0) info = 6;
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else if(*lda<std::max(1,(SIDE(*side)==LEFT)?*m:*n)) info = 9;
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else if(*ldb<std::max(1,*m)) info = 11;
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if(info)
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return xerbla_(SCALAR_SUFFIX_UP"TRMM ",&info,6);
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int code = OP(*opa) | (SIDE(*side) << 2) | (UPLO(*uplo) << 3) | (DIAG(*diag) << 4);
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if(*m==0 || *n==0)
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return 1;
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// FIXME find a way to avoid this copy
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Matrix<Scalar,Dynamic,Dynamic,ColMajor> tmp = matrix(b,*m,*n,*ldb);
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matrix(b,*m,*n,*ldb).setZero();
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if(SIDE(*side)==LEFT)
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{
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internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic,4> blocking(*m,*n,*m,1,false);
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func[code](*m, *n, *m, a, *lda, tmp.data(), tmp.outerStride(), b, *ldb, alpha, blocking);
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}
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else
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{
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internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic,4> blocking(*m,*n,*n,1,false);
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func[code](*m, *n, *n, tmp.data(), tmp.outerStride(), a, *lda, b, *ldb, alpha, blocking);
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}
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return 1;
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}
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// c = alpha*a*b + beta*c for side = 'L'or'l'
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// c = alpha*b*a + beta*c for side = 'R'or'r
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int EIGEN_BLAS_FUNC(symm)(const char *side, const char *uplo, const int *m, const int *n, const RealScalar *palpha,
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const RealScalar *pa, const int *lda, const RealScalar *pb, const int *ldb, const RealScalar *pbeta, RealScalar *pc, const int *ldc)
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{
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// std::cerr << "in symm " << *side << " " << *uplo << " " << *m << "x" << *n << " lda:" << *lda << " ldb:" << *ldb << " ldc:" << *ldc << " alpha:" << *palpha << " beta:" << *pbeta << "\n";
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const Scalar* a = reinterpret_cast<const Scalar*>(pa);
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const Scalar* b = reinterpret_cast<const Scalar*>(pb);
|
|
Scalar* c = reinterpret_cast<Scalar*>(pc);
|
|
Scalar alpha = *reinterpret_cast<const Scalar*>(palpha);
|
|
Scalar beta = *reinterpret_cast<const Scalar*>(pbeta);
|
|
|
|
int info = 0;
|
|
if(SIDE(*side)==INVALID) info = 1;
|
|
else if(UPLO(*uplo)==INVALID) info = 2;
|
|
else if(*m<0) info = 3;
|
|
else if(*n<0) info = 4;
|
|
else if(*lda<std::max(1,(SIDE(*side)==LEFT)?*m:*n)) info = 7;
|
|
else if(*ldb<std::max(1,*m)) info = 9;
|
|
else if(*ldc<std::max(1,*m)) info = 12;
|
|
if(info)
|
|
return xerbla_(SCALAR_SUFFIX_UP"SYMM ",&info,6);
|
|
|
|
if(beta!=Scalar(1))
|
|
{
|
|
if(beta==Scalar(0)) matrix(c, *m, *n, *ldc).setZero();
|
|
else matrix(c, *m, *n, *ldc) *= beta;
|
|
}
|
|
|
|
if(*m==0 || *n==0)
|
|
{
|
|
return 1;
|
|
}
|
|
|
|
int size = (SIDE(*side)==LEFT) ? (*m) : (*n);
|
|
#if ISCOMPLEX
|
|
// FIXME add support for symmetric complex matrix
|
|
Matrix<Scalar,Dynamic,Dynamic,ColMajor> matA(size,size);
|
|
if(UPLO(*uplo)==UP)
|
|
{
|
|
matA.triangularView<Upper>() = matrix(a,size,size,*lda);
|
|
matA.triangularView<Lower>() = matrix(a,size,size,*lda).transpose();
|
|
}
|
|
else if(UPLO(*uplo)==LO)
|
|
{
|
|
matA.triangularView<Lower>() = matrix(a,size,size,*lda);
|
|
matA.triangularView<Upper>() = matrix(a,size,size,*lda).transpose();
|
|
}
|
|
if(SIDE(*side)==LEFT)
|
|
matrix(c, *m, *n, *ldc) += alpha * matA * matrix(b, *m, *n, *ldb);
|
|
else if(SIDE(*side)==RIGHT)
|
|
matrix(c, *m, *n, *ldc) += alpha * matrix(b, *m, *n, *ldb) * matA;
|
|
#else
|
|
internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic> blocking(*m,*n,size,1,false);
|
|
|
|
if(SIDE(*side)==LEFT)
|
|
if(UPLO(*uplo)==UP) internal::product_selfadjoint_matrix<Scalar, DenseIndex, RowMajor,true,false, ColMajor,false,false, ColMajor>::run(*m, *n, a, *lda, b, *ldb, c, *ldc, alpha, blocking);
|
|
else if(UPLO(*uplo)==LO) internal::product_selfadjoint_matrix<Scalar, DenseIndex, ColMajor,true,false, ColMajor,false,false, ColMajor>::run(*m, *n, a, *lda, b, *ldb, c, *ldc, alpha, blocking);
|
|
else return 0;
|
|
else if(SIDE(*side)==RIGHT)
|
|
if(UPLO(*uplo)==UP) internal::product_selfadjoint_matrix<Scalar, DenseIndex, ColMajor,false,false, RowMajor,true,false, ColMajor>::run(*m, *n, b, *ldb, a, *lda, c, *ldc, alpha, blocking);
|
|
else if(UPLO(*uplo)==LO) internal::product_selfadjoint_matrix<Scalar, DenseIndex, ColMajor,false,false, ColMajor,true,false, ColMajor>::run(*m, *n, b, *ldb, a, *lda, c, *ldc, alpha, blocking);
|
|
else return 0;
|
|
else
|
|
return 0;
|
|
#endif
|
|
|
|
return 0;
|
|
}
|
|
|
|
// c = alpha*a*a' + beta*c for op = 'N'or'n'
|
|
// c = alpha*a'*a + beta*c for op = 'T'or't','C'or'c'
|
|
int EIGEN_BLAS_FUNC(syrk)(const char *uplo, const char *op, const int *n, const int *k,
|
|
const RealScalar *palpha, const RealScalar *pa, const int *lda, const RealScalar *pbeta, RealScalar *pc, const int *ldc)
|
|
{
|
|
// std::cerr << "in syrk " << *uplo << " " << *op << " " << *n << " " << *k << " " << *palpha << " " << *lda << " " << *pbeta << " " << *ldc << "\n";
|
|
#if !ISCOMPLEX
|
|
typedef void (*functype)(DenseIndex, DenseIndex, const Scalar *, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, const Scalar&, internal::level3_blocking<Scalar,Scalar>&);
|
|
static const functype func[8] = {
|
|
// array index: NOTR | (UP << 2)
|
|
(internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,ColMajor,Conj, Upper>::run),
|
|
// array index: TR | (UP << 2)
|
|
(internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,false,Scalar,ColMajor,ColMajor,Conj, Upper>::run),
|
|
// array index: ADJ | (UP << 2)
|
|
(internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,ColMajor,false,Upper>::run),
|
|
0,
|
|
// array index: NOTR | (LO << 2)
|
|
(internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,ColMajor,Conj, Lower>::run),
|
|
// array index: TR | (LO << 2)
|
|
(internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,false,Scalar,ColMajor,ColMajor,Conj, Lower>::run),
|
|
// array index: ADJ | (LO << 2)
|
|
(internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,ColMajor,false,Lower>::run),
|
|
0
|
|
};
|
|
#endif
|
|
|
|
const Scalar* a = reinterpret_cast<const Scalar*>(pa);
|
|
Scalar* c = reinterpret_cast<Scalar*>(pc);
|
|
Scalar alpha = *reinterpret_cast<const Scalar*>(palpha);
|
|
Scalar beta = *reinterpret_cast<const Scalar*>(pbeta);
|
|
|
|
int info = 0;
|
|
if(UPLO(*uplo)==INVALID) info = 1;
|
|
else if(OP(*op)==INVALID || (ISCOMPLEX && OP(*op)==ADJ) ) info = 2;
|
|
else if(*n<0) info = 3;
|
|
else if(*k<0) info = 4;
|
|
else if(*lda<std::max(1,(OP(*op)==NOTR)?*n:*k)) info = 7;
|
|
else if(*ldc<std::max(1,*n)) info = 10;
|
|
if(info)
|
|
return xerbla_(SCALAR_SUFFIX_UP"SYRK ",&info,6);
|
|
|
|
if(beta!=Scalar(1))
|
|
{
|
|
if(UPLO(*uplo)==UP)
|
|
if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Upper>().setZero();
|
|
else matrix(c, *n, *n, *ldc).triangularView<Upper>() *= beta;
|
|
else
|
|
if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Lower>().setZero();
|
|
else matrix(c, *n, *n, *ldc).triangularView<Lower>() *= beta;
|
|
}
|
|
|
|
if(*n==0 || *k==0)
|
|
return 0;
|
|
|
|
#if ISCOMPLEX
|
|
// FIXME add support for symmetric complex matrix
|
|
if(UPLO(*uplo)==UP)
|
|
{
|
|
if(OP(*op)==NOTR)
|
|
matrix(c, *n, *n, *ldc).triangularView<Upper>() += alpha * matrix(a,*n,*k,*lda) * matrix(a,*n,*k,*lda).transpose();
|
|
else
|
|
matrix(c, *n, *n, *ldc).triangularView<Upper>() += alpha * matrix(a,*k,*n,*lda).transpose() * matrix(a,*k,*n,*lda);
|
|
}
|
|
else
|
|
{
|
|
if(OP(*op)==NOTR)
|
|
matrix(c, *n, *n, *ldc).triangularView<Lower>() += alpha * matrix(a,*n,*k,*lda) * matrix(a,*n,*k,*lda).transpose();
|
|
else
|
|
matrix(c, *n, *n, *ldc).triangularView<Lower>() += alpha * matrix(a,*k,*n,*lda).transpose() * matrix(a,*k,*n,*lda);
|
|
}
|
|
#else
|
|
internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic> blocking(*n,*n,*k,1,false);
|
|
|
|
int code = OP(*op) | (UPLO(*uplo) << 2);
|
|
func[code](*n, *k, a, *lda, a, *lda, c, *ldc, alpha, blocking);
|
|
#endif
|
|
|
|
return 0;
|
|
}
|
|
|
|
// c = alpha*a*b' + alpha*b*a' + beta*c for op = 'N'or'n'
|
|
// c = alpha*a'*b + alpha*b'*a + beta*c for op = 'T'or't'
|
|
int EIGEN_BLAS_FUNC(syr2k)(const char *uplo, const char *op, const int *n, const int *k, const RealScalar *palpha,
|
|
const RealScalar *pa, const int *lda, const RealScalar *pb, const int *ldb, const RealScalar *pbeta, RealScalar *pc, const int *ldc)
|
|
{
|
|
const Scalar* a = reinterpret_cast<const Scalar*>(pa);
|
|
const Scalar* b = reinterpret_cast<const Scalar*>(pb);
|
|
Scalar* c = reinterpret_cast<Scalar*>(pc);
|
|
Scalar alpha = *reinterpret_cast<const Scalar*>(palpha);
|
|
Scalar beta = *reinterpret_cast<const Scalar*>(pbeta);
|
|
|
|
// std::cerr << "in syr2k " << *uplo << " " << *op << " " << *n << " " << *k << " " << alpha << " " << *lda << " " << *ldb << " " << beta << " " << *ldc << "\n";
|
|
|
|
int info = 0;
|
|
if(UPLO(*uplo)==INVALID) info = 1;
|
|
else if(OP(*op)==INVALID || (ISCOMPLEX && OP(*op)==ADJ) ) info = 2;
|
|
else if(*n<0) info = 3;
|
|
else if(*k<0) info = 4;
|
|
else if(*lda<std::max(1,(OP(*op)==NOTR)?*n:*k)) info = 7;
|
|
else if(*ldb<std::max(1,(OP(*op)==NOTR)?*n:*k)) info = 9;
|
|
else if(*ldc<std::max(1,*n)) info = 12;
|
|
if(info)
|
|
return xerbla_(SCALAR_SUFFIX_UP"SYR2K",&info,6);
|
|
|
|
if(beta!=Scalar(1))
|
|
{
|
|
if(UPLO(*uplo)==UP)
|
|
if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Upper>().setZero();
|
|
else matrix(c, *n, *n, *ldc).triangularView<Upper>() *= beta;
|
|
else
|
|
if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Lower>().setZero();
|
|
else matrix(c, *n, *n, *ldc).triangularView<Lower>() *= beta;
|
|
}
|
|
|
|
if(*k==0)
|
|
return 1;
|
|
|
|
if(OP(*op)==NOTR)
|
|
{
|
|
if(UPLO(*uplo)==UP)
|
|
{
|
|
matrix(c, *n, *n, *ldc).triangularView<Upper>()
|
|
+= alpha *matrix(a, *n, *k, *lda)*matrix(b, *n, *k, *ldb).transpose()
|
|
+ alpha*matrix(b, *n, *k, *ldb)*matrix(a, *n, *k, *lda).transpose();
|
|
}
|
|
else if(UPLO(*uplo)==LO)
|
|
matrix(c, *n, *n, *ldc).triangularView<Lower>()
|
|
+= alpha*matrix(a, *n, *k, *lda)*matrix(b, *n, *k, *ldb).transpose()
|
|
+ alpha*matrix(b, *n, *k, *ldb)*matrix(a, *n, *k, *lda).transpose();
|
|
}
|
|
else if(OP(*op)==TR || OP(*op)==ADJ)
|
|
{
|
|
if(UPLO(*uplo)==UP)
|
|
matrix(c, *n, *n, *ldc).triangularView<Upper>()
|
|
+= alpha*matrix(a, *k, *n, *lda).transpose()*matrix(b, *k, *n, *ldb)
|
|
+ alpha*matrix(b, *k, *n, *ldb).transpose()*matrix(a, *k, *n, *lda);
|
|
else if(UPLO(*uplo)==LO)
|
|
matrix(c, *n, *n, *ldc).triangularView<Lower>()
|
|
+= alpha*matrix(a, *k, *n, *lda).transpose()*matrix(b, *k, *n, *ldb)
|
|
+ alpha*matrix(b, *k, *n, *ldb).transpose()*matrix(a, *k, *n, *lda);
|
|
}
|
|
|
|
return 0;
|
|
}
|
|
|
|
|
|
#if ISCOMPLEX
|
|
|
|
// c = alpha*a*b + beta*c for side = 'L'or'l'
|
|
// c = alpha*b*a + beta*c for side = 'R'or'r
|
|
int EIGEN_BLAS_FUNC(hemm)(const char *side, const char *uplo, const int *m, const int *n, const RealScalar *palpha,
|
|
const RealScalar *pa, const int *lda, const RealScalar *pb, const int *ldb, const RealScalar *pbeta, RealScalar *pc, const int *ldc)
|
|
{
|
|
const Scalar* a = reinterpret_cast<const Scalar*>(pa);
|
|
const Scalar* b = reinterpret_cast<const Scalar*>(pb);
|
|
Scalar* c = reinterpret_cast<Scalar*>(pc);
|
|
Scalar alpha = *reinterpret_cast<const Scalar*>(palpha);
|
|
Scalar beta = *reinterpret_cast<const Scalar*>(pbeta);
|
|
|
|
// std::cerr << "in hemm " << *side << " " << *uplo << " " << *m << " " << *n << " " << alpha << " " << *lda << " " << beta << " " << *ldc << "\n";
|
|
|
|
int info = 0;
|
|
if(SIDE(*side)==INVALID) info = 1;
|
|
else if(UPLO(*uplo)==INVALID) info = 2;
|
|
else if(*m<0) info = 3;
|
|
else if(*n<0) info = 4;
|
|
else if(*lda<std::max(1,(SIDE(*side)==LEFT)?*m:*n)) info = 7;
|
|
else if(*ldb<std::max(1,*m)) info = 9;
|
|
else if(*ldc<std::max(1,*m)) info = 12;
|
|
if(info)
|
|
return xerbla_(SCALAR_SUFFIX_UP"HEMM ",&info,6);
|
|
|
|
if(beta==Scalar(0)) matrix(c, *m, *n, *ldc).setZero();
|
|
else if(beta!=Scalar(1)) matrix(c, *m, *n, *ldc) *= beta;
|
|
|
|
if(*m==0 || *n==0)
|
|
{
|
|
return 1;
|
|
}
|
|
|
|
int size = (SIDE(*side)==LEFT) ? (*m) : (*n);
|
|
internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic> blocking(*m,*n,size,1,false);
|
|
|
|
if(SIDE(*side)==LEFT)
|
|
{
|
|
if(UPLO(*uplo)==UP) internal::product_selfadjoint_matrix<Scalar,DenseIndex,RowMajor,true,Conj, ColMajor,false,false, ColMajor>
|
|
::run(*m, *n, a, *lda, b, *ldb, c, *ldc, alpha, blocking);
|
|
else if(UPLO(*uplo)==LO) internal::product_selfadjoint_matrix<Scalar,DenseIndex,ColMajor,true,false, ColMajor,false,false, ColMajor>
|
|
::run(*m, *n, a, *lda, b, *ldb, c, *ldc, alpha, blocking);
|
|
else return 0;
|
|
}
|
|
else if(SIDE(*side)==RIGHT)
|
|
{
|
|
if(UPLO(*uplo)==UP) matrix(c,*m,*n,*ldc) += alpha * matrix(b,*m,*n,*ldb) * matrix(a,*n,*n,*lda).selfadjointView<Upper>();/*internal::product_selfadjoint_matrix<Scalar,DenseIndex,ColMajor,false,false, RowMajor,true,Conj, ColMajor>
|
|
::run(*m, *n, b, *ldb, a, *lda, c, *ldc, alpha, blocking);*/
|
|
else if(UPLO(*uplo)==LO) internal::product_selfadjoint_matrix<Scalar,DenseIndex,ColMajor,false,false, ColMajor,true,false, ColMajor>
|
|
::run(*m, *n, b, *ldb, a, *lda, c, *ldc, alpha, blocking);
|
|
else return 0;
|
|
}
|
|
else
|
|
{
|
|
return 0;
|
|
}
|
|
|
|
return 0;
|
|
}
|
|
|
|
// c = alpha*a*conj(a') + beta*c for op = 'N'or'n'
|
|
// c = alpha*conj(a')*a + beta*c for op = 'C'or'c'
|
|
int EIGEN_BLAS_FUNC(herk)(const char *uplo, const char *op, const int *n, const int *k,
|
|
const RealScalar *palpha, const RealScalar *pa, const int *lda, const RealScalar *pbeta, RealScalar *pc, const int *ldc)
|
|
{
|
|
// std::cerr << "in herk " << *uplo << " " << *op << " " << *n << " " << *k << " " << *palpha << " " << *lda << " " << *pbeta << " " << *ldc << "\n";
|
|
|
|
typedef void (*functype)(DenseIndex, DenseIndex, const Scalar *, DenseIndex, const Scalar *, DenseIndex, Scalar *, DenseIndex, const Scalar&, internal::level3_blocking<Scalar,Scalar>&);
|
|
static const functype func[8] = {
|
|
// array index: NOTR | (UP << 2)
|
|
(internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,Conj, ColMajor,Upper>::run),
|
|
0,
|
|
// array index: ADJ | (UP << 2)
|
|
(internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,false,ColMajor,Upper>::run),
|
|
0,
|
|
// array index: NOTR | (LO << 2)
|
|
(internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,ColMajor,false,Scalar,RowMajor,Conj, ColMajor,Lower>::run),
|
|
0,
|
|
// array index: ADJ | (LO << 2)
|
|
(internal::general_matrix_matrix_triangular_product<DenseIndex,Scalar,RowMajor,Conj, Scalar,ColMajor,false,ColMajor,Lower>::run),
|
|
0
|
|
};
|
|
|
|
const Scalar* a = reinterpret_cast<const Scalar*>(pa);
|
|
Scalar* c = reinterpret_cast<Scalar*>(pc);
|
|
RealScalar alpha = *palpha;
|
|
RealScalar beta = *pbeta;
|
|
|
|
// std::cerr << "in herk " << *uplo << " " << *op << " " << *n << " " << *k << " " << alpha << " " << *lda << " " << beta << " " << *ldc << "\n";
|
|
|
|
int info = 0;
|
|
if(UPLO(*uplo)==INVALID) info = 1;
|
|
else if((OP(*op)==INVALID) || (OP(*op)==TR)) info = 2;
|
|
else if(*n<0) info = 3;
|
|
else if(*k<0) info = 4;
|
|
else if(*lda<std::max(1,(OP(*op)==NOTR)?*n:*k)) info = 7;
|
|
else if(*ldc<std::max(1,*n)) info = 10;
|
|
if(info)
|
|
return xerbla_(SCALAR_SUFFIX_UP"HERK ",&info,6);
|
|
|
|
int code = OP(*op) | (UPLO(*uplo) << 2);
|
|
|
|
if(beta!=RealScalar(1))
|
|
{
|
|
if(UPLO(*uplo)==UP)
|
|
if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Upper>().setZero();
|
|
else matrix(c, *n, *n, *ldc).triangularView<StrictlyUpper>() *= beta;
|
|
else
|
|
if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Lower>().setZero();
|
|
else matrix(c, *n, *n, *ldc).triangularView<StrictlyLower>() *= beta;
|
|
|
|
if(beta!=Scalar(0))
|
|
{
|
|
matrix(c, *n, *n, *ldc).diagonal().real() *= beta;
|
|
matrix(c, *n, *n, *ldc).diagonal().imag().setZero();
|
|
}
|
|
}
|
|
|
|
if(*k>0 && alpha!=RealScalar(0))
|
|
{
|
|
internal::gemm_blocking_space<ColMajor,Scalar,Scalar,Dynamic,Dynamic,Dynamic> blocking(*n,*n,*k,1,false);
|
|
func[code](*n, *k, a, *lda, a, *lda, c, *ldc, alpha, blocking);
|
|
matrix(c, *n, *n, *ldc).diagonal().imag().setZero();
|
|
}
|
|
return 0;
|
|
}
|
|
|
|
// c = alpha*a*conj(b') + conj(alpha)*b*conj(a') + beta*c, for op = 'N'or'n'
|
|
// c = alpha*conj(a')*b + conj(alpha)*conj(b')*a + beta*c, for op = 'C'or'c'
|
|
int EIGEN_BLAS_FUNC(her2k)(const char *uplo, const char *op, const int *n, const int *k,
|
|
const RealScalar *palpha, const RealScalar *pa, const int *lda, const RealScalar *pb, const int *ldb, const RealScalar *pbeta, RealScalar *pc, const int *ldc)
|
|
{
|
|
const Scalar* a = reinterpret_cast<const Scalar*>(pa);
|
|
const Scalar* b = reinterpret_cast<const Scalar*>(pb);
|
|
Scalar* c = reinterpret_cast<Scalar*>(pc);
|
|
Scalar alpha = *reinterpret_cast<const Scalar*>(palpha);
|
|
RealScalar beta = *pbeta;
|
|
|
|
// std::cerr << "in her2k " << *uplo << " " << *op << " " << *n << " " << *k << " " << alpha << " " << *lda << " " << *ldb << " " << beta << " " << *ldc << "\n";
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int info = 0;
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if(UPLO(*uplo)==INVALID) info = 1;
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else if((OP(*op)==INVALID) || (OP(*op)==TR)) info = 2;
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else if(*n<0) info = 3;
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else if(*k<0) info = 4;
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else if(*lda<std::max(1,(OP(*op)==NOTR)?*n:*k)) info = 7;
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else if(*ldb<std::max(1,(OP(*op)==NOTR)?*n:*k)) info = 9;
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else if(*ldc<std::max(1,*n)) info = 12;
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if(info)
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return xerbla_(SCALAR_SUFFIX_UP"HER2K",&info,6);
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if(beta!=RealScalar(1))
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{
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if(UPLO(*uplo)==UP)
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if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Upper>().setZero();
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else matrix(c, *n, *n, *ldc).triangularView<StrictlyUpper>() *= beta;
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else
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if(beta==Scalar(0)) matrix(c, *n, *n, *ldc).triangularView<Lower>().setZero();
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else matrix(c, *n, *n, *ldc).triangularView<StrictlyLower>() *= beta;
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if(beta!=Scalar(0))
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{
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matrix(c, *n, *n, *ldc).diagonal().real() *= beta;
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matrix(c, *n, *n, *ldc).diagonal().imag().setZero();
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}
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}
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else if(*k>0 && alpha!=Scalar(0))
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matrix(c, *n, *n, *ldc).diagonal().imag().setZero();
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if(*k==0)
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return 1;
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if(OP(*op)==NOTR)
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{
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if(UPLO(*uplo)==UP)
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{
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matrix(c, *n, *n, *ldc).triangularView<Upper>()
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+= alpha *matrix(a, *n, *k, *lda)*matrix(b, *n, *k, *ldb).adjoint()
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+ numext::conj(alpha)*matrix(b, *n, *k, *ldb)*matrix(a, *n, *k, *lda).adjoint();
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}
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else if(UPLO(*uplo)==LO)
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matrix(c, *n, *n, *ldc).triangularView<Lower>()
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+= alpha*matrix(a, *n, *k, *lda)*matrix(b, *n, *k, *ldb).adjoint()
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+ numext::conj(alpha)*matrix(b, *n, *k, *ldb)*matrix(a, *n, *k, *lda).adjoint();
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}
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else if(OP(*op)==ADJ)
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{
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if(UPLO(*uplo)==UP)
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matrix(c, *n, *n, *ldc).triangularView<Upper>()
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+= alpha*matrix(a, *k, *n, *lda).adjoint()*matrix(b, *k, *n, *ldb)
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+ numext::conj(alpha)*matrix(b, *k, *n, *ldb).adjoint()*matrix(a, *k, *n, *lda);
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else if(UPLO(*uplo)==LO)
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matrix(c, *n, *n, *ldc).triangularView<Lower>()
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+= alpha*matrix(a, *k, *n, *lda).adjoint()*matrix(b, *k, *n, *ldb)
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+ numext::conj(alpha)*matrix(b, *k, *n, *ldb).adjoint()*matrix(a, *k, *n, *lda);
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}
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return 1;
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}
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#endif // ISCOMPLEX
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