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The source code and dockerfile for the GSW2024 AI Lab.
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GSW_AI_LAB/tempest-devel/resources/3rdparty/patches/eigen.patch

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From 4d2074e54b27877bcd694add91447b569d88e918 Mon Sep 17 00:00:00 2001
From: Tim Quatmann <tim.quatmann@cs.rwth-aachen.de>
Date: Wed, 20 May 2020 15:48:43 +0200
Subject: [PATCH] Eigen Patch
---
Eigen/src/SparseLU/SparseLU.h | 10 +--
Eigen/src/SparseLU/SparseLU_column_bmod.h | 2 +-
Eigen/src/SparseLU/SparseLU_copy_to_ucol.h | 2 +-
Eigen/src/SparseLU/SparseLU_panel_bmod.h | 6 +-
Eigen/src/SparseLU/SparseLU_pivotL.h | 79 +++++++++++++++-------
5 files changed, 63 insertions(+), 36 deletions(-)
diff --git a/Eigen/src/SparseLU/SparseLU.h b/Eigen/src/SparseLU/SparseLU.h
index 7104831..9aeceb0 100644
--- a/Eigen/src/SparseLU/SparseLU.h
+++ b/Eigen/src/SparseLU/SparseLU.h
@@ -97,12 +97,12 @@ class SparseLU : public SparseSolverBase<SparseLU<_MatrixType,_OrderingType> >,
};
public:
- SparseLU():m_lastError(""),m_Ustore(0,0,0,0,0,0),m_symmetricmode(false),m_diagpivotthresh(1.0),m_detPermR(1)
+ SparseLU():m_lastError(""),m_Ustore(0,0,0,0,0,0),m_symmetricmode(false),m_diagpivotthresh(1),m_detPermR(1)
{
initperfvalues();
}
explicit SparseLU(const MatrixType& matrix)
- : m_lastError(""),m_Ustore(0,0,0,0,0,0),m_symmetricmode(false),m_diagpivotthresh(1.0),m_detPermR(1)
+ : m_lastError(""),m_Ustore(0,0,0,0,0,0),m_symmetricmode(false),m_diagpivotthresh(1),m_detPermR(1)
{
initperfvalues();
compute(matrix);
@@ -255,7 +255,7 @@ class SparseLU : public SparseSolverBase<SparseLU<_MatrixType,_OrderingType> >,
using std::abs;
eigen_assert(m_factorizationIsOk && "The matrix should be factorized first.");
// Initialize with the determinant of the row matrix
- Scalar det = Scalar(1.);
+ Scalar det = Scalar(1);
// Note that the diagonal blocks of U are stored in supernodes,
// which are available in the L part :)
for (Index j = 0; j < this->cols(); ++j)
@@ -286,7 +286,7 @@ class SparseLU : public SparseSolverBase<SparseLU<_MatrixType,_OrderingType> >,
using std::abs;
eigen_assert(m_factorizationIsOk && "The matrix should be factorized first.");
- Scalar det = Scalar(0.);
+ Scalar det = Scalar(0);
for (Index j = 0; j < this->cols(); ++j)
{
for (typename SCMatrix::InnerIterator it(m_Lstore, j); it; ++it)
@@ -338,7 +338,7 @@ class SparseLU : public SparseSolverBase<SparseLU<_MatrixType,_OrderingType> >,
{
eigen_assert(m_factorizationIsOk && "The matrix should be factorized first.");
// Initialize with the determinant of the row matrix
- Scalar det = Scalar(1.);
+ Scalar det = Scalar(1);
// Note that the diagonal blocks of U are stored in supernodes,
// which are available in the L part :)
for (Index j = 0; j < this->cols(); ++j)
diff --git a/Eigen/src/SparseLU/SparseLU_column_bmod.h b/Eigen/src/SparseLU/SparseLU_column_bmod.h
index b57f068..be15e5e 100644
--- a/Eigen/src/SparseLU/SparseLU_column_bmod.h
+++ b/Eigen/src/SparseLU/SparseLU_column_bmod.h
@@ -129,7 +129,7 @@ Index SparseLUImpl<Scalar,StorageIndex>::column_bmod(const Index jcol, const Ind
{
irow = glu.lsub(isub);
glu.lusup(nextlu) = dense(irow);
- dense(irow) = Scalar(0.0);
+ dense(irow) = Scalar(0);
++nextlu;
}
diff --git a/Eigen/src/SparseLU/SparseLU_copy_to_ucol.h b/Eigen/src/SparseLU/SparseLU_copy_to_ucol.h
index c32d8d8..03c8aaf 100644
--- a/Eigen/src/SparseLU/SparseLU_copy_to_ucol.h
+++ b/Eigen/src/SparseLU/SparseLU_copy_to_ucol.h
@@ -87,7 +87,7 @@ Index SparseLUImpl<Scalar,StorageIndex>::copy_to_ucol(const Index jcol, const In
irow = glu.lsub(isub);
glu.usub(nextu) = perm_r(irow); // Unlike the L part, the U part is stored in its final order
glu.ucol(nextu) = dense(irow);
- dense(irow) = Scalar(0.0);
+ dense(irow) = Scalar(0);
nextu++;
isub++;
}
diff --git a/Eigen/src/SparseLU/SparseLU_panel_bmod.h b/Eigen/src/SparseLU/SparseLU_panel_bmod.h
index 822cf32..5dc819c 100644
--- a/Eigen/src/SparseLU/SparseLU_panel_bmod.h
+++ b/Eigen/src/SparseLU/SparseLU_panel_bmod.h
@@ -122,7 +122,7 @@ void SparseLUImpl<Scalar,StorageIndex>::panel_bmod(const Index m, const Index w,
Index isub = lptr + no_zeros;
Index off = u_rows-segsize;
- for (Index i = 0; i < off; i++) U(i,u_col) = 0;
+ for (Index i = 0; i < off; i++) U(i,u_col) = Scalar(0);
for (Index i = 0; i < segsize; i++)
{
Index irow = glu.lsub(isub);
@@ -172,7 +172,7 @@ void SparseLUImpl<Scalar,StorageIndex>::panel_bmod(const Index m, const Index w,
{
Index irow = glu.lsub(isub++);
dense_col(irow) = U.coeff(i+off,u_col);
- U.coeffRef(i+off,u_col) = 0;
+ U.coeffRef(i+off,u_col) = Scalar(0);
}
// Scatter l into SPA dense[]
@@ -180,7 +180,7 @@ void SparseLUImpl<Scalar,StorageIndex>::panel_bmod(const Index m, const Index w,
{
Index irow = glu.lsub(isub++);
dense_col(irow) -= L.coeff(i,u_col);
- L.coeffRef(i,u_col) = 0;
+ L.coeffRef(i,u_col) = Scalar(0);
}
u_col++;
}
diff --git a/Eigen/src/SparseLU/SparseLU_pivotL.h b/Eigen/src/SparseLU/SparseLU_pivotL.h
index a86dac9..f1ebd3c 100644
--- a/Eigen/src/SparseLU/SparseLU_pivotL.h
+++ b/Eigen/src/SparseLU/SparseLU_pivotL.h
@@ -32,7 +32,46 @@
namespace Eigen {
namespace internal {
-
+ template<typename Scalar, typename StorageIndex, typename std::enable_if<!std::is_same<Scalar, storm::RationalFunction>::value, int>::type = 0>
+ void findLargestAbsolutePivotElement(const Index& nsupc, const Index& nsupr, Scalar const* lu_col_ptr, StorageIndex const* lsub_ptr, Index const& diagind, Index& diag, Index& pivptr, Scalar& pivmax) {
+ Scalar rtemp = 0;
+ for (Index isub = nsupc; isub < nsupr; ++isub) {
+ rtemp = storm::utility::abs(lu_col_ptr[isub]);
+ if (rtemp > pivmax) {
+ pivmax = rtemp;
+ pivptr = isub;
+ }
+ if (lsub_ptr[isub] == diagind) diag = isub;
+ }
+ }
+
+ template<typename Scalar, typename StorageIndex, typename std::enable_if<std::is_same<Scalar, storm::RationalFunction>::value, int>::type = 0>
+ void findLargestAbsolutePivotElement(const Index& nsupc, const Index& nsupr, Scalar const* lu_col_ptr, StorageIndex const* lsub_ptr, Index const& diagind, Index& diag, Index& pivptr, Scalar& pivmax) {
+ bool foundPivotElement = false;
+ for (Index isub = nsupc; isub < nsupr; ++isub) {
+ Scalar const& rtemp = lu_col_ptr[isub];
+ if (!foundPivotElement && !storm::utility::isZero(rtemp)) {
+ foundPivotElement = true;
+ pivmax = rtemp;
+ pivptr = isub;
+ }
+ if (lsub_ptr[isub] == diagind) diag = isub;
+ }
+ }
+
+ template<typename Scalar, typename std::enable_if<std::is_same<Scalar, double>::value, int>::type = 0>
+ bool diagonalElementCanBePivot(Scalar const* lu_col_ptr, Index const& diag, Scalar const& diagpivotthresh, Scalar const& pivmax) {
+ Scalar thresh = diagpivotthresh * pivmax;
+ double rtemp = std::abs(lu_col_ptr[diag]);
+ if (!storm::utility::isZero(rtemp) && rtemp >= thresh) return true;
+ return false;
+ }
+
+ template<typename Scalar, typename std::enable_if<!std::is_same<Scalar, double>::value, int>::type = 0>
+ bool diagonalElementCanBePivot(Scalar const* lu_col_ptr, Index const& diag, Scalar const& diagpivotthresh, Scalar const& pivmax) {
+ if (!storm::utility::isZero(lu_col_ptr[diag])) return true;
+ return false;
+ }
/**
* \brief Performs the numerical pivotin on the current column of L, and the CDIV operation.
*
@@ -70,42 +109,30 @@ Index SparseLUImpl<Scalar,StorageIndex>::pivotL(const Index jcol, const RealScal
StorageIndex* lsub_ptr = &(glu.lsub.data()[lptr]); // Start of row indices of the supernode
// Determine the largest abs numerical value for partial pivoting
- Index diagind = iperm_c(jcol); // diagonal index
- RealScalar pivmax(-1.0);
- Index pivptr = nsupc;
- Index diag = emptyIdxLU;
- RealScalar rtemp;
- Index isub, icol, itemp, k;
- for (isub = nsupc; isub < nsupr; ++isub) {
- using std::abs;
- rtemp = abs(lu_col_ptr[isub]);
- if (rtemp > pivmax) {
- pivmax = rtemp;
- pivptr = isub;
- }
- if (lsub_ptr[isub] == diagind) diag = isub;
- }
+ Index diagind = iperm_c(jcol); // diagonal index
+ RealScalar pivmax(-1);
+ Index pivptr = nsupc;
+ Index diag = emptyIdxLU;
+ Index icol, itemp, k;
+
+ findLargestAbsolutePivotElement(nsupc, nsupr, lu_col_ptr, lsub_ptr, diagind, diag, pivptr, pivmax);
// Test for singularity
- if ( pivmax <= RealScalar(0.0) ) {
+ bool columnStructurallyEmpty = nsupr <= nsupc;
+ if ( columnStructurallyEmpty || storm::utility::isZero(pivmax)) {
// if pivmax == -1, the column is structurally empty, otherwise it is only numerically zero
- pivrow = pivmax < RealScalar(0.0) ? diagind : lsub_ptr[pivptr];
+ pivrow = columnStructurallyEmpty ? diagind : lsub_ptr[pivptr];
perm_r(pivrow) = StorageIndex(jcol);
return (jcol+1);
}
- RealScalar thresh = diagpivotthresh * pivmax;
-
- // Choose appropriate pivotal element
-
+ // Choose appropriate pivotal element
{
// Test if the diagonal element can be used as a pivot (given the threshold value)
if (diag >= 0 )
{
// Diagonal element exists
- using std::abs;
- rtemp = abs(lu_col_ptr[diag]);
- if (rtemp != RealScalar(0.0) && rtemp >= thresh) pivptr = diag;
+ if (diagonalElementCanBePivot(lu_col_ptr, diag, diagpivotthresh, pivmax)) pivptr = diag;
}
pivrow = lsub_ptr[pivptr];
}
@@ -125,7 +152,7 @@ Index SparseLUImpl<Scalar,StorageIndex>::pivotL(const Index jcol, const RealScal
}
}
// cdiv operations
- Scalar temp = Scalar(1.0) / lu_col_ptr[nsupc];
+ Scalar temp = Scalar(1) / lu_col_ptr[nsupc];
for (k = nsupc+1; k < nsupr; k++)
lu_col_ptr[k] *= temp;
return 0;
--
2.21.0 (Apple Git-122)