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Fix cuda device warnings

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This commit is contained in:
Antonio Sanchez
2025-02-28 15:21:23 -08:00
parent c53002f5fb
commit 23b1682723
53 changed files with 655 additions and 600 deletions
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4
Eigen/src/Core/Assign.h
View File

@@ -16,7 +16,7 @@ namespace Eigen {
template<typename Derived>
template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived& DenseBase<Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>
::lazyAssign(const DenseBase<OtherDerived>& other)
{
enum{
@@ -29,7 +29,7 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>
eigen_assert(rows() == other.rows() && cols() == other.cols());
internal::call_assignment_no_alias(derived(),other.derived());
return derived();
}

66
Eigen/src/Core/AssignEvaluator.h
View File

@@ -17,7 +17,7 @@ namespace Eigen {
// This implementation is based on Assign.h
namespace internal {
/***************************************************************************
* Part 1 : the logic deciding a strategy for traversal and unrolling *
***************************************************************************/
@@ -29,12 +29,12 @@ struct copy_using_evaluator_traits
{
typedef typename DstEvaluator::XprType Dst;
typedef typename Dst::Scalar DstScalar;
enum {
DstFlags = DstEvaluator::Flags,
SrcFlags = SrcEvaluator::Flags
};
public:
enum {
DstAlignment = DstEvaluator::Alignment,
@@ -135,7 +135,7 @@ public:
? int(CompleteUnrolling)
: int(NoUnrolling) )
: int(Traversal) == int(LinearTraversal)
? ( bool(MayUnrollCompletely) ? int(CompleteUnrolling)
? ( bool(MayUnrollCompletely) ? int(CompleteUnrolling)
: int(NoUnrolling) )
#if EIGEN_UNALIGNED_VECTORIZE
: int(Traversal) == int(SliceVectorizedTraversal)
@@ -195,7 +195,7 @@ struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling
// FIXME: this is not very clean, perhaps this information should be provided by the kernel?
typedef typename Kernel::DstEvaluatorType DstEvaluatorType;
typedef typename DstEvaluatorType::XprType DstXprType;
enum {
outer = Index / DstXprType::InnerSizeAtCompileTime,
inner = Index % DstXprType::InnerSizeAtCompileTime
@@ -261,7 +261,7 @@ struct copy_using_evaluator_innervec_CompleteUnrolling
typedef typename Kernel::DstEvaluatorType DstEvaluatorType;
typedef typename DstEvaluatorType::XprType DstXprType;
typedef typename Kernel::PacketType PacketType;
enum {
outer = Index / DstXprType::InnerSizeAtCompileTime,
inner = Index % DstXprType::InnerSizeAtCompileTime,
@@ -426,7 +426,7 @@ struct dense_assignment_loop<Kernel, LinearVectorizedTraversal, CompleteUnrollin
{
typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
typedef typename Kernel::PacketType PacketType;
enum { size = DstXprType::SizeAtCompileTime,
packetSize =unpacket_traits<PacketType>::size,
alignedSize = (size/packetSize)*packetSize };
@@ -599,14 +599,14 @@ protected:
typedef typename DstEvaluatorTypeT::XprType DstXprType;
typedef typename SrcEvaluatorTypeT::XprType SrcXprType;
public:
typedef DstEvaluatorTypeT DstEvaluatorType;
typedef SrcEvaluatorTypeT SrcEvaluatorType;
typedef typename DstEvaluatorType::Scalar Scalar;
typedef copy_using_evaluator_traits<DstEvaluatorTypeT, SrcEvaluatorTypeT, Functor> AssignmentTraits;
typedef typename AssignmentTraits::PacketType PacketType;
EIGEN_DEVICE_FUNC generic_dense_assignment_kernel(DstEvaluatorType &dst, const SrcEvaluatorType &src, const Functor &func, DstXprType& dstExpr)
: m_dst(dst), m_src(src), m_functor(func), m_dstExpr(dstExpr)
{
@@ -614,58 +614,58 @@ public:
AssignmentTraits::debug();
#endif
}
EIGEN_DEVICE_FUNC Index size() const { return m_dstExpr.size(); }
EIGEN_DEVICE_FUNC Index innerSize() const { return m_dstExpr.innerSize(); }
EIGEN_DEVICE_FUNC Index outerSize() const { return m_dstExpr.outerSize(); }
EIGEN_DEVICE_FUNC Index rows() const { return m_dstExpr.rows(); }
EIGEN_DEVICE_FUNC Index cols() const { return m_dstExpr.cols(); }
EIGEN_DEVICE_FUNC Index outerStride() const { return m_dstExpr.outerStride(); }
EIGEN_DEVICE_FUNC DstEvaluatorType& dstEvaluator() { return m_dst; }
EIGEN_DEVICE_FUNC const SrcEvaluatorType& srcEvaluator() const { return m_src; }
/// Assign src(row,col) to dst(row,col) through the assignment functor.
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignCoeff(Index row, Index col)
{
m_functor.assignCoeff(m_dst.coeffRef(row,col), m_src.coeff(row,col));
}
/// \sa assignCoeff(Index,Index)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignCoeff(Index index)
{
m_functor.assignCoeff(m_dst.coeffRef(index), m_src.coeff(index));
}
/// \sa assignCoeff(Index,Index)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignCoeffByOuterInner(Index outer, Index inner)
{
Index row = rowIndexByOuterInner(outer, inner);
Index col = colIndexByOuterInner(outer, inner);
Index row = rowIndexByOuterInner(outer, inner);
Index col = colIndexByOuterInner(outer, inner);
assignCoeff(row, col);
}
template<int StoreMode, int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacket(Index row, Index col)
{
m_functor.template assignPacket<StoreMode>(&m_dst.coeffRef(row,col), m_src.template packet<LoadMode,PacketType>(row,col));
}
template<int StoreMode, int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacket(Index index)
{
m_functor.template assignPacket<StoreMode>(&m_dst.coeffRef(index), m_src.template packet<LoadMode,PacketType>(index));
}
template<int StoreMode, int LoadMode, typename PacketType>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacketByOuterInner(Index outer, Index inner)
{
Index row = rowIndexByOuterInner(outer, inner);
Index row = rowIndexByOuterInner(outer, inner);
Index col = colIndexByOuterInner(outer, inner);
assignPacket<StoreMode,LoadMode,PacketType>(row, col);
}
EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Index rowIndexByOuterInner(Index outer, Index inner)
{
typedef typename DstEvaluatorType::ExpressionTraits Traits;
@@ -688,7 +688,7 @@ public:
{
return m_dstExpr.data();
}
protected:
DstEvaluatorType& m_dst;
const SrcEvaluatorType& m_src;
@@ -734,7 +734,7 @@ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void call_dense_assignment_loop(DstXprType
resize_if_allowed(dst, src, func);
DstEvaluatorType dstEvaluator(dst);
typedef generic_dense_assignment_kernel<DstEvaluatorType,SrcEvaluatorType,Functor> Kernel;
Kernel kernel(dstEvaluator, srcEvaluator, func, dst.const_cast_derived());
@@ -762,7 +762,7 @@ struct EigenBase2EigenBase {};
template<typename,typename> struct AssignmentKind { typedef EigenBase2EigenBase Kind; };
template<> struct AssignmentKind<DenseShape,DenseShape> { typedef Dense2Dense Kind; };
// This is the main assignment class
template< typename DstXprType, typename SrcXprType, typename Functor,
typename Kind = typename AssignmentKind< typename evaluator_traits<DstXprType>::Shape , typename evaluator_traits<SrcXprType>::Shape >::Kind,
@@ -787,7 +787,7 @@ void call_assignment(const Dst& dst, const Src& src)
{
call_assignment(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
}
// Deal with "assume-aliasing"
template<typename Dst, typename Src, typename Func>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
@@ -827,12 +827,12 @@ void call_assignment_no_alias(Dst& dst, const Src& src, const Func& func)
typedef typename internal::conditional<NeedToTranspose, Transpose<Dst>, Dst>::type ActualDstTypeCleaned;
typedef typename internal::conditional<NeedToTranspose, Transpose<Dst>, Dst&>::type ActualDstType;
ActualDstType actualDst(dst);
// TODO check whether this is the right place to perform these checks:
EIGEN_STATIC_ASSERT_LVALUE(Dst)
EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(ActualDstTypeCleaned,Src)
EIGEN_CHECK_BINARY_COMPATIBILIY(Func,typename ActualDstTypeCleaned::Scalar,typename Src::Scalar);
Assignment<ActualDstTypeCleaned,Src,Func>::run(actualDst, src, func);
}
template<typename Dst, typename Src>
@@ -869,13 +869,12 @@ template<typename Dst, typename Src> void check_for_aliasing(const Dst &dst, con
template< typename DstXprType, typename SrcXprType, typename Functor, typename Weak>
struct Assignment<DstXprType, SrcXprType, Functor, Dense2Dense, Weak>
{
EIGEN_DEVICE_FUNC
static EIGEN_STRONG_INLINE void run(DstXprType &dst, const SrcXprType &src, const Functor &func)
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(DstXprType &dst, const SrcXprType &src, const Functor &func)
{
#ifndef EIGEN_NO_DEBUG
internal::check_for_aliasing(dst, src);
#endif
call_dense_assignment_loop(dst, src, func);
}
};
@@ -887,8 +886,7 @@ struct Assignment<DstXprType, SrcXprType, Functor, Dense2Dense, Weak>
template< typename DstXprType, typename SrcXprType, typename Functor, typename Weak>
struct Assignment<DstXprType, SrcXprType, Functor, EigenBase2EigenBase, Weak>
{
EIGEN_DEVICE_FUNC
static EIGEN_STRONG_INLINE void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
{
Index dstRows = src.rows();
Index dstCols = src.cols();

10
Eigen/src/Core/CommaInitializer.h
View File

@@ -11,7 +11,7 @@
#ifndef EIGEN_COMMAINITIALIZER_H
#define EIGEN_COMMAINITIALIZER_H
namespace Eigen {
namespace Eigen {
/** \class CommaInitializer
* \ingroup Core_Module
@@ -44,7 +44,7 @@ struct CommaInitializer
m_xpr.block(0, 0, other.rows(), other.cols()) = other;
}
/* Copy/Move constructor which transfers ownership. This is crucial in
/* Copy/Move constructor which transfers ownership. This is crucial in
* absence of return value optimization to avoid assertions during destruction. */
// FIXME in C++11 mode this could be replaced by a proper RValue constructor
EIGEN_DEVICE_FUNC
@@ -135,13 +135,13 @@ struct CommaInitializer
*
* Example: \include MatrixBase_set.cpp
* Output: \verbinclude MatrixBase_set.out
*
*
* \note According the c++ standard, the argument expressions of this comma initializer are evaluated in arbitrary order.
*
* \sa CommaInitializer::finished(), class CommaInitializer
*/
template<typename Derived>
inline CommaInitializer<Derived> DenseBase<Derived>::operator<< (const Scalar& s)
EIGEN_DEVICE_FUNC inline CommaInitializer<Derived> DenseBase<Derived>::operator<< (const Scalar& s)
{
return CommaInitializer<Derived>(*static_cast<Derived*>(this), s);
}
@@ -149,7 +149,7 @@ inline CommaInitializer<Derived> DenseBase<Derived>::operator<< (const Scalar& s
/** \sa operator<<(const Scalar&) */
template<typename Derived>
template<typename OtherDerived>
inline CommaInitializer<Derived>
EIGEN_DEVICE_FUNC inline CommaInitializer<Derived>
DenseBase<Derived>::operator<<(const DenseBase<OtherDerived>& other)
{
return CommaInitializer<Derived>(*static_cast<Derived *>(this), other);

8
Eigen/src/Core/CwiseBinaryOp.h
View File

@@ -74,7 +74,7 @@ class CwiseBinaryOpImpl;
* \sa MatrixBase::binaryExpr(const MatrixBase<OtherDerived> &,const CustomBinaryOp &) const, class CwiseUnaryOp, class CwiseNullaryOp
*/
template<typename BinaryOp, typename LhsType, typename RhsType>
class CwiseBinaryOp :
class CwiseBinaryOp :
public CwiseBinaryOpImpl<
BinaryOp, LhsType, RhsType,
typename internal::cwise_promote_storage_type<typename internal::traits<LhsType>::StorageKind,
@@ -83,7 +83,7 @@ class CwiseBinaryOp :
internal::no_assignment_operator
{
public:
typedef typename internal::remove_all<BinaryOp>::type Functor;
typedef typename internal::remove_all<LhsType>::type Lhs;
typedef typename internal::remove_all<RhsType>::type Rhs;
@@ -158,7 +158,7 @@ public:
*/
template<typename Derived>
template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived &
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived &
MatrixBase<Derived>::operator-=(const MatrixBase<OtherDerived> &other)
{
call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar,typename OtherDerived::Scalar>());
@@ -171,7 +171,7 @@ MatrixBase<Derived>::operator-=(const MatrixBase<OtherDerived> &other)
*/
template<typename Derived>
template<typename OtherDerived>
EIGEN_STRONG_INLINE Derived &
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived &
MatrixBase<Derived>::operator+=(const MatrixBase<OtherDerived>& other)
{
call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar,typename OtherDerived::Scalar>());

6
Eigen/src/Core/CwiseNullaryOp.h
View File

@@ -126,12 +126,12 @@ DenseBase<Derived>::NullaryExpr(Index rows, Index cols, const CustomNullaryOp& f
*
* Here is an example with C++11 random generators: \include random_cpp11.cpp
* Output: \verbinclude random_cpp11.out
*
*
* \sa class CwiseNullaryOp
*/
template<typename Derived>
template<typename CustomNullaryOp>
EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, typename DenseBase<Derived>::PlainObject>
DenseBase<Derived>::NullaryExpr(Index size, const CustomNullaryOp& func)
{
EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
@@ -170,7 +170,7 @@ DenseBase<Derived>::NullaryExpr(const CustomNullaryOp& func)
* \sa class CwiseNullaryOp
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
DenseBase<Derived>::Constant(Index rows, Index cols, const Scalar& value)
{
return DenseBase<Derived>::NullaryExpr(rows, cols, internal::scalar_constant_op<Scalar>(value));

18
Eigen/src/Core/Diagonal.h
View File

@@ -11,7 +11,7 @@
#ifndef EIGEN_DIAGONAL_H
#define EIGEN_DIAGONAL_H
namespace Eigen {
namespace Eigen {
/** \class Diagonal
* \ingroup Core_Module
@@ -149,8 +149,8 @@ template<typename MatrixType, int _DiagIndex> class Diagonal
}
EIGEN_DEVICE_FUNC
inline const typename internal::remove_all<typename MatrixType::Nested>::type&
nestedExpression() const
inline const typename internal::remove_all<typename MatrixType::Nested>::type&
nestedExpression() const
{
return m_matrix;
}
@@ -187,7 +187,7 @@ template<typename MatrixType, int _DiagIndex> class Diagonal
*
* \sa class Diagonal */
template<typename Derived>
inline typename MatrixBase<Derived>::DiagonalReturnType
EIGEN_DEVICE_FUNC inline typename MatrixBase<Derived>::DiagonalReturnType
MatrixBase<Derived>::diagonal()
{
return DiagonalReturnType(derived());
@@ -195,7 +195,7 @@ MatrixBase<Derived>::diagonal()
/** This is the const version of diagonal(). */
template<typename Derived>
inline typename MatrixBase<Derived>::ConstDiagonalReturnType
EIGEN_DEVICE_FUNC inline typename MatrixBase<Derived>::ConstDiagonalReturnType
MatrixBase<Derived>::diagonal() const
{
return ConstDiagonalReturnType(derived());
@@ -213,7 +213,7 @@ MatrixBase<Derived>::diagonal() const
*
* \sa MatrixBase::diagonal(), class Diagonal */
template<typename Derived>
inline typename MatrixBase<Derived>::DiagonalDynamicIndexReturnType
EIGEN_DEVICE_FUNC inline typename MatrixBase<Derived>::DiagonalDynamicIndexReturnType
MatrixBase<Derived>::diagonal(Index index)
{
return DiagonalDynamicIndexReturnType(derived(), index);
@@ -221,7 +221,7 @@ MatrixBase<Derived>::diagonal(Index index)
/** This is the const version of diagonal(Index). */
template<typename Derived>
inline typename MatrixBase<Derived>::ConstDiagonalDynamicIndexReturnType
EIGEN_DEVICE_FUNC inline typename MatrixBase<Derived>::ConstDiagonalDynamicIndexReturnType
MatrixBase<Derived>::diagonal(Index index) const
{
return ConstDiagonalDynamicIndexReturnType(derived(), index);
@@ -240,7 +240,7 @@ MatrixBase<Derived>::diagonal(Index index) const
* \sa MatrixBase::diagonal(), class Diagonal */
template<typename Derived>
template<int Index_>
inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<Index_>::Type
EIGEN_DEVICE_FUNC inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<Index_>::Type
MatrixBase<Derived>::diagonal()
{
return typename DiagonalIndexReturnType<Index_>::Type(derived());
@@ -249,7 +249,7 @@ MatrixBase<Derived>::diagonal()
/** This is the const version of diagonal<int>(). */
template<typename Derived>
template<int Index_>
inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<Index_>::Type
EIGEN_DEVICE_FUNC inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<Index_>::Type
MatrixBase<Derived>::diagonal() const
{
return typename ConstDiagonalIndexReturnType<Index_>::Type(derived());

16
Eigen/src/Core/DiagonalMatrix.h
View File

@@ -11,7 +11,7 @@
#ifndef EIGEN_DIAGONALMATRIX_H
#define EIGEN_DIAGONALMATRIX_H
namespace Eigen {
namespace Eigen {
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename Derived>
@@ -44,7 +44,7 @@ class DiagonalBase : public EigenBase<Derived>
EIGEN_DEVICE_FUNC
DenseMatrixType toDenseMatrix() const { return derived(); }
EIGEN_DEVICE_FUNC
inline const DiagonalVectorType& diagonal() const { return derived().diagonal(); }
EIGEN_DEVICE_FUNC
@@ -70,7 +70,7 @@ class DiagonalBase : public EigenBase<Derived>
{
return InverseReturnType(diagonal().cwiseInverse());
}
EIGEN_DEVICE_FUNC
inline const DiagonalWrapper<const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DiagonalVectorType,Scalar,product) >
operator*(const Scalar& scalar) const
@@ -273,7 +273,7 @@ class DiagonalWrapper
* \sa class DiagonalWrapper, class DiagonalMatrix, diagonal(), isDiagonal()
**/
template<typename Derived>
inline const DiagonalWrapper<const Derived>
EIGEN_DEVICE_FUNC inline const DiagonalWrapper<const Derived>
MatrixBase<Derived>::asDiagonal() const
{
return DiagonalWrapper<const Derived>(derived());
@@ -318,20 +318,20 @@ template<> struct AssignmentKind<DenseShape,DiagonalShape> { typedef Diagonal2De
template< typename DstXprType, typename SrcXprType, typename Functor>
struct Assignment<DstXprType, SrcXprType, Functor, Diagonal2Dense>
{
static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
static EIGEN_DEVICE_FUNC void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
{
Index dstRows = src.rows();
Index dstCols = src.cols();
if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
dst.resize(dstRows, dstCols);
dst.setZero();
dst.diagonal() = src.diagonal();
}
static void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
{ dst.diagonal() += src.diagonal(); }
static void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
{ dst.diagonal() -= src.diagonal(); }
};

20
Eigen/src/Core/Dot.h
View File

@@ -10,7 +10,7 @@
#ifndef EIGEN_DOT_H
#define EIGEN_DOT_H
namespace Eigen {
namespace Eigen {
namespace internal {
@@ -78,7 +78,7 @@ MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const
typedef internal::scalar_conj_product_op<Scalar,typename OtherDerived::Scalar> func;
EIGEN_CHECK_BINARY_COMPATIBILIY(func,Scalar,typename OtherDerived::Scalar);
#endif
eigen_assert(size() == other.size());
return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
@@ -93,7 +93,7 @@ MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const
* \sa dot(), norm(), lpNorm()
*/
template<typename Derived>
EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::squaredNorm() const
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::squaredNorm() const
{
return numext::real((*this).cwiseAbs2().sum());
}
@@ -105,7 +105,7 @@ EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scala
* \sa lpNorm(), dot(), squaredNorm()
*/
template<typename Derived>
EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::norm() const
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::norm() const
{
return numext::sqrt(squaredNorm());
}
@@ -120,7 +120,7 @@ EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scala
* \sa norm(), normalize()
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::PlainObject
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::PlainObject
MatrixBase<Derived>::normalized() const
{
typedef typename internal::nested_eval<Derived,2>::type _Nested;
@@ -142,7 +142,7 @@ MatrixBase<Derived>::normalized() const
* \sa norm(), normalized()
*/
template<typename Derived>
EIGEN_STRONG_INLINE void MatrixBase<Derived>::normalize()
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void MatrixBase<Derived>::normalize()
{
RealScalar z = squaredNorm();
// NOTE: after extensive benchmarking, this conditional does not impact performance, at least on recent x86 CPU
@@ -163,7 +163,7 @@ EIGEN_STRONG_INLINE void MatrixBase<Derived>::normalize()
* \sa stableNorm(), stableNormalize(), normalized()
*/
template<typename Derived>
EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::PlainObject
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::PlainObject
MatrixBase<Derived>::stableNormalized() const
{
typedef typename internal::nested_eval<Derived,3>::type _Nested;
@@ -188,7 +188,7 @@ MatrixBase<Derived>::stableNormalized() const
* \sa stableNorm(), stableNormalized(), normalize()
*/
template<typename Derived>
EIGEN_STRONG_INLINE void MatrixBase<Derived>::stableNormalize()
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void MatrixBase<Derived>::stableNormalize()
{
RealScalar w = cwiseAbs().maxCoeff();
RealScalar z = (derived()/w).squaredNorm();
@@ -260,9 +260,9 @@ struct lpNorm_selector<Derived, Infinity>
template<typename Derived>
template<int p>
#ifndef EIGEN_PARSED_BY_DOXYGEN
inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real
EIGEN_DEVICE_FUNC inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real
#else
MatrixBase<Derived>::RealScalar
EIGEN_DEVICE_FUNC MatrixBase<Derived>::RealScalar
#endif
MatrixBase<Derived>::lpNorm() const
{

8
Eigen/src/Core/Fuzzy.h
View File

@@ -11,7 +11,7 @@
#ifndef EIGEN_FUZZY_H
#define EIGEN_FUZZY_H
namespace Eigen {
namespace Eigen {
namespace internal
{
@@ -100,7 +100,7 @@ struct isMuchSmallerThan_scalar_selector<Derived, true>
*/
template<typename Derived>
template<typename OtherDerived>
bool DenseBase<Derived>::isApprox(
EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isApprox(
const DenseBase<OtherDerived>& other,
const RealScalar& prec
) const
@@ -122,7 +122,7 @@ bool DenseBase<Derived>::isApprox(
* \sa isApprox(), isMuchSmallerThan(const DenseBase<OtherDerived>&, RealScalar) const
*/
template<typename Derived>
bool DenseBase<Derived>::isMuchSmallerThan(
EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isMuchSmallerThan(
const typename NumTraits<Scalar>::Real& other,
const RealScalar& prec
) const
@@ -142,7 +142,7 @@ bool DenseBase<Derived>::isMuchSmallerThan(
*/
template<typename Derived>
template<typename OtherDerived>
bool DenseBase<Derived>::isMuchSmallerThan(
EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isMuchSmallerThan(
const DenseBase<OtherDerived>& other,
const RealScalar& prec
) const

10
Eigen/src/Core/GeneralProduct.h
View File

@@ -207,12 +207,12 @@ template<> struct gemv_dense_selector<OnTheRight,ColMajor,true>
typedef typename Rhs::Scalar RhsScalar;
typedef typename Dest::Scalar ResScalar;
typedef typename Dest::RealScalar RealScalar;
typedef internal::blas_traits<Lhs> LhsBlasTraits;
typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
typedef internal::blas_traits<Rhs> RhsBlasTraits;
typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
typedef Map<Matrix<ResScalar,Dynamic,1>, EIGEN_PLAIN_ENUM_MIN(AlignedMax,internal::packet_traits<ResScalar>::size)> MappedDest;
ActualLhsType actualLhs = LhsBlasTraits::extract(lhs);
@@ -300,7 +300,7 @@ template<> struct gemv_dense_selector<OnTheRight,RowMajor,true>
typedef typename Lhs::Scalar LhsScalar;
typedef typename Rhs::Scalar RhsScalar;
typedef typename Dest::Scalar ResScalar;
typedef internal::blas_traits<Lhs> LhsBlasTraits;
typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
typedef internal::blas_traits<Rhs> RhsBlasTraits;
@@ -386,7 +386,7 @@ template<> struct gemv_dense_selector<OnTheRight,RowMajor,false>
*/
template<typename Derived>
template<typename OtherDerived>
inline const Product<Derived, OtherDerived>
EIGEN_DEVICE_FUNC inline const Product<Derived, OtherDerived>
MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
{
// A note regarding the function declaration: In MSVC, this function will sometimes
@@ -428,7 +428,7 @@ MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
*/
template<typename Derived>
template<typename OtherDerived>
const Product<Derived,OtherDerived,LazyProduct>
EIGEN_DEVICE_FUNC const Product<Derived,OtherDerived,LazyProduct>
MatrixBase<Derived>::lazyProduct(const MatrixBase<OtherDerived> &other) const
{
enum {

42
Eigen/src/Core/GenericPacketMath.h
View File

@@ -237,7 +237,7 @@ ploaddup(const typename unpacket_traits<Packet>::type* from) { return *from; }
* For instance, for a packet of 8 elements, 2 scalars will be read from \a *from and
* replicated to form: {from[0],from[0],from[0],from[0],from[1],from[1],from[1],from[1]}
* Currently, this function is only used in matrix products.
* For packet-size smaller or equal to 4, this function is equivalent to pload1
* For packet-size smaller or equal to 4, this function is equivalent to pload1
*/
template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
ploadquad(const typename unpacket_traits<Packet>::type* from)
@@ -359,77 +359,77 @@ template<typename Packet> EIGEN_DEVICE_FUNC inline Packet pcplxflip(const Packet
***************************/
/** \internal \returns the sine of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet psin(const Packet& a) { using std::sin; return sin(a); }
/** \internal \returns the cosine of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet pcos(const Packet& a) { using std::cos; return cos(a); }
/** \internal \returns the tan of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet ptan(const Packet& a) { using std::tan; return tan(a); }
/** \internal \returns the arc sine of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet pasin(const Packet& a) { using std::asin; return asin(a); }
/** \internal \returns the arc cosine of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet pacos(const Packet& a) { using std::acos; return acos(a); }
/** \internal \returns the arc tangent of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet patan(const Packet& a) { using std::atan; return atan(a); }
/** \internal \returns the hyperbolic sine of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet psinh(const Packet& a) { using std::sinh; return sinh(a); }
/** \internal \returns the hyperbolic cosine of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet pcosh(const Packet& a) { using std::cosh; return cosh(a); }
/** \internal \returns the hyperbolic tan of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet ptanh(const Packet& a) { using std::tanh; return tanh(a); }
/** \internal \returns the exp of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet pexp(const Packet& a) { using std::exp; return exp(a); }
/** \internal \returns the log of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet plog(const Packet& a) { using std::log; return log(a); }
/** \internal \returns the log1p of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet plog1p(const Packet& a) { return numext::log1p(a); }
/** \internal \returns the log10 of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet plog10(const Packet& a) { using std::log10; return log10(a); }
/** \internal \returns the square-root of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet psqrt(const Packet& a) { using std::sqrt; return sqrt(a); }
/** \internal \returns the reciprocal square-root of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet prsqrt(const Packet& a) {
return pdiv(pset1<Packet>(1), psqrt(a));
}
/** \internal \returns the rounded value of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet pround(const Packet& a) { using numext::round; return round(a); }
/** \internal \returns the floor of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet pfloor(const Packet& a) { using numext::floor; return floor(a); }
/** \internal \returns the ceil of \a a (coeff-wise) */
template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
template<typename Packet> EIGEN_DEVICE_FUNC EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
Packet pceil(const Packet& a) { using numext::ceil; return ceil(a); }
/***************************************************************************
@@ -494,14 +494,14 @@ struct palign_impl
/** \internal update \a first using the concatenation of the packet_size minus \a Offset last elements
* of \a first and \a Offset first elements of \a second.
*
*
* This function is currently only used to optimize matrix-vector products on unligned matrices.
* It takes 2 packets that represent a contiguous memory array, and returns a packet starting
* at the position \a Offset. For instance, for packets of 4 elements, we have:
* Input:
* - first = {f0,f1,f2,f3}
* - second = {s0,s1,s2,s3}
* Output:
* Output:
* - if Offset==0 then {f0,f1,f2,f3}
* - if Offset==1 then {f1,f2,f3,s0}
* - if Offset==2 then {f2,f3,s0,s1}

2
Eigen/src/Core/NestByValue.h
View File

@@ -99,7 +99,7 @@ template<typename ExpressionType> class NestByValue
/** \returns an expression of the temporary version of *this.
*/
template<typename Derived>
inline const NestByValue<Derived>
EIGEN_DEVICE_FUNC inline const NestByValue<Derived>
DenseBase<Derived>::nestByValue() const
{
return NestByValue<Derived>(derived());

140
Eigen/src/Core/ProductEvaluators.h
View File

@@ -14,7 +14,7 @@
#define EIGEN_PRODUCTEVALUATORS_H
namespace Eigen {
namespace internal {
/** \internal
@@ -22,19 +22,19 @@ namespace internal {
* Since products require special treatments to handle all possible cases,
* we simply deffer the evaluation logic to a product_evaluator class
* which offers more partial specialization possibilities.
*
*
* \sa class product_evaluator
*/
template<typename Lhs, typename Rhs, int Options>
struct evaluator<Product<Lhs, Rhs, Options> >
struct evaluator<Product<Lhs, Rhs, Options> >
: public product_evaluator<Product<Lhs, Rhs, Options> >
{
typedef Product<Lhs, Rhs, Options> XprType;
typedef product_evaluator<XprType> Base;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {}
};
// Catch "scalar * ( A * B )" and transform it to "(A*scalar) * B"
// TODO we should apply that rule only if that's really helpful
template<typename Lhs, typename Rhs, typename Scalar1, typename Scalar2, typename Plain1>
@@ -62,12 +62,12 @@ struct evaluator<CwiseBinaryOp<internal::scalar_product_op<Scalar1,Scalar2>,
template<typename Lhs, typename Rhs, int DiagIndex>
struct evaluator<Diagonal<const Product<Lhs, Rhs, DefaultProduct>, DiagIndex> >
struct evaluator<Diagonal<const Product<Lhs, Rhs, DefaultProduct>, DiagIndex> >
: public evaluator<Diagonal<const Product<Lhs, Rhs, LazyProduct>, DiagIndex> >
{
typedef Diagonal<const Product<Lhs, Rhs, DefaultProduct>, DiagIndex> XprType;
typedef evaluator<Diagonal<const Product<Lhs, Rhs, LazyProduct>, DiagIndex> > Base;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr)
: Base(Diagonal<const Product<Lhs, Rhs, LazyProduct>, DiagIndex>(
Product<Lhs, Rhs, LazyProduct>(xpr.nestedExpression().lhs(), xpr.nestedExpression().rhs()),
@@ -108,23 +108,23 @@ struct product_evaluator<Product<Lhs, Rhs, Options>, ProductTag, LhsShape, RhsSh
: m_result(xpr.rows(), xpr.cols())
{
::new (static_cast<Base*>(this)) Base(m_result);
// FIXME shall we handle nested_eval here?,
// if so, then we must take care at removing the call to nested_eval in the specializations (e.g., in permutation_matrix_product, transposition_matrix_product, etc.)
// typedef typename internal::nested_eval<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
// typedef typename internal::nested_eval<Rhs,Lhs::RowsAtCompileTime>::type RhsNested;
// typedef typename internal::remove_all<LhsNested>::type LhsNestedCleaned;
// typedef typename internal::remove_all<RhsNested>::type RhsNestedCleaned;
//
//
// const LhsNested lhs(xpr.lhs());
// const RhsNested rhs(xpr.rhs());
//
//
// generic_product_impl<LhsNestedCleaned, RhsNestedCleaned>::evalTo(m_result, lhs, rhs);
generic_product_impl<Lhs, Rhs, LhsShape, RhsShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
}
protected:
protected:
PlainObject m_result;
};
@@ -137,7 +137,7 @@ struct Assignment<DstXprType, Product<Lhs,Rhs,Options>, internal::assign_op<Scal
typename enable_if<(Options==DefaultProduct || Options==AliasFreeProduct)>::type>
{
typedef Product<Lhs,Rhs,Options> SrcXprType;
static EIGEN_STRONG_INLINE
static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC
void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &)
{
Index dstRows = src.rows();
@@ -155,7 +155,7 @@ struct Assignment<DstXprType, Product<Lhs,Rhs,Options>, internal::add_assign_op<
typename enable_if<(Options==DefaultProduct || Options==AliasFreeProduct)>::type>
{
typedef Product<Lhs,Rhs,Options> SrcXprType;
static EIGEN_STRONG_INLINE
static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC
void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<Scalar,Scalar> &)
{
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
@@ -170,7 +170,7 @@ struct Assignment<DstXprType, Product<Lhs,Rhs,Options>, internal::sub_assign_op<
typename enable_if<(Options==DefaultProduct || Options==AliasFreeProduct)>::type>
{
typedef Product<Lhs,Rhs,Options> SrcXprType;
static EIGEN_STRONG_INLINE
static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC
void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<Scalar,Scalar> &)
{
eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
@@ -190,7 +190,7 @@ struct Assignment<DstXprType, CwiseBinaryOp<internal::scalar_product_op<ScalarBi
typedef CwiseBinaryOp<internal::scalar_product_op<ScalarBis,Scalar>,
const CwiseNullaryOp<internal::scalar_constant_op<ScalarBis>,Plain>,
const Product<Lhs,Rhs,DefaultProduct> > SrcXprType;
static EIGEN_STRONG_INLINE
static EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC
void run(DstXprType &dst, const SrcXprType &src, const AssignFunc& func)
{
call_assignment_no_alias(dst, (src.lhs().functor().m_other * src.rhs().lhs())*src.rhs().rhs(), func);
@@ -250,13 +250,13 @@ struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,InnerProduct>
{
dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
}
template<typename Dst>
static EIGEN_STRONG_INLINE void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
dst.coeffRef(0,0) += (lhs.transpose().cwiseProduct(rhs)).sum();
}
template<typename Dst>
static EIGEN_STRONG_INLINE void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{ dst.coeffRef(0,0) -= (lhs.transpose().cwiseProduct(rhs)).sum(); }
@@ -298,7 +298,7 @@ struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,OuterProduct>
{
template<typename T> struct is_row_major : internal::conditional<(int(T::Flags)&RowMajorBit), internal::true_type, internal::false_type>::type {};
typedef typename Product<Lhs,Rhs>::Scalar Scalar;
// TODO it would be nice to be able to exploit our *_assign_op functors for that purpose
struct set { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() = src; } };
struct add { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() += src; } };
@@ -310,31 +310,31 @@ struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,OuterProduct>
dst.const_cast_derived() += m_scale * src;
}
};
template<typename Dst>
static EIGEN_STRONG_INLINE void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
internal::outer_product_selector_run(dst, lhs, rhs, set(), is_row_major<Dst>());
}
template<typename Dst>
static EIGEN_STRONG_INLINE void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
internal::outer_product_selector_run(dst, lhs, rhs, add(), is_row_major<Dst>());
}
template<typename Dst>
static EIGEN_STRONG_INLINE void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
internal::outer_product_selector_run(dst, lhs, rhs, sub(), is_row_major<Dst>());
}
template<typename Dst>
static EIGEN_STRONG_INLINE void scaleAndAddTo(Dst& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
{
internal::outer_product_selector_run(dst, lhs, rhs, adds(alpha), is_row_major<Dst>());
}
};
@@ -343,7 +343,7 @@ template<typename Lhs, typename Rhs, typename Derived>
struct generic_product_impl_base
{
typedef typename Product<Lhs,Rhs>::Scalar Scalar;
template<typename Dst>
static EIGEN_STRONG_INLINE void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{ dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); }
@@ -355,7 +355,7 @@ struct generic_product_impl_base
template<typename Dst>
static EIGEN_STRONG_INLINE void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{ scaleAndAddTo(dst, lhs, rhs, Scalar(-1)); }
template<typename Dst>
static EIGEN_STRONG_INLINE void scaleAndAddTo(Dst& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
{ Derived::scaleAndAddTo(dst,lhs,rhs,alpha); }
@@ -385,12 +385,12 @@ struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,GemvProduct>
};
template<typename Lhs, typename Rhs>
struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,CoeffBasedProductMode>
struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,CoeffBasedProductMode>
{
typedef typename Product<Lhs,Rhs>::Scalar Scalar;
template<typename Dst>
static EIGEN_STRONG_INLINE void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
// Same as: dst.noalias() = lhs.lazyProduct(rhs);
// but easier on the compiler side
@@ -403,7 +403,7 @@ struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,CoeffBasedProductMode>
// dst.noalias() += lhs.lazyProduct(rhs);
call_assignment_no_alias(dst, lhs.lazyProduct(rhs), internal::add_assign_op<typename Dst::Scalar,Scalar>());
}
template<typename Dst>
static EIGEN_STRONG_INLINE void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
@@ -435,8 +435,8 @@ struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,CoeffBasedProductMode>
{
call_assignment_no_alias(dst, lhs.lazyProduct(rhs), func);
}
// template<typename Dst>
// static inline void scaleAndAddTo(Dst& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
// { dst.noalias() += alpha * lhs.lazyProduct(rhs); }
@@ -497,7 +497,7 @@ struct product_evaluator<Product<Lhs, Rhs, LazyProduct>, ProductTag, DenseShape,
typedef typename internal::nested_eval<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
typedef typename internal::nested_eval<Rhs,Lhs::RowsAtCompileTime>::type RhsNested;
typedef typename internal::remove_all<LhsNested>::type LhsNestedCleaned;
typedef typename internal::remove_all<RhsNested>::type RhsNestedCleaned;
@@ -516,7 +516,7 @@ struct product_evaluator<Product<Lhs, Rhs, LazyProduct>, ProductTag, DenseShape,
typedef typename find_best_packet<Scalar,ColsAtCompileTime>::type RhsVecPacketType;
enum {
LhsCoeffReadCost = LhsEtorType::CoeffReadCost,
RhsCoeffReadCost = RhsEtorType::CoeffReadCost,
CoeffReadCost = InnerSize==0 ? NumTraits<Scalar>::ReadCost
@@ -525,10 +525,10 @@ struct product_evaluator<Product<Lhs, Rhs, LazyProduct>, ProductTag, DenseShape,
+ (InnerSize - 1) * NumTraits<Scalar>::AddCost,
Unroll = CoeffReadCost <= EIGEN_UNROLLING_LIMIT,
LhsFlags = LhsEtorType::Flags,
RhsFlags = RhsEtorType::Flags,
LhsRowMajor = LhsFlags & RowMajorBit,
RhsRowMajor = RhsFlags & RowMajorBit,
@@ -538,7 +538,7 @@ struct product_evaluator<Product<Lhs, Rhs, LazyProduct>, ProductTag, DenseShape,
// Here, we don't care about alignment larger than the usable packet size.
LhsAlignment = EIGEN_PLAIN_ENUM_MIN(LhsEtorType::Alignment,LhsVecPacketSize*int(sizeof(typename LhsNestedCleaned::Scalar))),
RhsAlignment = EIGEN_PLAIN_ENUM_MIN(RhsEtorType::Alignment,RhsVecPacketSize*int(sizeof(typename RhsNestedCleaned::Scalar))),
SameType = is_same<typename LhsNestedCleaned::Scalar,typename RhsNestedCleaned::Scalar>::value,
CanVectorizeRhs = bool(RhsRowMajor) && (RhsFlags & PacketAccessBit) && (ColsAtCompileTime!=1),
@@ -553,7 +553,7 @@ struct product_evaluator<Product<Lhs, Rhs, LazyProduct>, ProductTag, DenseShape,
// TODO enable vectorization for mixed types
| (SameType && (CanVectorizeLhs || CanVectorizeRhs) ? PacketAccessBit : 0)
| (XprType::IsVectorAtCompileTime ? LinearAccessBit : 0),
LhsOuterStrideBytes = int(LhsNestedCleaned::OuterStrideAtCompileTime) * int(sizeof(typename LhsNestedCleaned::Scalar)),
RhsOuterStrideBytes = int(RhsNestedCleaned::OuterStrideAtCompileTime) * int(sizeof(typename RhsNestedCleaned::Scalar)),
@@ -572,7 +572,7 @@ struct product_evaluator<Product<Lhs, Rhs, LazyProduct>, ProductTag, DenseShape,
&& (LhsFlags & RhsFlags & ActualPacketAccessBit)
&& (InnerSize % packet_traits<Scalar>::size == 0)
};
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index row, Index col) const
{
return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum();
@@ -611,7 +611,7 @@ struct product_evaluator<Product<Lhs, Rhs, LazyProduct>, ProductTag, DenseShape,
protected:
typename internal::add_const_on_value_type<LhsNested>::type m_lhs;
typename internal::add_const_on_value_type<RhsNested>::type m_rhs;
LhsEtorType m_lhsImpl;
RhsEtorType m_rhsImpl;
@@ -730,7 +730,7 @@ struct generic_product_impl<Lhs,Rhs,TriangularShape,DenseShape,ProductTag>
: generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,TriangularShape,DenseShape,ProductTag> >
{
typedef typename Product<Lhs,Rhs>::Scalar Scalar;
template<typename Dest>
static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
{
@@ -744,7 +744,7 @@ struct generic_product_impl<Lhs,Rhs,DenseShape,TriangularShape,ProductTag>
: generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,DenseShape,TriangularShape,ProductTag> >
{
typedef typename Product<Lhs,Rhs>::Scalar Scalar;
template<typename Dest>
static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
{
@@ -765,7 +765,7 @@ struct generic_product_impl<Lhs,Rhs,SelfAdjointShape,DenseShape,ProductTag>
: generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,SelfAdjointShape,DenseShape,ProductTag> >
{
typedef typename Product<Lhs,Rhs>::Scalar Scalar;
template<typename Dest>
static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
{
@@ -778,7 +778,7 @@ struct generic_product_impl<Lhs,Rhs,DenseShape,SelfAdjointShape,ProductTag>
: generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,DenseShape,SelfAdjointShape,ProductTag> >
{
typedef typename Product<Lhs,Rhs>::Scalar Scalar;
template<typename Dest>
static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
{
@@ -790,7 +790,7 @@ struct generic_product_impl<Lhs,Rhs,DenseShape,SelfAdjointShape,ProductTag>
/***************************************************************************
* Diagonal products
***************************************************************************/
template<typename MatrixType, typename DiagonalType, typename Derived, int ProductOrder>
struct diagonal_product_evaluator_base
: evaluator_base<Derived>
@@ -799,7 +799,7 @@ struct diagonal_product_evaluator_base
public:
enum {
CoeffReadCost = NumTraits<Scalar>::MulCost + evaluator<MatrixType>::CoeffReadCost + evaluator<DiagonalType>::CoeffReadCost,
MatrixFlags = evaluator<MatrixType>::Flags,
DiagFlags = evaluator<DiagonalType>::Flags,
_StorageOrder = MatrixFlags & RowMajorBit ? RowMajor : ColMajor,
@@ -817,14 +817,14 @@ public:
|| (DiagonalType::SizeAtCompileTime==Dynamic && MatrixType::RowsAtCompileTime==1 && ProductOrder==OnTheLeft)
|| (DiagonalType::SizeAtCompileTime==Dynamic && MatrixType::ColsAtCompileTime==1 && ProductOrder==OnTheRight)
};
diagonal_product_evaluator_base(const MatrixType &mat, const DiagonalType &diag)
: m_diagImpl(diag), m_matImpl(mat)
{
EIGEN_INTERNAL_CHECK_COST_VALUE(NumTraits<Scalar>::MulCost);
EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index idx) const
{
if(AsScalarProduct)
@@ -832,7 +832,7 @@ public:
else
return m_diagImpl.coeff(idx) * m_matImpl.coeff(idx);
}
protected:
template<int LoadMode,typename PacketType>
EIGEN_STRONG_INLINE PacketType packet_impl(Index row, Index col, Index id, internal::true_type) const
@@ -840,7 +840,7 @@ protected:
return internal::pmul(m_matImpl.template packet<LoadMode,PacketType>(row, col),
internal::pset1<PacketType>(m_diagImpl.coeff(id)));
}
template<int LoadMode,typename PacketType>
EIGEN_STRONG_INLINE PacketType packet_impl(Index row, Index col, Index id, internal::false_type) const
{
@@ -851,7 +851,7 @@ protected:
return internal::pmul(m_matImpl.template packet<LoadMode,PacketType>(row, col),
m_diagImpl.template packet<DiagonalPacketLoadMode,PacketType>(id));
}
evaluator<DiagonalType> m_diagImpl;
evaluator<MatrixType> m_matImpl;
};
@@ -866,10 +866,10 @@ struct product_evaluator<Product<Lhs, Rhs, ProductKind>, ProductTag, DiagonalSha
using Base::m_matImpl;
using Base::coeff;
typedef typename Base::Scalar Scalar;
typedef Product<Lhs, Rhs, ProductKind> XprType;
typedef typename XprType::PlainObject PlainObject;
enum {
StorageOrder = int(Rhs::Flags) & RowMajorBit ? RowMajor : ColMajor
};
@@ -878,12 +878,12 @@ struct product_evaluator<Product<Lhs, Rhs, ProductKind>, ProductTag, DiagonalSha
: Base(xpr.rhs(), xpr.lhs().diagonal())
{
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
{
return m_diagImpl.coeff(row) * m_matImpl.coeff(row, col);
}
#ifndef __CUDACC__
template<int LoadMode,typename PacketType>
EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const
@@ -893,7 +893,7 @@ struct product_evaluator<Product<Lhs, Rhs, ProductKind>, ProductTag, DiagonalSha
return this->template packet_impl<LoadMode,PacketType>(row,col, row,
typename internal::conditional<int(StorageOrder)==RowMajor, internal::true_type, internal::false_type>::type());
}
template<int LoadMode,typename PacketType>
EIGEN_STRONG_INLINE PacketType packet(Index idx) const
{
@@ -912,22 +912,22 @@ struct product_evaluator<Product<Lhs, Rhs, ProductKind>, ProductTag, DenseShape,
using Base::m_matImpl;
using Base::coeff;
typedef typename Base::Scalar Scalar;
typedef Product<Lhs, Rhs, ProductKind> XprType;
typedef typename XprType::PlainObject PlainObject;
enum { StorageOrder = int(Lhs::Flags) & RowMajorBit ? RowMajor : ColMajor };
EIGEN_DEVICE_FUNC explicit product_evaluator(const XprType& xpr)
: Base(xpr.lhs(), xpr.rhs().diagonal())
{
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
{
return m_matImpl.coeff(row, col) * m_diagImpl.coeff(col);
}
#ifndef __CUDACC__
template<int LoadMode,typename PacketType>
EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const
@@ -935,7 +935,7 @@ struct product_evaluator<Product<Lhs, Rhs, ProductKind>, ProductTag, DenseShape,
return this->template packet_impl<LoadMode,PacketType>(row,col, col,
typename internal::conditional<int(StorageOrder)==ColMajor, internal::true_type, internal::false_type>::type());
}
template<int LoadMode,typename PacketType>
EIGEN_STRONG_INLINE PacketType packet(Index idx) const
{
@@ -1017,7 +1017,7 @@ template<typename Lhs, typename Rhs, int ProductTag, typename MatrixShape>
struct generic_product_impl<Lhs, Rhs, PermutationShape, MatrixShape, ProductTag>
{
template<typename Dest>
static void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs)
static EIGEN_DEVICE_FUNC void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs)
{
permutation_matrix_product<Rhs, OnTheLeft, false, MatrixShape>::run(dst, lhs, rhs);
}
@@ -1027,7 +1027,7 @@ template<typename Lhs, typename Rhs, int ProductTag, typename MatrixShape>
struct generic_product_impl<Lhs, Rhs, MatrixShape, PermutationShape, ProductTag>
{
template<typename Dest>
static void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs)
static EIGEN_DEVICE_FUNC void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs)
{
permutation_matrix_product<Lhs, OnTheRight, false, MatrixShape>::run(dst, rhs, lhs);
}
@@ -1037,7 +1037,7 @@ template<typename Lhs, typename Rhs, int ProductTag, typename MatrixShape>
struct generic_product_impl<Inverse<Lhs>, Rhs, PermutationShape, MatrixShape, ProductTag>
{
template<typename Dest>
static void evalTo(Dest& dst, const Inverse<Lhs>& lhs, const Rhs& rhs)
static EIGEN_DEVICE_FUNC void evalTo(Dest& dst, const Inverse<Lhs>& lhs, const Rhs& rhs)
{
permutation_matrix_product<Rhs, OnTheLeft, true, MatrixShape>::run(dst, lhs.nestedExpression(), rhs);
}
@@ -1047,7 +1047,7 @@ template<typename Lhs, typename Rhs, int ProductTag, typename MatrixShape>
struct generic_product_impl<Lhs, Inverse<Rhs>, MatrixShape, PermutationShape, ProductTag>
{
template<typename Dest>
static void evalTo(Dest& dst, const Lhs& lhs, const Inverse<Rhs>& rhs)
static EIGEN_DEVICE_FUNC void evalTo(Dest& dst, const Lhs& lhs, const Inverse<Rhs>& rhs)
{
permutation_matrix_product<Lhs, OnTheRight, true, MatrixShape>::run(dst, rhs.nestedExpression(), lhs);
}
@@ -1069,7 +1069,7 @@ struct transposition_matrix_product
{
typedef typename nested_eval<ExpressionType, 1>::type MatrixType;
typedef typename remove_all<MatrixType>::type MatrixTypeCleaned;
template<typename Dest, typename TranspositionType>
static inline void run(Dest& dst, const TranspositionType& tr, const ExpressionType& xpr)
{
@@ -1094,7 +1094,7 @@ template<typename Lhs, typename Rhs, int ProductTag, typename MatrixShape>
struct generic_product_impl<Lhs, Rhs, TranspositionsShape, MatrixShape, ProductTag>
{
template<typename Dest>
static void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs)
static EIGEN_DEVICE_FUNC void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs)
{
transposition_matrix_product<Rhs, OnTheLeft, false, MatrixShape>::run(dst, lhs, rhs);
}
@@ -1104,7 +1104,7 @@ template<typename Lhs, typename Rhs, int ProductTag, typename MatrixShape>
struct generic_product_impl<Lhs, Rhs, MatrixShape, TranspositionsShape, ProductTag>
{
template<typename Dest>
static void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs)
static EIGEN_DEVICE_FUNC void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs)
{
transposition_matrix_product<Lhs, OnTheRight, false, MatrixShape>::run(dst, rhs, lhs);
}
@@ -1115,7 +1115,7 @@ template<typename Lhs, typename Rhs, int ProductTag, typename MatrixShape>
struct generic_product_impl<Transpose<Lhs>, Rhs, TranspositionsShape, MatrixShape, ProductTag>
{
template<typename Dest>
static void evalTo(Dest& dst, const Transpose<Lhs>& lhs, const Rhs& rhs)
static EIGEN_DEVICE_FUNC void evalTo(Dest& dst, const Transpose<Lhs>& lhs, const Rhs& rhs)
{
transposition_matrix_product<Rhs, OnTheLeft, true, MatrixShape>::run(dst, lhs.nestedExpression(), rhs);
}
@@ -1125,7 +1125,7 @@ template<typename Lhs, typename Rhs, int ProductTag, typename MatrixShape>
struct generic_product_impl<Lhs, Transpose<Rhs>, MatrixShape, TranspositionsShape, ProductTag>
{
template<typename Dest>
static void evalTo(Dest& dst, const Lhs& lhs, const Transpose<Rhs>& rhs)
static EIGEN_DEVICE_FUNC void evalTo(Dest& dst, const Lhs& lhs, const Transpose<Rhs>& rhs)
{
transposition_matrix_product<Lhs, OnTheRight, true, MatrixShape>::run(dst, rhs.nestedExpression(), lhs);
}

24
Eigen/src/Core/Random.h
View File

@@ -10,7 +10,7 @@
#ifndef EIGEN_RANDOM_H
#define EIGEN_RANDOM_H
namespace Eigen {
namespace Eigen {
namespace internal {
@@ -29,16 +29,16 @@ struct functor_traits<scalar_random_op<Scalar> >
*
* Numbers are uniformly spread through their whole definition range for integer types,
* and in the [-1:1] range for floating point scalar types.
*
*
* The parameters \a rows and \a cols are the number of rows and of columns of
* the returned matrix. Must be compatible with this MatrixBase type.
*
* \not_reentrant
*
*
* This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
* it is redundant to pass \a rows and \a cols as arguments, so Random() should be used
* instead.
*
*
*
* Example: \include MatrixBase_random_int_int.cpp
* Output: \verbinclude MatrixBase_random_int_int.out
@@ -46,7 +46,7 @@ struct functor_traits<scalar_random_op<Scalar> >
* This expression has the "evaluate before nesting" flag so that it will be evaluated into
* a temporary matrix whenever it is nested in a larger expression. This prevents unexpected
* behavior with expressions involving random matrices.
*
*
* See DenseBase::NullaryExpr(Index, const CustomNullaryOp&) for an example using C++11 random generators.
*
* \sa DenseBase::setRandom(), DenseBase::Random(Index), DenseBase::Random()
@@ -93,7 +93,7 @@ DenseBase<Derived>::Random(Index size)
*
* Numbers are uniformly spread through their whole definition range for integer types,
* and in the [-1:1] range for floating point scalar types.
*
*
* This variant is only for fixed-size MatrixBase types. For dynamic-size types, you
* need to use the variants taking size arguments.
*
@@ -103,7 +103,7 @@ DenseBase<Derived>::Random(Index size)
* This expression has the "evaluate before nesting" flag so that it will be evaluated into
* a temporary matrix whenever it is nested in a larger expression. This prevents unexpected
* behavior with expressions involving random matrices.
*
*
* \not_reentrant
*
* \sa DenseBase::setRandom(), DenseBase::Random(Index,Index), DenseBase::Random(Index)
@@ -119,16 +119,16 @@ DenseBase<Derived>::Random()
*
* Numbers are uniformly spread through their whole definition range for integer types,
* and in the [-1:1] range for floating point scalar types.
*
*
* \not_reentrant
*
*
* Example: \include MatrixBase_setRandom.cpp
* Output: \verbinclude MatrixBase_setRandom.out
*
* \sa class CwiseNullaryOp, setRandom(Index), setRandom(Index,Index)
*/
template<typename Derived>
inline Derived& DenseBase<Derived>::setRandom()
EIGEN_DEVICE_FUNC inline Derived& DenseBase<Derived>::setRandom()
{
return *this = Random(rows(), cols());
}
@@ -137,7 +137,7 @@ inline Derived& DenseBase<Derived>::setRandom()
*
* Numbers are uniformly spread through their whole definition range for integer types,
* and in the [-1:1] range for floating point scalar types.
*
*
* \only_for_vectors
* \not_reentrant
*
@@ -160,7 +160,7 @@ PlainObjectBase<Derived>::setRandom(Index newSize)
* and in the [-1:1] range for floating point scalar types.
*
* \not_reentrant
*
*
* \param rows the new number of rows
* \param cols the new number of columns
*

38
Eigen/src/Core/Redux.h
View File

@@ -11,7 +11,7 @@
#ifndef EIGEN_REDUX_H
#define EIGEN_REDUX_H
namespace Eigen {
namespace Eigen {
namespace internal {
@@ -60,7 +60,7 @@ public:
enum {
Unrolling = Cost <= UnrollingLimit ? CompleteUnrolling : NoUnrolling
};
#ifdef EIGEN_DEBUG_ASSIGN
static void debug()
{
@@ -128,7 +128,7 @@ template<typename Func, typename Derived, int Start>
struct redux_novec_unroller<Func, Derived, Start, 0>
{
typedef typename Derived::Scalar Scalar;
EIGEN_DEVICE_FUNC
EIGEN_DEVICE_FUNC
static EIGEN_STRONG_INLINE Scalar run(const Derived&, const Func&) { return Scalar(); }
};
@@ -215,7 +215,7 @@ struct redux_impl<Func, Derived, LinearVectorizedTraversal, NoUnrolling>
static Scalar run(const Derived &mat, const Func& func)
{
const Index size = mat.size();
const Index packetSize = redux_traits<Func, Derived>::PacketSize;
const int packetAlignment = unpacket_traits<PacketScalar>::alignment;
enum {
@@ -336,12 +336,12 @@ class redux_evaluator
public:
typedef _XprType XprType;
EIGEN_DEVICE_FUNC explicit redux_evaluator(const XprType &xpr) : m_evaluator(xpr), m_xpr(xpr) {}
typedef typename XprType::Scalar Scalar;
typedef typename XprType::CoeffReturnType CoeffReturnType;
typedef typename XprType::PacketScalar PacketScalar;
typedef typename XprType::PacketReturnType PacketReturnType;
enum {
MaxRowsAtCompileTime = XprType::MaxRowsAtCompileTime,
MaxColsAtCompileTime = XprType::MaxColsAtCompileTime,
@@ -353,7 +353,7 @@ public:
CoeffReadCost = evaluator<XprType>::CoeffReadCost,
Alignment = evaluator<XprType>::Alignment
};
EIGEN_DEVICE_FUNC Index rows() const { return m_xpr.rows(); }
EIGEN_DEVICE_FUNC Index cols() const { return m_xpr.cols(); }
EIGEN_DEVICE_FUNC Index size() const { return m_xpr.size(); }
@@ -375,17 +375,17 @@ public:
template<int LoadMode, typename PacketType>
PacketType packet(Index index) const
{ return m_evaluator.template packet<LoadMode,PacketType>(index); }
EIGEN_DEVICE_FUNC
CoeffReturnType coeffByOuterInner(Index outer, Index inner) const
{ return m_evaluator.coeff(IsRowMajor ? outer : inner, IsRowMajor ? inner : outer); }
template<int LoadMode, typename PacketType>
PacketType packetByOuterInner(Index outer, Index inner) const
{ return m_evaluator.template packet<LoadMode,PacketType>(IsRowMajor ? outer : inner, IsRowMajor ? inner : outer); }
const XprType & nestedExpression() const { return m_xpr; }
protected:
internal::evaluator<XprType> m_evaluator;
const XprType &m_xpr;
@@ -407,14 +407,14 @@ protected:
*/
template<typename Derived>
template<typename Func>
EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
DenseBase<Derived>::redux(const Func& func) const
{
eigen_assert(this->rows()>0 && this->cols()>0 && "you are using an empty matrix");
typedef typename internal::redux_evaluator<Derived> ThisEvaluator;
ThisEvaluator thisEval(derived());
return internal::redux_impl<Func, ThisEvaluator>::run(thisEval, func);
}
@@ -422,7 +422,7 @@ DenseBase<Derived>::redux(const Func& func) const
* \warning the result is undefined if \c *this contains NaN.
*/
template<typename Derived>
EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
DenseBase<Derived>::minCoeff() const
{
return derived().redux(Eigen::internal::scalar_min_op<Scalar,Scalar>());
@@ -432,7 +432,7 @@ DenseBase<Derived>::minCoeff() const
* \warning the result is undefined if \c *this contains NaN.
*/
template<typename Derived>
EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
DenseBase<Derived>::maxCoeff() const
{
return derived().redux(Eigen::internal::scalar_max_op<Scalar,Scalar>());
@@ -445,7 +445,7 @@ DenseBase<Derived>::maxCoeff() const
* \sa trace(), prod(), mean()
*/
template<typename Derived>
EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
DenseBase<Derived>::sum() const
{
if(SizeAtCompileTime==0 || (SizeAtCompileTime==Dynamic && size()==0))
@@ -458,7 +458,7 @@ DenseBase<Derived>::sum() const
* \sa trace(), prod(), sum()
*/
template<typename Derived>
EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
DenseBase<Derived>::mean() const
{
#ifdef __INTEL_COMPILER
@@ -479,7 +479,7 @@ DenseBase<Derived>::mean() const
* \sa sum(), mean(), trace()
*/
template<typename Derived>
EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
DenseBase<Derived>::prod() const
{
if(SizeAtCompileTime==0 || (SizeAtCompileTime==Dynamic && size()==0))
@@ -494,7 +494,7 @@ DenseBase<Derived>::prod() const
* \sa diagonal(), sum()
*/
template<typename Derived>
EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
MatrixBase<Derived>::trace() const
{
return derived().diagonal().sum();

12
Eigen/src/Core/Replicate.h
View File

@@ -10,7 +10,7 @@
#ifndef EIGEN_REPLICATE_H
#define EIGEN_REPLICATE_H
namespace Eigen {
namespace Eigen {
namespace internal {
template<typename MatrixType,int RowFactor,int ColFactor>
@@ -35,7 +35,7 @@ struct traits<Replicate<MatrixType,RowFactor,ColFactor> >
IsRowMajor = MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1 ? 1
: MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1 ? 0
: (MatrixType::Flags & RowMajorBit) ? 1 : 0,
// FIXME enable DirectAccess with negative strides?
Flags = IsRowMajor ? RowMajorBit : 0
};
@@ -95,8 +95,8 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
EIGEN_DEVICE_FUNC
const _MatrixTypeNested& nestedExpression() const
{
return m_matrix;
{
return m_matrix;
}
protected:
@@ -115,7 +115,7 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
*/
template<typename Derived>
template<int RowFactor, int ColFactor>
const Replicate<Derived,RowFactor,ColFactor>
EIGEN_DEVICE_FUNC const Replicate<Derived,RowFactor,ColFactor>
DenseBase<Derived>::replicate() const
{
return Replicate<Derived,RowFactor,ColFactor>(derived());
@@ -130,7 +130,7 @@ DenseBase<Derived>::replicate() const
* \sa VectorwiseOp::replicate(), DenseBase::replicate(), class Replicate
*/
template<typename ExpressionType, int Direction>
const typename VectorwiseOp<ExpressionType,Direction>::ReplicateReturnType
EIGEN_DEVICE_FUNC const typename VectorwiseOp<ExpressionType,Direction>::ReplicateReturnType
VectorwiseOp<ExpressionType,Direction>::replicate(Index factor) const
{
return typename VectorwiseOp<ExpressionType,Direction>::ReplicateReturnType

6
Eigen/src/Core/ReturnByValue.h
View File

@@ -79,7 +79,7 @@ template<typename Derived> class ReturnByValue
template<typename Derived>
template<typename OtherDerived>
Derived& DenseBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
EIGEN_DEVICE_FUNC Derived& DenseBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
{
other.evalTo(derived());
return derived();
@@ -90,7 +90,7 @@ namespace internal {
// Expression is evaluated in a temporary; default implementation of Assignment is bypassed so that
// when a ReturnByValue expression is assigned, the evaluator is not constructed.
// TODO: Finalize port to new regime; ReturnByValue should not exist in the expression world
template<typename Derived>
struct evaluator<ReturnByValue<Derived> >
: public evaluator<typename internal::traits<Derived>::ReturnType>
@@ -98,7 +98,7 @@ struct evaluator<ReturnByValue<Derived> >
typedef ReturnByValue<Derived> XprType;
typedef typename internal::traits<Derived>::ReturnType PlainObject;
typedef evaluator<PlainObject> Base;
EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr)
: m_result(xpr.rows(), xpr.cols())
{

14
Eigen/src/Core/Reverse.h
View File

@@ -12,7 +12,7 @@
#ifndef EIGEN_REVERSE_H
#define EIGEN_REVERSE_H
namespace Eigen {
namespace Eigen {
namespace internal {
@@ -44,7 +44,7 @@ template<typename PacketType> struct reverse_packet_cond<PacketType,false>
static inline PacketType run(const PacketType& x) { return x; }
};
} // end namespace internal
} // end namespace internal
/** \class Reverse
* \ingroup Core_Module
@@ -98,7 +98,7 @@ template<typename MatrixType, int Direction> class Reverse
}
EIGEN_DEVICE_FUNC const typename internal::remove_all<typename MatrixType::Nested>::type&
nestedExpression() const
nestedExpression() const
{
return m_matrix;
}
@@ -114,7 +114,7 @@ template<typename MatrixType, int Direction> class Reverse
*
*/
template<typename Derived>
inline typename DenseBase<Derived>::ReverseReturnType
EIGEN_DEVICE_FUNC inline typename DenseBase<Derived>::ReverseReturnType
DenseBase<Derived>::reverse()
{
return ReverseReturnType(derived());
@@ -136,7 +136,7 @@ DenseBase<Derived>::reverse()
*
* \sa VectorwiseOp::reverseInPlace(), reverse() */
template<typename Derived>
inline void DenseBase<Derived>::reverseInPlace()
EIGEN_DEVICE_FUNC inline void DenseBase<Derived>::reverseInPlace()
{
if(cols()>rows())
{
@@ -161,7 +161,7 @@ inline void DenseBase<Derived>::reverseInPlace()
}
namespace internal {
template<int Direction>
struct vectorwise_reverse_inplace_impl;
@@ -201,7 +201,7 @@ struct vectorwise_reverse_inplace_impl<Horizontal>
*
* \sa DenseBase::reverseInPlace(), reverse() */
template<typename ExpressionType, int Direction>
void VectorwiseOp<ExpressionType,Direction>::reverseInPlace()
EIGEN_DEVICE_FUNC void VectorwiseOp<ExpressionType,Direction>::reverseInPlace()
{
internal::vectorwise_reverse_inplace_impl<Direction>::run(_expression().const_cast_derived());
}

22
Eigen/src/Core/SelfAdjointView.h
View File

@@ -10,7 +10,7 @@
#ifndef EIGEN_SELFADJOINTMATRIX_H
#define EIGEN_SELFADJOINTMATRIX_H
namespace Eigen {
namespace Eigen {
/** \class SelfAdjointView
* \ingroup Core_Module
@@ -58,7 +58,7 @@ template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
typedef MatrixTypeNestedCleaned NestedExpression;
/** \brief The type of coefficients in this matrix */
typedef typename internal::traits<SelfAdjointView>::Scalar Scalar;
typedef typename internal::traits<SelfAdjointView>::Scalar Scalar;
typedef typename MatrixType::StorageIndex StorageIndex;
typedef typename internal::remove_all<typename MatrixType::ConjugateReturnType>::type MatrixConjugateReturnType;
@@ -131,7 +131,7 @@ template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
{
return Product<OtherDerived,SelfAdjointView>(lhs.derived(),rhs);
}
friend EIGEN_DEVICE_FUNC
const SelfAdjointView<const EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar,MatrixType,product),UpLo>
operator*(const Scalar& s, const SelfAdjointView& mat)
@@ -287,17 +287,17 @@ protected:
using Base::m_src;
using Base::m_functor;
public:
typedef typename Base::DstEvaluatorType DstEvaluatorType;
typedef typename Base::SrcEvaluatorType SrcEvaluatorType;
typedef typename Base::Scalar Scalar;
typedef typename Base::AssignmentTraits AssignmentTraits;
EIGEN_DEVICE_FUNC triangular_dense_assignment_kernel(DstEvaluatorType &dst, const SrcEvaluatorType &src, const Functor &func, DstXprType& dstExpr)
: Base(dst, src, func, dstExpr)
{}
EIGEN_DEVICE_FUNC void assignCoeff(Index row, Index col)
{
eigen_internal_assert(row!=col);
@@ -305,12 +305,12 @@ public:
m_functor.assignCoeff(m_dst.coeffRef(row,col), tmp);
m_functor.assignCoeff(m_dst.coeffRef(col,row), numext::conj(tmp));
}
EIGEN_DEVICE_FUNC void assignDiagonalCoeff(Index id)
{
Base::assignCoeff(id,id);
}
EIGEN_DEVICE_FUNC void assignOppositeCoeff(Index, Index)
{ eigen_internal_assert(false && "should never be called"); }
};
@@ -324,7 +324,7 @@ public:
/** This is the const version of MatrixBase::selfadjointView() */
template<typename Derived>
template<unsigned int UpLo>
typename MatrixBase<Derived>::template ConstSelfAdjointViewReturnType<UpLo>::Type
EIGEN_DEVICE_FUNC typename MatrixBase<Derived>::template ConstSelfAdjointViewReturnType<UpLo>::Type
MatrixBase<Derived>::selfadjointView() const
{
return typename ConstSelfAdjointViewReturnType<UpLo>::Type(derived());
@@ -341,7 +341,7 @@ MatrixBase<Derived>::selfadjointView() const
*/
template<typename Derived>
template<unsigned int UpLo>
typename MatrixBase<Derived>::template SelfAdjointViewReturnType<UpLo>::Type
EIGEN_DEVICE_FUNC typename MatrixBase<Derived>::template SelfAdjointViewReturnType<UpLo>::Type
MatrixBase<Derived>::selfadjointView()
{
return typename SelfAdjointViewReturnType<UpLo>::Type(derived());

26
Eigen/src/Core/Solve.h
View File

@@ -13,7 +13,7 @@
namespace Eigen {
template<typename Decomposition, typename RhsType, typename StorageKind> class SolveImpl;
/** \class Solve
* \ingroup Core_Module
*
@@ -64,11 +64,11 @@ class Solve : public SolveImpl<Decomposition,RhsType,typename internal::traits<R
public:
typedef typename internal::traits<Solve>::PlainObject PlainObject;
typedef typename internal::traits<Solve>::StorageIndex StorageIndex;
Solve(const Decomposition &dec, const RhsType &rhs)
: m_dec(dec), m_rhs(rhs)
{}
EIGEN_DEVICE_FUNC Index rows() const { return m_dec.cols(); }
EIGEN_DEVICE_FUNC Index cols() const { return m_rhs.cols(); }
@@ -87,14 +87,14 @@ class SolveImpl<Decomposition,RhsType,Dense>
: public MatrixBase<Solve<Decomposition,RhsType> >
{
typedef Solve<Decomposition,RhsType> Derived;
public:
typedef MatrixBase<Solve<Decomposition,RhsType> > Base;
EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
private:
Scalar coeff(Index row, Index col) const;
Scalar coeff(Index i) const;
};
@@ -119,15 +119,15 @@ struct evaluator<Solve<Decomposition,RhsType> >
typedef evaluator<PlainObject> Base;
enum { Flags = Base::Flags | EvalBeforeNestingBit };
EIGEN_DEVICE_FUNC explicit evaluator(const SolveType& solve)
: m_result(solve.rows(), solve.cols())
{
::new (static_cast<Base*>(this)) Base(m_result);
solve.dec()._solve_impl(solve.rhs(), m_result);
}
protected:
protected:
PlainObject m_result;
};
@@ -137,7 +137,7 @@ template<typename DstXprType, typename DecType, typename RhsType, typename Scala
struct Assignment<DstXprType, Solve<DecType,RhsType>, internal::assign_op<Scalar,Scalar>, Dense2Dense>
{
typedef Solve<DecType,RhsType> SrcXprType;
static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &)
static EIGEN_DEVICE_FUNC void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &)
{
Index dstRows = src.rows();
Index dstCols = src.cols();
@@ -153,7 +153,7 @@ template<typename DstXprType, typename DecType, typename RhsType, typename Scala
struct Assignment<DstXprType, Solve<Transpose<const DecType>,RhsType>, internal::assign_op<Scalar,Scalar>, Dense2Dense>
{
typedef Solve<Transpose<const DecType>,RhsType> SrcXprType;
static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &)
static EIGEN_DEVICE_FUNC void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &)
{
Index dstRows = src.rows();
Index dstCols = src.cols();
@@ -170,13 +170,13 @@ struct Assignment<DstXprType, Solve<CwiseUnaryOp<internal::scalar_conjugate_op<t
internal::assign_op<Scalar,Scalar>, Dense2Dense>
{
typedef Solve<CwiseUnaryOp<internal::scalar_conjugate_op<typename DecType::Scalar>, const Transpose<const DecType> >,RhsType> SrcXprType;
static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &)
static EIGEN_DEVICE_FUNC void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &)
{
Index dstRows = src.rows();
Index dstCols = src.cols();
if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
dst.resize(dstRows, dstCols);
src.dec().nestedExpression().nestedExpression().template _solve_impl_transposed<true>(src.rhs(), dst);
}
};

10
Eigen/src/Core/SolveTriangular.h
View File

@@ -10,7 +10,7 @@
#ifndef EIGEN_SOLVETRIANGULAR_H
#define EIGEN_SOLVETRIANGULAR_H
namespace Eigen {
namespace Eigen {
namespace internal {
@@ -64,7 +64,7 @@ struct triangular_solver_selector<Lhs,Rhs,Side,Mode,NoUnrolling,1>
ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhs,rhs.size(),
(useRhsDirectly ? rhs.data() : 0));
if(!useRhsDirectly)
MappedRhs(actualRhs,rhs.size()) = rhs;
@@ -148,7 +148,7 @@ struct triangular_solver_selector<Lhs,Rhs,OnTheRight,Mode,CompleteUnrolling,1> {
{
Transpose<const Lhs> trLhs(lhs);
Transpose<Rhs> trRhs(rhs);
triangular_solver_unroller<Transpose<const Lhs>,Transpose<Rhs>,
((Mode&Upper)==Upper ? Lower : Upper) | (Mode&UnitDiag),
0,Rhs::SizeAtCompileTime>::run(trLhs,trRhs);
@@ -164,7 +164,7 @@ struct triangular_solver_selector<Lhs,Rhs,OnTheRight,Mode,CompleteUnrolling,1> {
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename MatrixType, unsigned int Mode>
template<int Side, typename OtherDerived>
void TriangularViewImpl<MatrixType,Mode,Dense>::solveInPlace(const MatrixBase<OtherDerived>& _other) const
EIGEN_DEVICE_FUNC void TriangularViewImpl<MatrixType,Mode,Dense>::solveInPlace(const MatrixBase<OtherDerived>& _other) const
{
OtherDerived& other = _other.const_cast_derived();
eigen_assert( derived().cols() == derived().rows() && ((Side==OnTheLeft && derived().cols() == other.rows()) || (Side==OnTheRight && derived().cols() == other.cols())) );
@@ -187,7 +187,7 @@ void TriangularViewImpl<MatrixType,Mode,Dense>::solveInPlace(const MatrixBase<Ot
template<typename Derived, unsigned int Mode>
template<int Side, typename Other>
const internal::triangular_solve_retval<Side,TriangularView<Derived,Mode>,Other>
EIGEN_DEVICE_FUNC const internal::triangular_solve_retval<Side,TriangularView<Derived,Mode>,Other>
TriangularViewImpl<Derived,Mode,Dense>::solve(const MatrixBase<Other>& other) const
{
return internal::triangular_solve_retval<Side,TriangularViewType,Other>(derived(), other.derived());

14
Eigen/src/Core/Transpose.h
View File

@@ -11,7 +11,7 @@
#ifndef EIGEN_TRANSPOSE_H
#define EIGEN_TRANSPOSE_H
namespace Eigen {
namespace Eigen {
namespace internal {
template<typename MatrixType>
@@ -170,7 +170,7 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
*
* \sa transposeInPlace(), adjoint() */
template<typename Derived>
inline Transpose<Derived>
EIGEN_DEVICE_FUNC inline Transpose<Derived>
DenseBase<Derived>::transpose()
{
return TransposeReturnType(derived());
@@ -182,7 +182,7 @@ DenseBase<Derived>::transpose()
*
* \sa transposeInPlace(), adjoint() */
template<typename Derived>
inline typename DenseBase<Derived>::ConstTransposeReturnType
EIGEN_DEVICE_FUNC inline typename DenseBase<Derived>::ConstTransposeReturnType
DenseBase<Derived>::transpose() const
{
return ConstTransposeReturnType(derived());
@@ -208,7 +208,7 @@ DenseBase<Derived>::transpose() const
*
* \sa adjointInPlace(), transpose(), conjugate(), class Transpose, class internal::scalar_conjugate_op */
template<typename Derived>
inline const typename MatrixBase<Derived>::AdjointReturnType
EIGEN_DEVICE_FUNC inline const typename MatrixBase<Derived>::AdjointReturnType
MatrixBase<Derived>::adjoint() const
{
return AdjointReturnType(this->transpose());
@@ -278,12 +278,12 @@ struct inplace_transpose_selector<MatrixType,false,MatchPacketSize> { // non squ
* Notice however that this method is only useful if you want to replace a matrix by its own transpose.
* If you just need the transpose of a matrix, use transpose().
*
* \note if the matrix is not square, then \c *this must be a resizable matrix.
* \note if the matrix is not square, then \c *this must be a resizable matrix.
* This excludes (non-square) fixed-size matrices, block-expressions and maps.
*
* \sa transpose(), adjoint(), adjointInPlace() */
template<typename Derived>
inline void DenseBase<Derived>::transposeInPlace()
EIGEN_DEVICE_FUNC inline void DenseBase<Derived>::transposeInPlace()
{
eigen_assert((rows() == cols() || (RowsAtCompileTime == Dynamic && ColsAtCompileTime == Dynamic))
&& "transposeInPlace() called on a non-square non-resizable matrix");
@@ -314,7 +314,7 @@ inline void DenseBase<Derived>::transposeInPlace()
*
* \sa transpose(), adjoint(), transposeInPlace() */
template<typename Derived>
inline void MatrixBase<Derived>::adjointInPlace()
EIGEN_DEVICE_FUNC inline void MatrixBase<Derived>::adjointInPlace()
{
derived() = adjoint().eval();
}

98
Eigen/src/Core/TriangularMatrix.h
View File

@@ -11,12 +11,12 @@
#ifndef EIGEN_TRIANGULARMATRIX_H
#define EIGEN_TRIANGULARMATRIX_H
namespace Eigen {
namespace Eigen {
namespace internal {
template<int Side, typename TriangularType, typename Rhs> struct triangular_solve_retval;
}
/** \class TriangularBase
@@ -34,16 +34,16 @@ template<typename Derived> class TriangularBase : public EigenBase<Derived>
ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
MaxRowsAtCompileTime = internal::traits<Derived>::MaxRowsAtCompileTime,
MaxColsAtCompileTime = internal::traits<Derived>::MaxColsAtCompileTime,
SizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::RowsAtCompileTime,
internal::traits<Derived>::ColsAtCompileTime>::ret),
/**< This is equal to the number of coefficients, i.e. the number of
* rows times the number of columns, or to \a Dynamic if this is not
* known at compile-time. \sa RowsAtCompileTime, ColsAtCompileTime */
MaxSizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::MaxRowsAtCompileTime,
internal::traits<Derived>::MaxColsAtCompileTime>::ret)
};
typedef typename internal::traits<Derived>::Scalar Scalar;
typedef typename internal::traits<Derived>::StorageKind StorageKind;
@@ -63,7 +63,7 @@ template<typename Derived> class TriangularBase : public EigenBase<Derived>
inline Index outerStride() const { return derived().outerStride(); }
EIGEN_DEVICE_FUNC
inline Index innerStride() const { return derived().innerStride(); }
// dummy resize function
void resize(Index rows, Index cols)
{
@@ -155,7 +155,7 @@ template<typename Derived> class TriangularBase : public EigenBase<Derived>
* \param MatrixType the type of the object in which we are taking the triangular part
* \param Mode the kind of triangular matrix expression to construct. Can be #Upper,
* #Lower, #UnitUpper, #UnitLower, #StrictlyUpper, or #StrictlyLower.
* This is in fact a bit field; it must have either #Upper or #Lower,
* This is in fact a bit field; it must have either #Upper or #Lower,
* and additionally it may have #UnitDiag or #ZeroDiag or neither.
*
* This class represents a triangular part of a matrix, not necessarily square. Strictly speaking, for rectangular
@@ -197,7 +197,7 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
typedef typename internal::traits<TriangularView>::MatrixTypeNestedNonRef MatrixTypeNestedNonRef;
typedef typename internal::remove_all<typename MatrixType::ConjugateReturnType>::type MatrixConjugateReturnType;
public:
typedef typename internal::traits<TriangularView>::StorageKind StorageKind;
@@ -216,7 +216,7 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
EIGEN_DEVICE_FUNC
explicit inline TriangularView(MatrixType& matrix) : m_matrix(matrix)
{}
EIGEN_INHERIT_ASSIGNMENT_OPERATORS(TriangularView)
/** \copydoc EigenBase::rows() */
@@ -233,7 +233,7 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
/** \returns a reference to the nested expression */
EIGEN_DEVICE_FUNC
NestedExpression& nestedExpression() { return m_matrix; }
typedef TriangularView<const MatrixConjugateReturnType,Mode> ConjugateReturnType;
/** \sa MatrixBase::conjugate() const */
EIGEN_DEVICE_FUNC
@@ -255,7 +255,7 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
typename MatrixType::TransposeReturnType tmp(m_matrix);
return TransposeReturnType(tmp);
}
typedef TriangularView<const typename MatrixType::ConstTransposeReturnType,TransposeMode> ConstTransposeReturnType;
/** \sa MatrixBase::transpose() const */
EIGEN_DEVICE_FUNC
@@ -266,10 +266,10 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
template<typename Other>
EIGEN_DEVICE_FUNC
inline const Solve<TriangularView, Other>
inline const Solve<TriangularView, Other>
solve(const MatrixBase<Other>& other) const
{ return Solve<TriangularView, Other>(*this, other.derived()); }
// workaround MSVC ICE
#if EIGEN_COMP_MSVC
template<int Side, typename Other>
@@ -313,7 +313,7 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
else
return m_matrix.diagonal().prod();
}
protected:
MatrixTypeNested m_matrix;
@@ -375,7 +375,7 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularViewImpl<_Mat
internal::call_assignment_no_alias(derived(), other.derived(), internal::sub_assign_op<Scalar,typename Other::Scalar>());
return derived();
}
/** \sa MatrixBase::operator*=() */
EIGEN_DEVICE_FUNC
TriangularViewType& operator*=(const typename internal::traits<MatrixType>::Scalar& other) { return *this = derived().nestedExpression() * other; }
@@ -556,7 +556,7 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularViewImpl<_Mat
// FIXME should we keep that possibility
template<typename MatrixType, unsigned int Mode>
template<typename OtherDerived>
inline TriangularView<MatrixType, Mode>&
EIGEN_DEVICE_FUNC inline TriangularView<MatrixType, Mode>&
TriangularViewImpl<MatrixType, Mode, Dense>::operator=(const MatrixBase<OtherDerived>& other)
{
internal::call_assignment_no_alias(derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
@@ -566,7 +566,7 @@ TriangularViewImpl<MatrixType, Mode, Dense>::operator=(const MatrixBase<OtherDer
// FIXME should we keep that possibility
template<typename MatrixType, unsigned int Mode>
template<typename OtherDerived>
void TriangularViewImpl<MatrixType, Mode, Dense>::lazyAssign(const MatrixBase<OtherDerived>& other)
EIGEN_DEVICE_FUNC void TriangularViewImpl<MatrixType, Mode, Dense>::lazyAssign(const MatrixBase<OtherDerived>& other)
{
internal::call_assignment_no_alias(derived(), other.template triangularView<Mode>());
}
@@ -575,7 +575,7 @@ void TriangularViewImpl<MatrixType, Mode, Dense>::lazyAssign(const MatrixBase<Ot
template<typename MatrixType, unsigned int Mode>
template<typename OtherDerived>
inline TriangularView<MatrixType, Mode>&
EIGEN_DEVICE_FUNC inline TriangularView<MatrixType, Mode>&
TriangularViewImpl<MatrixType, Mode, Dense>::operator=(const TriangularBase<OtherDerived>& other)
{
eigen_assert(Mode == int(OtherDerived::Mode));
@@ -585,7 +585,7 @@ TriangularViewImpl<MatrixType, Mode, Dense>::operator=(const TriangularBase<Othe
template<typename MatrixType, unsigned int Mode>
template<typename OtherDerived>
void TriangularViewImpl<MatrixType, Mode, Dense>::lazyAssign(const TriangularBase<OtherDerived>& other)
EIGEN_DEVICE_FUNC void TriangularViewImpl<MatrixType, Mode, Dense>::lazyAssign(const TriangularBase<OtherDerived>& other)
{
eigen_assert(Mode == int(OtherDerived::Mode));
internal::call_assignment_no_alias(derived(), other.derived());
@@ -600,7 +600,7 @@ void TriangularViewImpl<MatrixType, Mode, Dense>::lazyAssign(const TriangularBas
* If the matrix is triangular, the opposite part is set to zero. */
template<typename Derived>
template<typename DenseDerived>
void TriangularBase<Derived>::evalTo(MatrixBase<DenseDerived> &other) const
EIGEN_DEVICE_FUNC void TriangularBase<Derived>::evalTo(MatrixBase<DenseDerived> &other) const
{
evalToLazy(other.derived());
}
@@ -626,7 +626,7 @@ void TriangularBase<Derived>::evalTo(MatrixBase<DenseDerived> &other) const
*/
template<typename Derived>
template<unsigned int Mode>
typename MatrixBase<Derived>::template TriangularViewReturnType<Mode>::Type
EIGEN_DEVICE_FUNC typename MatrixBase<Derived>::template TriangularViewReturnType<Mode>::Type
MatrixBase<Derived>::triangularView()
{
return typename TriangularViewReturnType<Mode>::Type(derived());
@@ -635,7 +635,7 @@ MatrixBase<Derived>::triangularView()
/** This is the const version of MatrixBase::triangularView() */
template<typename Derived>
template<unsigned int Mode>
typename MatrixBase<Derived>::template ConstTriangularViewReturnType<Mode>::Type
EIGEN_DEVICE_FUNC typename MatrixBase<Derived>::template ConstTriangularViewReturnType<Mode>::Type
MatrixBase<Derived>::triangularView() const
{
return typename ConstTriangularViewReturnType<Mode>::Type(derived());
@@ -700,7 +700,7 @@ bool MatrixBase<Derived>::isLowerTriangular(const RealScalar& prec) const
namespace internal {
// TODO currently a triangular expression has the form TriangularView<.,.>
// in the future triangular-ness should be defined by the expression traits
// such that Transpose<TriangularView<.,.> > is valid. (currently TriangularBase::transpose() is overloaded to make it work)
@@ -728,7 +728,7 @@ struct Dense2Triangular {};
template<typename Kernel, unsigned int Mode, int UnrollCount, bool ClearOpposite> struct triangular_assignment_loop;
/** \internal Specialization of the dense assignment kernel for triangular matrices.
* The main difference is that the triangular, diagonal, and opposite parts are processed through three different functions.
* \tparam UpLo must be either Lower or Upper
@@ -745,17 +745,17 @@ protected:
using Base::m_src;
using Base::m_functor;
public:
typedef typename Base::DstEvaluatorType DstEvaluatorType;
typedef typename Base::SrcEvaluatorType SrcEvaluatorType;
typedef typename Base::Scalar Scalar;
typedef typename Base::AssignmentTraits AssignmentTraits;
EIGEN_DEVICE_FUNC triangular_dense_assignment_kernel(DstEvaluatorType &dst, const SrcEvaluatorType &src, const Functor &func, DstXprType& dstExpr)
: Base(dst, src, func, dstExpr)
{}
#ifdef EIGEN_INTERNAL_DEBUGGING
EIGEN_DEVICE_FUNC void assignCoeff(Index row, Index col)
{
@@ -765,16 +765,16 @@ public:
#else
using Base::assignCoeff;
#endif
EIGEN_DEVICE_FUNC void assignDiagonalCoeff(Index id)
{
if(Mode==UnitDiag && SetOpposite) m_functor.assignCoeff(m_dst.coeffRef(id,id), Scalar(1));
else if(Mode==ZeroDiag && SetOpposite) m_functor.assignCoeff(m_dst.coeffRef(id,id), Scalar(0));
else if(Mode==0) Base::assignCoeff(id,id);
}
EIGEN_DEVICE_FUNC void assignOppositeCoeff(Index row, Index col)
{
{
eigen_internal_assert(row!=col);
if(SetOpposite)
m_functor.assignCoeff(m_dst.coeffRef(row,col), Scalar(0));
@@ -795,17 +795,17 @@ void call_triangular_assignment_loop(DstXprType& dst, const SrcXprType& src, con
if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
dst.resize(dstRows, dstCols);
DstEvaluatorType dstEvaluator(dst);
typedef triangular_dense_assignment_kernel< Mode&(Lower|Upper),Mode&(UnitDiag|ZeroDiag|SelfAdjoint),SetOpposite,
DstEvaluatorType,SrcEvaluatorType,Functor> Kernel;
Kernel kernel(dstEvaluator, srcEvaluator, func, dst.const_cast_derived());
enum {
unroll = DstXprType::SizeAtCompileTime != Dynamic
&& SrcEvaluatorType::CoeffReadCost < HugeCost
&& DstXprType::SizeAtCompileTime * (DstEvaluatorType::CoeffReadCost+SrcEvaluatorType::CoeffReadCost) / 2 <= EIGEN_UNROLLING_LIMIT
};
triangular_assignment_loop<Kernel, Mode, unroll ? int(DstXprType::SizeAtCompileTime) : Dynamic, SetOpposite>::run(kernel);
}
@@ -827,8 +827,8 @@ struct Assignment<DstXprType, SrcXprType, Functor, Triangular2Triangular>
EIGEN_DEVICE_FUNC static void run(DstXprType &dst, const SrcXprType &src, const Functor &func)
{
eigen_assert(int(DstXprType::Mode) == int(SrcXprType::Mode));
call_triangular_assignment_loop<DstXprType::Mode, false>(dst, src, func);
call_triangular_assignment_loop<DstXprType::Mode, false>(dst, src, func);
}
};
@@ -837,7 +837,7 @@ struct Assignment<DstXprType, SrcXprType, Functor, Triangular2Dense>
{
EIGEN_DEVICE_FUNC static void run(DstXprType &dst, const SrcXprType &src, const Functor &func)
{
call_triangular_assignment_loop<SrcXprType::Mode, (SrcXprType::Mode&SelfAdjoint)==0>(dst, src, func);
call_triangular_assignment_loop<SrcXprType::Mode, (SrcXprType::Mode&SelfAdjoint)==0>(dst, src, func);
}
};
@@ -846,7 +846,7 @@ struct Assignment<DstXprType, SrcXprType, Functor, Dense2Triangular>
{
EIGEN_DEVICE_FUNC static void run(DstXprType &dst, const SrcXprType &src, const Functor &func)
{
call_triangular_assignment_loop<DstXprType::Mode, false>(dst, src, func);
call_triangular_assignment_loop<DstXprType::Mode, false>(dst, src, func);
}
};
@@ -857,19 +857,19 @@ struct triangular_assignment_loop
// FIXME: this is not very clean, perhaps this information should be provided by the kernel?
typedef typename Kernel::DstEvaluatorType DstEvaluatorType;
typedef typename DstEvaluatorType::XprType DstXprType;
enum {
col = (UnrollCount-1) / DstXprType::RowsAtCompileTime,
row = (UnrollCount-1) % DstXprType::RowsAtCompileTime
};
typedef typename Kernel::Scalar Scalar;
EIGEN_DEVICE_FUNC
static inline void run(Kernel &kernel)
{
triangular_assignment_loop<Kernel, Mode, UnrollCount-1, SetOpposite>::run(kernel);
if(row==col)
kernel.assignDiagonalCoeff(row);
else if( ((Mode&Lower) && row>col) || ((Mode&Upper) && row<col) )
@@ -912,10 +912,10 @@ struct triangular_assignment_loop<Kernel, Mode, Dynamic, SetOpposite>
}
else
i = maxi;
if(i<kernel.rows()) // then i==j
kernel.assignDiagonalCoeff(i++);
if (((Mode&Upper) && SetOpposite) || (Mode&Lower))
{
for(; i < kernel.rows(); ++i)
@@ -932,20 +932,20 @@ struct triangular_assignment_loop<Kernel, Mode, Dynamic, SetOpposite>
* If the matrix is triangular, the opposite part is set to zero. */
template<typename Derived>
template<typename DenseDerived>
void TriangularBase<Derived>::evalToLazy(MatrixBase<DenseDerived> &other) const
EIGEN_DEVICE_FUNC void TriangularBase<Derived>::evalToLazy(MatrixBase<DenseDerived> &other) const
{
other.derived().resize(this->rows(), this->cols());
internal::call_triangular_assignment_loop<Derived::Mode,(Derived::Mode&SelfAdjoint)==0 /* SetOpposite */>(other.derived(), derived().nestedExpression());
}
namespace internal {
// Triangular = Product
template< typename DstXprType, typename Lhs, typename Rhs, typename Scalar>
struct Assignment<DstXprType, Product<Lhs,Rhs,DefaultProduct>, internal::assign_op<Scalar,typename Product<Lhs,Rhs,DefaultProduct>::Scalar>, Dense2Triangular>
{
typedef Product<Lhs,Rhs,DefaultProduct> SrcXprType;
static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,typename SrcXprType::Scalar> &)
static EIGEN_DEVICE_FUNC void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,typename SrcXprType::Scalar> &)
{
Index dstRows = src.rows();
Index dstCols = src.cols();
@@ -961,7 +961,7 @@ template< typename DstXprType, typename Lhs, typename Rhs, typename Scalar>
struct Assignment<DstXprType, Product<Lhs,Rhs,DefaultProduct>, internal::add_assign_op<Scalar,typename Product<Lhs,Rhs,DefaultProduct>::Scalar>, Dense2Triangular>
{
typedef Product<Lhs,Rhs,DefaultProduct> SrcXprType;
static void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<Scalar,typename SrcXprType::Scalar> &)
static EIGEN_DEVICE_FUNC void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<Scalar,typename SrcXprType::Scalar> &)
{
dst._assignProduct(src, 1, 1);
}
@@ -972,7 +972,7 @@ template< typename DstXprType, typename Lhs, typename Rhs, typename Scalar>
struct Assignment<DstXprType, Product<Lhs,Rhs,DefaultProduct>, internal::sub_assign_op<Scalar,typename Product<Lhs,Rhs,DefaultProduct>::Scalar>, Dense2Triangular>
{
typedef Product<Lhs,Rhs,DefaultProduct> SrcXprType;
static void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<Scalar,typename SrcXprType::Scalar> &)
static EIGEN_DEVICE_FUNC void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<Scalar,typename SrcXprType::Scalar> &)
{
dst._assignProduct(src, -1, 1);
}

4
Eigen/src/Core/VectorwiseOp.h
View File

@@ -670,7 +670,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
* \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
*/
template<typename Derived>
inline typename DenseBase<Derived>::ColwiseReturnType
EIGEN_DEVICE_FUNC inline typename DenseBase<Derived>::ColwiseReturnType
DenseBase<Derived>::colwise()
{
return ColwiseReturnType(derived());
@@ -684,7 +684,7 @@ DenseBase<Derived>::colwise()
* \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
*/
template<typename Derived>
inline typename DenseBase<Derived>::RowwiseReturnType
EIGEN_DEVICE_FUNC inline typename DenseBase<Derived>::RowwiseReturnType
DenseBase<Derived>::rowwise()
{
return RowwiseReturnType(derived());

4
Eigen/src/Core/arch/CUDA/PacketMath.h
View File

@@ -167,10 +167,10 @@ template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double2 ploadu<double2>(const d
return make_double2(from[0], from[1]);
}
template<> EIGEN_STRONG_INLINE float4 ploaddup<float4>(const float* from) {
template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE float4 ploaddup<float4>(const float* from) {
return make_float4(from[0], from[0], from[1], from[1]);
}
template<> EIGEN_STRONG_INLINE double2 ploaddup<double2>(const double* from) {
template<> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double2 ploaddup<double2>(const double* from) {
return make_double2(from[0], from[0]);
}

28
Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h
View File

@@ -10,7 +10,7 @@
#ifndef EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_H
#define EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_H
namespace Eigen {
namespace Eigen {
template<typename Scalar, typename Index, int StorageOrder, int UpLo, bool ConjLhs, bool ConjRhs>
struct selfadjoint_rank1_update;
@@ -27,7 +27,7 @@ namespace internal {
// forward declarations (defined at the end of this file)
template<typename LhsScalar, typename RhsScalar, typename Index, int mr, int nr, bool ConjLhs, bool ConjRhs, int ResInnerStride, int UpLo>
struct tribb_kernel;
/* Optimized matrix-matrix product evaluating only one triangular half */
template <typename Index,
typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs,
@@ -164,7 +164,7 @@ struct tribb_kernel
if(UpLo==Upper)
gebp_kernel1(res.getSubMapper(0, j), blockA, actual_b, j, depth, actualBlockSize, alpha,
-1, -1, 0, 0);
// selfadjoint micro block
{
Index i = j;
@@ -186,7 +186,7 @@ struct tribb_kernel
if(UpLo==Lower)
{
Index i = j+actualBlockSize;
gebp_kernel1(res.getSubMapper(i, j), blockA+depth*i, actual_b, size-i,
gebp_kernel1(res.getSubMapper(i, j), blockA+depth*i, actual_b, size-i,
depth, actualBlockSize, alpha, -1, -1, 0, 0);
}
}
@@ -207,13 +207,13 @@ struct general_product_to_triangular_selector<MatrixType,ProductType,UpLo,true>
static void run(MatrixType& mat, const ProductType& prod, const typename MatrixType::Scalar& alpha, bool beta)
{
typedef typename MatrixType::Scalar Scalar;
typedef typename internal::remove_all<typename ProductType::LhsNested>::type Lhs;
typedef internal::blas_traits<Lhs> LhsBlasTraits;
typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhs;
typedef typename internal::remove_all<ActualLhs>::type _ActualLhs;
typename internal::add_const_on_value_type<ActualLhs>::type actualLhs = LhsBlasTraits::extract(prod.lhs());
typedef typename internal::remove_all<typename ProductType::RhsNested>::type Rhs;
typedef internal::blas_traits<Rhs> RhsBlasTraits;
typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhs;
@@ -230,18 +230,18 @@ struct general_product_to_triangular_selector<MatrixType,ProductType,UpLo,true>
UseLhsDirectly = _ActualLhs::InnerStrideAtCompileTime==1,
UseRhsDirectly = _ActualRhs::InnerStrideAtCompileTime==1
};
internal::gemv_static_vector_if<Scalar,Lhs::SizeAtCompileTime,Lhs::MaxSizeAtCompileTime,!UseLhsDirectly> static_lhs;
ei_declare_aligned_stack_constructed_variable(Scalar, actualLhsPtr, actualLhs.size(),
(UseLhsDirectly ? const_cast<Scalar*>(actualLhs.data()) : static_lhs.data()));
if(!UseLhsDirectly) Map<typename _ActualLhs::PlainObject>(actualLhsPtr, actualLhs.size()) = actualLhs;
internal::gemv_static_vector_if<Scalar,Rhs::SizeAtCompileTime,Rhs::MaxSizeAtCompileTime,!UseRhsDirectly> static_rhs;
ei_declare_aligned_stack_constructed_variable(Scalar, actualRhsPtr, actualRhs.size(),
(UseRhsDirectly ? const_cast<Scalar*>(actualRhs.data()) : static_rhs.data()));
if(!UseRhsDirectly) Map<typename _ActualRhs::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
selfadjoint_rank1_update<Scalar,Index,StorageOrder,UpLo,
LhsBlasTraits::NeedToConjugate && NumTraits<Scalar>::IsComplex,
RhsBlasTraits::NeedToConjugate && NumTraits<Scalar>::IsComplex>
@@ -259,7 +259,7 @@ struct general_product_to_triangular_selector<MatrixType,ProductType,UpLo,false>
typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhs;
typedef typename internal::remove_all<ActualLhs>::type _ActualLhs;
typename internal::add_const_on_value_type<ActualLhs>::type actualLhs = LhsBlasTraits::extract(prod.lhs());
typedef typename internal::remove_all<typename ProductType::RhsNested>::type Rhs;
typedef internal::blas_traits<Rhs> RhsBlasTraits;
typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhs;
@@ -302,13 +302,13 @@ struct general_product_to_triangular_selector<MatrixType,ProductType,UpLo,false>
template<typename _MatrixType, unsigned int _Mode>
template<typename ProductType>
TriangularView<_MatrixType,_Mode>& TriangularViewImpl<_MatrixType,_Mode,Dense>::_assignProduct(const ProductType& prod, const Scalar& alpha, bool beta)
EIGEN_DEVICE_FUNC TriangularView<_MatrixType,_Mode>& TriangularViewImpl<_MatrixType,_Mode,Dense>::_assignProduct(const ProductType& prod, const Scalar& alpha, bool beta)
{
EIGEN_STATIC_ASSERT((_Mode&UnitDiag)==0, WRITING_TO_TRIANGULAR_PART_WITH_UNIT_DIAGONAL_IS_NOT_SUPPORTED);
eigen_assert(derived().nestedExpression().rows() == prod.rows() && derived().cols() == prod.cols());
general_product_to_triangular_selector<_MatrixType, ProductType, _Mode, internal::traits<ProductType>::InnerSize==1>::run(derived().nestedExpression().const_cast_derived(), prod, alpha, beta);
return derived();
}

8
Eigen/src/Core/products/SelfadjointProduct.h
View File

@@ -16,7 +16,7 @@
* It corresponds to the level 3 SYRK and level 2 SYR Blas routines.
**********************************************************************/
namespace Eigen {
namespace Eigen {
template<typename Scalar, typename Index, int UpLo, bool ConjLhs, bool ConjRhs>
@@ -68,10 +68,10 @@ struct selfadjoint_product_selector<MatrixType,OtherType,UpLo,true>
ei_declare_aligned_stack_constructed_variable(Scalar, actualOtherPtr, other.size(),
(UseOtherDirectly ? const_cast<Scalar*>(actualOther.data()) : static_other.data()));
if(!UseOtherDirectly)
Map<typename _ActualOtherType::PlainObject>(actualOtherPtr, actualOther.size()) = actualOther;
selfadjoint_rank1_update<Scalar,Index,StorageOrder,UpLo,
OtherBlasTraits::NeedToConjugate && NumTraits<Scalar>::IsComplex,
(!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::IsComplex>
@@ -120,7 +120,7 @@ struct selfadjoint_product_selector<MatrixType,OtherType,UpLo,false>
template<typename MatrixType, unsigned int UpLo>
template<typename DerivedU>
SelfAdjointView<MatrixType,UpLo>& SelfAdjointView<MatrixType,UpLo>
EIGEN_DEVICE_FUNC SelfAdjointView<MatrixType,UpLo>& SelfAdjointView<MatrixType,UpLo>
::rankUpdate(const MatrixBase<DerivedU>& u, const Scalar& alpha)
{
selfadjoint_product_selector<MatrixType,DerivedU,UpLo>::run(_expression().const_cast_derived(), u.derived(), alpha);

4
Eigen/src/Core/products/SelfadjointRank2Update.h
View File

@@ -10,7 +10,7 @@
#ifndef EIGEN_SELFADJOINTRANK2UPTADE_H
#define EIGEN_SELFADJOINTRANK2UPTADE_H
namespace Eigen {
namespace Eigen {
namespace internal {
@@ -57,7 +57,7 @@ template<bool Cond, typename T> struct conj_expr_if
template<typename MatrixType, unsigned int UpLo>
template<typename DerivedU, typename DerivedV>
SelfAdjointView<MatrixType,UpLo>& SelfAdjointView<MatrixType,UpLo>
EIGEN_DEVICE_FUNC SelfAdjointView<MatrixType,UpLo>& SelfAdjointView<MatrixType,UpLo>
::rankUpdate(const MatrixBase<DerivedU>& u, const MatrixBase<DerivedV>& v, const Scalar& alpha)
{
typedef internal::blas_traits<DerivedU> UBlasTraits;