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Adds missing EIGEN_STRONG_INLINE to support MSVC properly inlining small vector calculations

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When working with MSVC often small vector operations are not properly inlined. This behaviour is observed even on the most recent compiler versions.
This commit is contained in:
Basil Fierz 2017-10-26 22:44:28 +02:00
parent 746a6b7b81
commit 624df50945
4 changed files with 26 additions and 23 deletions
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17
Eigen/src/Core/Dot.h
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@ -31,7 +31,8 @@ struct dot_nocheck
typedef scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> conj_prod; typedef scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> conj_prod;
typedef typename conj_prod::result_type ResScalar; typedef typename conj_prod::result_type ResScalar;
EIGEN_DEVICE_FUNC EIGEN_DEVICE_FUNC
static inline ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b) EIGEN_STRONG_INLINE
static ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b)
{ {
return a.template binaryExpr<conj_prod>(b).sum(); return a.template binaryExpr<conj_prod>(b).sum();
} }
@ -43,7 +44,8 @@ struct dot_nocheck<T, U, true>
typedef scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> conj_prod; typedef scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> conj_prod;
typedef typename conj_prod::result_type ResScalar; typedef typename conj_prod::result_type ResScalar;
EIGEN_DEVICE_FUNC EIGEN_DEVICE_FUNC
static inline ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b) EIGEN_STRONG_INLINE
static ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b)
{ {
return a.transpose().template binaryExpr<conj_prod>(b).sum(); return a.transpose().template binaryExpr<conj_prod>(b).sum();
} }
@ -65,6 +67,7 @@ struct dot_nocheck<T, U, true>
template<typename Derived> template<typename Derived>
template<typename OtherDerived> template<typename OtherDerived>
EIGEN_DEVICE_FUNC EIGEN_DEVICE_FUNC
EIGEN_STRONG_INLINE
typename ScalarBinaryOpTraits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType typename ScalarBinaryOpTraits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType
MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const
{ {
@ -102,7 +105,7 @@ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename NumTraits<typename internal::trai
* \sa lpNorm(), dot(), squaredNorm() * \sa lpNorm(), dot(), squaredNorm()
*/ */
template<typename Derived> template<typename Derived>
EIGEN_DEVICE_FUNC 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()); return numext::sqrt(squaredNorm());
} }
@ -117,7 +120,7 @@ EIGEN_DEVICE_FUNC inline typename NumTraits<typename internal::traits<Derived>::
* \sa norm(), normalize() * \sa norm(), normalize()
*/ */
template<typename Derived> template<typename Derived>
EIGEN_DEVICE_FUNC inline const typename MatrixBase<Derived>::PlainObject EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::PlainObject
MatrixBase<Derived>::normalized() const MatrixBase<Derived>::normalized() const
{ {
typedef typename internal::nested_eval<Derived,2>::type _Nested; typedef typename internal::nested_eval<Derived,2>::type _Nested;
@ -139,7 +142,7 @@ MatrixBase<Derived>::normalized() const
* \sa norm(), normalized() * \sa norm(), normalized()
*/ */
template<typename Derived> template<typename Derived>
EIGEN_DEVICE_FUNC inline void MatrixBase<Derived>::normalize() EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void MatrixBase<Derived>::normalize()
{ {
RealScalar z = squaredNorm(); RealScalar z = squaredNorm();
// NOTE: after extensive benchmarking, this conditional does not impact performance, at least on recent x86 CPU // NOTE: after extensive benchmarking, this conditional does not impact performance, at least on recent x86 CPU
@ -160,7 +163,7 @@ EIGEN_DEVICE_FUNC inline void MatrixBase<Derived>::normalize()
* \sa stableNorm(), stableNormalize(), normalized() * \sa stableNorm(), stableNormalize(), normalized()
*/ */
template<typename Derived> template<typename Derived>
EIGEN_DEVICE_FUNC inline const typename MatrixBase<Derived>::PlainObject EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::PlainObject
MatrixBase<Derived>::stableNormalized() const MatrixBase<Derived>::stableNormalized() const
{ {
typedef typename internal::nested_eval<Derived,3>::type _Nested; typedef typename internal::nested_eval<Derived,3>::type _Nested;
@ -185,7 +188,7 @@ MatrixBase<Derived>::stableNormalized() const
* \sa stableNorm(), stableNormalized(), normalize() * \sa stableNorm(), stableNormalized(), normalize()
*/ */
template<typename Derived> template<typename Derived>
EIGEN_DEVICE_FUNC inline void MatrixBase<Derived>::stableNormalize() EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void MatrixBase<Derived>::stableNormalize()
{ {
RealScalar w = cwiseAbs().maxCoeff(); RealScalar w = cwiseAbs().maxCoeff();
RealScalar z = (derived()/w).squaredNorm(); RealScalar z = (derived()/w).squaredNorm();

10
Eigen/src/Core/Product.h
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@ -97,8 +97,8 @@ class Product : public ProductImpl<_Lhs,_Rhs,Option,
&& "if you wanted a coeff-wise or a dot product use the respective explicit functions"); && "if you wanted a coeff-wise or a dot product use the respective explicit functions");
} }
EIGEN_DEVICE_FUNC inline Index rows() const { return m_lhs.rows(); } EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index rows() const { return m_lhs.rows(); }
EIGEN_DEVICE_FUNC inline Index cols() const { return m_rhs.cols(); } EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index cols() const { return m_rhs.cols(); }
EIGEN_DEVICE_FUNC const LhsNestedCleaned& lhs() const { return m_lhs; } EIGEN_DEVICE_FUNC const LhsNestedCleaned& lhs() const { return m_lhs; }
EIGEN_DEVICE_FUNC const RhsNestedCleaned& rhs() const { return m_rhs; } EIGEN_DEVICE_FUNC const RhsNestedCleaned& rhs() const { return m_rhs; }
@ -127,7 +127,7 @@ public:
using Base::derived; using Base::derived;
typedef typename Base::Scalar Scalar; typedef typename Base::Scalar Scalar;
operator const Scalar() const EIGEN_STRONG_INLINE operator const Scalar() const
{ {
return internal::evaluator<ProductXpr>(derived()).coeff(0,0); return internal::evaluator<ProductXpr>(derived()).coeff(0,0);
} }
@ -162,7 +162,7 @@ class ProductImpl<Lhs,Rhs,Option,Dense>
public: public:
EIGEN_DEVICE_FUNC Scalar coeff(Index row, Index col) const EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar coeff(Index row, Index col) const
{ {
EIGEN_STATIC_ASSERT(EnableCoeff, THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS); EIGEN_STATIC_ASSERT(EnableCoeff, THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS);
eigen_assert( (Option==LazyProduct) || (this->rows() == 1 && this->cols() == 1) ); eigen_assert( (Option==LazyProduct) || (this->rows() == 1 && this->cols() == 1) );
@ -170,7 +170,7 @@ class ProductImpl<Lhs,Rhs,Option,Dense>
return internal::evaluator<Derived>(derived()).coeff(row,col); return internal::evaluator<Derived>(derived()).coeff(row,col);
} }
EIGEN_DEVICE_FUNC Scalar coeff(Index i) const EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar coeff(Index i) const
{ {
EIGEN_STATIC_ASSERT(EnableCoeff, THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS); EIGEN_STATIC_ASSERT(EnableCoeff, THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS);
eigen_assert( (Option==LazyProduct) || (this->rows() == 1 && this->cols() == 1) ); eigen_assert( (Option==LazyProduct) || (this->rows() == 1 && this->cols() == 1) );

20
Eigen/src/Core/ProductEvaluators.h
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@ -32,7 +32,7 @@ struct evaluator<Product<Lhs, Rhs, Options> >
typedef Product<Lhs, Rhs, Options> XprType; typedef Product<Lhs, Rhs, Options> XprType;
typedef product_evaluator<XprType> Base; typedef product_evaluator<XprType> Base;
EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr) : Base(xpr) {} EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {}
}; };
// Catch "scalar * ( A * B )" and transform it to "(A*scalar) * B" // Catch "scalar * ( A * B )" and transform it to "(A*scalar) * B"
@ -55,7 +55,7 @@ struct evaluator<CwiseBinaryOp<internal::scalar_product_op<Scalar1,Scalar2>,
const Product<Lhs, Rhs, DefaultProduct> > XprType; const Product<Lhs, Rhs, DefaultProduct> > XprType;
typedef evaluator<Product<EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar1,Lhs,product), Rhs, DefaultProduct> > Base; typedef evaluator<Product<EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar1,Lhs,product), Rhs, DefaultProduct> > Base;
EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr) EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr)
: Base(xpr.lhs().functor().m_other * xpr.rhs().lhs() * xpr.rhs().rhs()) : Base(xpr.lhs().functor().m_other * xpr.rhs().lhs() * xpr.rhs().rhs())
{} {}
}; };
@ -68,7 +68,7 @@ struct evaluator<Diagonal<const Product<Lhs, Rhs, DefaultProduct>, DiagIndex> >
typedef Diagonal<const Product<Lhs, Rhs, DefaultProduct>, DiagIndex> XprType; typedef Diagonal<const Product<Lhs, Rhs, DefaultProduct>, DiagIndex> XprType;
typedef evaluator<Diagonal<const Product<Lhs, Rhs, LazyProduct>, DiagIndex> > Base; typedef evaluator<Diagonal<const Product<Lhs, Rhs, LazyProduct>, DiagIndex> > Base;
EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr) EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr)
: Base(Diagonal<const Product<Lhs, Rhs, LazyProduct>, DiagIndex>( : Base(Diagonal<const Product<Lhs, Rhs, LazyProduct>, DiagIndex>(
Product<Lhs, Rhs, LazyProduct>(xpr.nestedExpression().lhs(), xpr.nestedExpression().rhs()), Product<Lhs, Rhs, LazyProduct>(xpr.nestedExpression().lhs(), xpr.nestedExpression().rhs()),
xpr.index() )) xpr.index() ))
@ -246,19 +246,19 @@ template<typename Lhs, typename Rhs>
struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,InnerProduct> struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,InnerProduct>
{ {
template<typename Dst> template<typename Dst>
static inline void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) static EIGEN_STRONG_INLINE void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{ {
dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
} }
template<typename Dst> template<typename Dst>
static inline void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) static EIGEN_STRONG_INLINE void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{ {
dst.coeffRef(0,0) += (lhs.transpose().cwiseProduct(rhs)).sum(); dst.coeffRef(0,0) += (lhs.transpose().cwiseProduct(rhs)).sum();
} }
template<typename Dst> template<typename Dst>
static void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) static EIGEN_STRONG_INLINE void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{ dst.coeffRef(0,0) -= (lhs.transpose().cwiseProduct(rhs)).sum(); } { dst.coeffRef(0,0) -= (lhs.transpose().cwiseProduct(rhs)).sum(); }
}; };
@ -312,25 +312,25 @@ struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,OuterProduct>
}; };
template<typename Dst> template<typename Dst>
static inline void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) 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>()); internal::outer_product_selector_run(dst, lhs, rhs, set(), is_row_major<Dst>());
} }
template<typename Dst> template<typename Dst>
static inline void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) 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>()); internal::outer_product_selector_run(dst, lhs, rhs, add(), is_row_major<Dst>());
} }
template<typename Dst> template<typename Dst>
static inline void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) 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>()); internal::outer_product_selector_run(dst, lhs, rhs, sub(), is_row_major<Dst>());
} }
template<typename Dst> template<typename Dst>
static inline void scaleAndAddTo(Dst& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha) 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>()); internal::outer_product_selector_run(dst, lhs, rhs, adds(alpha), is_row_major<Dst>());
} }

2
Eigen/src/Core/Redux.h
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@ -407,7 +407,7 @@ protected:
*/ */
template<typename Derived> template<typename Derived>
template<typename Func> template<typename Func>
EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::traits<Derived>::Scalar
DenseBase<Derived>::redux(const Func& func) const DenseBase<Derived>::redux(const Func& func) const
{ {
eigen_assert(this->rows()>0 && this->cols()>0 && "you are using an empty matrix"); eigen_assert(this->rows()>0 && this->cols()>0 && "you are using an empty matrix");