Merged in lukier/eigen (pull request PR-234)

Enabling CUDA in Geometry
This commit is contained in:
Benoit Steiner
2016-10-13 18:09:28 +00:00
21 changed files with 429 additions and 409 deletions

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@@ -554,7 +554,7 @@ struct dense_assignment_loop<Kernel, SliceVectorizedTraversal, NoUnrolling>
for(Index inner = alignedEnd; inner<innerSize ; ++inner)
kernel.assignCoeffByOuterInner(outer, inner);
alignedStart = std::min<Index>((alignedStart+alignedStep)%packetSize, innerSize);
alignedStart = numext::mini((alignedStart+alignedStep)%packetSize, innerSize);
}
}
};

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@@ -752,7 +752,7 @@ struct setIdentity_impl<Derived, true>
static EIGEN_STRONG_INLINE Derived& run(Derived& m)
{
m.setZero();
const Index size = (std::min)(m.rows(), m.cols());
const Index size = numext::mini(m.rows(), m.cols());
for(Index i = 0; i < size; ++i) m.coeffRef(i,i) = typename Derived::Scalar(1);
return m;
}

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@@ -290,12 +290,11 @@ MatrixBase<Derived>::asDiagonal() const
template<typename Derived>
bool MatrixBase<Derived>::isDiagonal(const RealScalar& prec) const
{
using std::abs;
if(cols() != rows()) return false;
RealScalar maxAbsOnDiagonal = static_cast<RealScalar>(-1);
for(Index j = 0; j < cols(); ++j)
{
RealScalar absOnDiagonal = abs(coeff(j,j));
RealScalar absOnDiagonal = numext::abs(coeff(j,j));
if(absOnDiagonal > maxAbsOnDiagonal) maxAbsOnDiagonal = absOnDiagonal;
}
for(Index j = 0; j < cols(); ++j)

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@@ -399,12 +399,14 @@ template<typename Derived> class MatrixBase
EIGEN_DEVICE_FUNC
inline PlainObject unitOrthogonal(void) const;
EIGEN_DEVICE_FUNC
inline Matrix<Scalar,3,1> eulerAngles(Index a0, Index a1, Index a2) const;
// put this as separate enum value to work around possible GCC 4.3 bug (?)
enum { HomogeneousReturnTypeDirection = ColsAtCompileTime==1&&RowsAtCompileTime==1 ? ((internal::traits<Derived>::Flags&RowMajorBit)==RowMajorBit ? Horizontal : Vertical)
: ColsAtCompileTime==1 ? Vertical : Horizontal };
typedef Homogeneous<Derived, HomogeneousReturnTypeDirection> HomogeneousReturnType;
EIGEN_DEVICE_FUNC
inline HomogeneousReturnType homogeneous() const;
enum {
@@ -414,7 +416,7 @@ template<typename Derived> class MatrixBase
internal::traits<Derived>::ColsAtCompileTime==1 ? SizeMinusOne : 1,
internal::traits<Derived>::ColsAtCompileTime==1 ? 1 : SizeMinusOne> ConstStartMinusOne;
typedef EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(ConstStartMinusOne,Scalar,quotient) HNormalizedReturnType;
EIGEN_DEVICE_FUNC
inline const HNormalizedReturnType hnormalized() const;
////////// Householder module ///////////

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@@ -916,8 +916,8 @@ struct conservative_resize_like_impl
{
// The storage order does not allow us to use reallocation.
typename Derived::PlainObject tmp(rows,cols);
const Index common_rows = (std::min)(rows, _this.rows());
const Index common_cols = (std::min)(cols, _this.cols());
const Index common_rows = numext::mini(rows, _this.rows());
const Index common_cols = numext::mini(cols, _this.cols());
tmp.block(0,0,common_rows,common_cols) = _this.block(0,0,common_rows,common_cols);
_this.derived().swap(tmp);
}
@@ -950,8 +950,8 @@ struct conservative_resize_like_impl
{
// The storage order does not allow us to use reallocation.
typename Derived::PlainObject tmp(other);
const Index common_rows = (std::min)(tmp.rows(), _this.rows());
const Index common_cols = (std::min)(tmp.cols(), _this.cols());
const Index common_rows = numext::mini(tmp.rows(), _this.rows());
const Index common_cols = numext::mini(tmp.cols(), _this.cols());
tmp.block(0,0,common_rows,common_cols) = _this.block(0,0,common_rows,common_cols);
_this.derived().swap(tmp);
}

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@@ -641,21 +641,20 @@ MatrixBase<Derived>::triangularView() const
template<typename Derived>
bool MatrixBase<Derived>::isUpperTriangular(const RealScalar& prec) const
{
using std::abs;
RealScalar maxAbsOnUpperPart = static_cast<RealScalar>(-1);
for(Index j = 0; j < cols(); ++j)
{
Index maxi = (std::min)(j, rows()-1);
Index maxi = numext::mini(j, rows()-1);
for(Index i = 0; i <= maxi; ++i)
{
RealScalar absValue = abs(coeff(i,j));
RealScalar absValue = numext::abs(coeff(i,j));
if(absValue > maxAbsOnUpperPart) maxAbsOnUpperPart = absValue;
}
}
RealScalar threshold = maxAbsOnUpperPart * prec;
for(Index j = 0; j < cols(); ++j)
for(Index i = j+1; i < rows(); ++i)
if(abs(coeff(i, j)) > threshold) return false;
if(numext::abs(coeff(i, j)) > threshold) return false;
return true;
}
@@ -667,20 +666,19 @@ bool MatrixBase<Derived>::isUpperTriangular(const RealScalar& prec) const
template<typename Derived>
bool MatrixBase<Derived>::isLowerTriangular(const RealScalar& prec) const
{
using std::abs;
RealScalar maxAbsOnLowerPart = static_cast<RealScalar>(-1);
for(Index j = 0; j < cols(); ++j)
for(Index i = j; i < rows(); ++i)
{
RealScalar absValue = abs(coeff(i,j));
RealScalar absValue = numext::abs(coeff(i,j));
if(absValue > maxAbsOnLowerPart) maxAbsOnLowerPart = absValue;
}
RealScalar threshold = maxAbsOnLowerPart * prec;
for(Index j = 1; j < cols(); ++j)
{
Index maxi = (std::min)(j, rows()-1);
Index maxi = numext::mini(j, rows()-1);
for(Index i = 0; i < maxi; ++i)
if(abs(coeff(i, j)) > threshold) return false;
if(numext::abs(coeff(i, j)) > threshold) return false;
}
return true;
}
@@ -893,7 +891,7 @@ struct triangular_assignment_loop<Kernel, Mode, Dynamic, SetOpposite>
{
for(Index j = 0; j < kernel.cols(); ++j)
{
Index maxi = (std::min)(j, kernel.rows());
Index maxi = numext::mini(j, kernel.rows());
Index i = 0;
if (((Mode&Lower) && SetOpposite) || (Mode&Upper))
{

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@@ -625,6 +625,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
/////////// Geometry module ///////////
typedef Homogeneous<ExpressionType,Direction> HomogeneousReturnType;
EIGEN_DEVICE_FUNC
HomogeneousReturnType homogeneous() const;
typedef typename ExpressionType::PlainObject CrossReturnType;
@@ -654,6 +655,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
Direction==Horizontal ? HNormalized_SizeMinusOne : 1> >
HNormalizedReturnType;
EIGEN_DEVICE_FUNC
const HNormalizedReturnType hnormalized() const;
protected:

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@@ -266,7 +266,7 @@ struct scalar_hypot_op<Scalar,Scalar> : binary_op_base<Scalar,Scalar>
// typedef typename NumTraits<Scalar>::Real result_type;
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& _x, const Scalar& _y) const
{
using std::sqrt;
EIGEN_USING_STD_MATH(sqrt)
Scalar p, qp;
if(_x>_y)
{

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@@ -321,7 +321,7 @@ struct functor_traits<scalar_log1p_op<Scalar> > {
*/
template<typename Scalar> struct scalar_log10_op {
EIGEN_EMPTY_STRUCT_CTOR(scalar_log10_op)
EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { using std::log10; return log10(a); }
EIGEN_DEVICE_FUNC inline const Scalar operator() (const Scalar& a) const { EIGEN_USING_STD_MATH(log10) return log10(a); }
template <typename Packet>
EIGEN_DEVICE_FUNC inline Packet packetOp(const Packet& a) const { return internal::plog10(a); }
};