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fix a few compilation errors and warnings (ICC)
This commit is contained in:
Gael Guennebaud
parent
14691d6836
commit
f697ea6d30
@ -280,22 +280,22 @@ template<typename ExpressionType, int Direction> class PartialRedux
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{
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return Reverse<ExpressionType, Direction>( _expression() );
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}
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const Replicate<ExpressionType,Direction==Vertical?Dynamic:1,Direction==Horizontal?Dynamic:1>
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replicate(int factor) const;
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template<int Factor>
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const Replicate<ExpressionType,Direction==Vertical?Factor:1,Direction==Horizontal?Factor:1>
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const Replicate<ExpressionType,(Direction==Vertical?Factor:1),(Direction==Horizontal?Factor:1)>
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replicate(int factor = Factor) const;
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/////////// Geometry module ///////////
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const Homogeneous<ExpressionType,Direction> homogeneous() const;
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const Replicate<ExpressionType,Direction==Vertical?Dynamic:1,Direction==Horizontal?Dynamic:1>
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replicate(int factor) const;
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typedef typename ExpressionType::PlainMatrixType CrossReturnType;
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template<typename OtherDerived>
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const CrossReturnType cross(const MatrixBase<OtherDerived>& other) const;
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enum {
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HNormalized_Size = Direction==Vertical ? ei_traits<ExpressionType>::RowsAtCompileTime
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: ei_traits<ExpressionType>::ColsAtCompileTime,
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@ -311,13 +311,13 @@ template<typename ExpressionType, int Direction> class PartialRedux
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Direction==Vertical ? 1 : int(ei_traits<ExpressionType>::RowsAtCompileTime),
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Direction==Horizontal ? 1 : int(ei_traits<ExpressionType>::ColsAtCompileTime)>
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HNormalized_Factors;
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typedef CwiseBinaryOp<ei_scalar_quotient_op<typename ei_traits<ExpressionType>::Scalar>,
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typedef CwiseBinaryOp<ei_scalar_quotient_op<typename ei_traits<ExpressionType>::Scalar>,
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NestByValue<HNormalized_Block>,
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NestByValue<Replicate<NestByValue<HNormalized_Factors>,
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Direction==Vertical ? HNormalized_SizeMinusOne : 1,
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Direction==Horizontal ? HNormalized_SizeMinusOne : 1> > >
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HNormalizedReturnType;
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const HNormalizedReturnType hnormalized() const;
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protected:
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@ -25,7 +25,7 @@
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#ifndef EIGEN_REPLICATE_H
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#define EIGEN_REPLICATE_H
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/** \nonstableyet
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/** \nonstableyet
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* \class Replicate
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*
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* \brief Expression of the multiple replication of a matrix or vector
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@ -70,11 +70,11 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
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EIGEN_GENERIC_PUBLIC_INTERFACE(Replicate)
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inline Replicate(const MatrixType& matrix)
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: m_matrix(matrix)
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: m_matrix(matrix), m_rowFactor(RowFactor), m_colFactor(ColFactor)
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{
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ei_assert(RowFactor!=Dynamic && ColFactor!=Dynamic);
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}
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inline Replicate(const MatrixType& matrix, int rowFactor, int colFactor)
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: m_matrix(matrix), m_rowFactor(rowFactor), m_colFactor(colFactor)
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{}
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@ -93,9 +93,9 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
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const ei_int_if_dynamic<ColFactor> m_colFactor;
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};
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/** \nonstableyet
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/** \nonstableyet
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* \return an expression of the replication of \c *this
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*
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*
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* Example: \include MatrixBase_replicate.cpp
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* Output: \verbinclude MatrixBase_replicate.out
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*
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@ -109,9 +109,9 @@ MatrixBase<Derived>::replicate() const
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return derived();
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}
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/** \nonstableyet
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/** \nonstableyet
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* \return an expression of the replication of \c *this
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*
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*
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* Example: \include MatrixBase_replicate_int_int.cpp
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* Output: \verbinclude MatrixBase_replicate_int_int.out
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*
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@ -124,9 +124,9 @@ MatrixBase<Derived>::replicate(int rowFactor,int colFactor) const
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return Replicate<Derived,Dynamic,Dynamic>(derived(),rowFactor,colFactor);
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}
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/** \nonstableyet
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/** \nonstableyet
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* \return an expression of the replication of each column (or row) of \c *this
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*
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*
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* Example: \include DirectionWise_replicate_int.cpp
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* Output: \verbinclude DirectionWise_replicate_int.out
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*
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@ -140,9 +140,9 @@ PartialRedux<ExpressionType,Direction>::replicate(int factor) const
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(_expression(),Direction==Vertical?factor:1,Direction==Horizontal?factor:1);
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}
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/** \nonstableyet
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/** \nonstableyet
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* \return an expression of the replication of each column (or row) of \c *this
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*
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*
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* Example: \include DirectionWise_replicate.cpp
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* Output: \verbinclude DirectionWise_replicate.out
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*
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@ -156,5 +156,5 @@ PartialRedux<ExpressionType,Direction>::replicate(int factor) const
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return Replicate<ExpressionType,Direction==Vertical?Factor:1,Direction==Horizontal?Factor:1>
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(_expression(),Direction==Vertical?factor:1,Direction==Horizontal?factor:1);
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}
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#endif // EIGEN_REPLICATE_H
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@ -33,8 +33,8 @@ template<typename Lhs, typename Rhs,
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? LowerTriangular
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: (int(Lhs::Flags) & UpperTriangularBit)
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? UpperTriangular
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: -1,
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int StorageOrder = ei_is_part<Lhs>::value ? -1 // this is to solve ambiguous specializations
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: 0xffffff,
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int StorageOrder = ei_is_part<Lhs>::value ? 0xffffff // this is to solve ambiguous specializations
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: int(Lhs::Flags) & (RowMajorBit|SparseBit)
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>
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struct ei_solve_triangular_selector;
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@ -69,7 +69,7 @@ static void ei_cache_friendly_product(
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typedef typename ei_packet_traits<Scalar>::type PacketType;
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#ifndef EIGEN_USE_ALT_PRODUCT
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@ -83,31 +83,31 @@ static void ei_cache_friendly_product(
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// register block size along the N direction
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nr = HalfRegisterCount/2,
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// register block size along the M direction
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mr = 2 * PacketSize,
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// max cache block size along the K direction
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Max_kc = ei_L2_block_traits<EIGEN_TUNE_FOR_CPU_CACHE_SIZE,Scalar>::width,
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// max cache block size along the M direction
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Max_mc = 2*Max_kc
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};
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int kc = std::min<int>(Max_kc,depth); // cache block size along the K direction
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int mc = std::min<int>(Max_mc,rows); // cache block size along the M direction
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Scalar* blockA = ei_aligned_stack_new(Scalar, kc*mc);
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Scalar* blockB = ei_aligned_stack_new(Scalar, kc*cols*PacketSize);
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// number of columns which can be processed by packet of nr columns
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int packet_cols = (cols/nr)*nr;
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// GEMM_VAR1
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for(int k2=0; k2<depth; k2+=kc)
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{
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const int actual_kc = std::min(k2+kc,depth)-k2;
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// we have selected one row panel of rhs and one column panel of lhs
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// pack rhs's panel into a sequential chunk of memory
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// and expand each coeff to a constant packet for further reuse
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@ -132,12 +132,12 @@ static void ei_cache_friendly_product(
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}
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}
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}
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// => GEPP_VAR1
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for(int i2=0; i2<rows; i2+=mc)
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{
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const int actual_mc = std::min(i2+mc,rows)-i2;
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// We have selected a mc x kc block of lhs
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// Let's pack it in a clever order for further purely sequential access
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int count = 0;
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@ -176,11 +176,11 @@ static void ei_cache_friendly_product(
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{
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const Scalar* blA = &blockA[i*actual_kc];
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#ifdef EIGEN_VECTORIZE_SSE
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_mm_prefetch(&blA[0], _MM_HINT_T0);
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_mm_prefetch((const char*)(&blA[0]), _MM_HINT_T0);
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#endif
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// TODO move the res loads to the stores
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// gets res block as register
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PacketType C0, C1, C2, C3, C4, C5, C6, C7;
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C0 = ei_ploadu(&res[(j2+0)*resStride + i2 + i]);
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@ -191,7 +191,7 @@ static void ei_cache_friendly_product(
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C5 = ei_ploadu(&res[(j2+1)*resStride + i2 + i + PacketSize]);
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if(nr==4) C6 = ei_ploadu(&res[(j2+2)*resStride + i2 + i + PacketSize]);
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if(nr==4) C7 = ei_ploadu(&res[(j2+3)*resStride + i2 + i + PacketSize]);
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// performs "inner" product
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// TODO let's check wether the flowing peeled loop could not be
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// optimized via optimal prefetching from one loop to the other
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@ -258,7 +258,7 @@ static void ei_cache_friendly_product(
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if(nr==4) C6 = ei_pmadd(B2, A1, C6);
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if(nr==4) C3 = ei_pmadd(B3, A0, C3);
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if(nr==4) C7 = ei_pmadd(B3, A1, C7);
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blB += 4*nr*PacketSize;
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blA += 4*mr;
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}
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@ -281,7 +281,7 @@ static void ei_cache_friendly_product(
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if(nr==4) C6 = ei_pmadd(B2, A1, C6);
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if(nr==4) C3 = ei_pmadd(B3, A0, C3);
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if(nr==4) C7 = ei_pmadd(B3, A1, C7);
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blB += nr*PacketSize;
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blA += mr;
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}
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@ -299,9 +299,9 @@ static void ei_cache_friendly_product(
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{
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const Scalar* blA = &blockA[i*actual_kc];
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#ifdef EIGEN_VECTORIZE_SSE
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_mm_prefetch(&blA[0], _MM_HINT_T0);
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_mm_prefetch((const char*)(&blA[0]), _MM_HINT_T0);
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#endif
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// gets a 1 x nr res block as registers
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Scalar C0(0), C1(0), C2(0), C3(0);
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const Scalar* blB = &blockB[j2*actual_kc*PacketSize];
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@ -318,7 +318,7 @@ static void ei_cache_friendly_product(
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C1 += B1 * A0;
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if(nr==4) C2 += B2 * A0;
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if(nr==4) C3 += B3 * A0;
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blB += nr*PacketSize;
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}
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res[(j2+0)*resStride + i2 + i] += C0;
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@ -344,10 +344,10 @@ static void ei_cache_friendly_product(
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}
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}
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}
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ei_aligned_stack_delete(Scalar, blockA, kc*mc);
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ei_aligned_stack_delete(Scalar, blockB, kc*cols*PacketSize);
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#else // alternate product from cylmor
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enum {
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@ -364,18 +364,18 @@ static void ei_cache_friendly_product(
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// maximal size of the blocks fitted in L2 cache
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MaxL2BlockSize = ei_L2_block_traits<EIGEN_TUNE_FOR_CPU_CACHE_SIZE,Scalar>::width
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};
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const bool resIsAligned = (PacketSize==1) || (((resStride%PacketSize) == 0) && (size_t(res)%16==0));
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const int remainingSize = depth % PacketSize;
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const int size = depth - remainingSize; // third dimension of the product clamped to packet boundaries
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const int l2BlockRows = MaxL2BlockSize > rows ? rows : 512;
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const int l2BlockCols = MaxL2BlockSize > cols ? cols : 128;
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const int l2BlockSize = MaxL2BlockSize > size ? size : 256;
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const int l2BlockSizeAligned = (1 + std::max(l2BlockSize,l2BlockCols)/PacketSize)*PacketSize;
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const bool needRhsCopy = (PacketSize>1) && ((rhsStride%PacketSize!=0) || (size_t(rhs)%16!=0));
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Scalar* EIGEN_RESTRICT block = new Scalar[l2BlockRows*size];
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// for(int i=0; i<l2BlockRows*l2BlockSize; ++i)
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// block[i] = 0;
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@ -491,7 +491,7 @@ static void ei_cache_friendly_product(
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delete[] block;
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#endif
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}
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#endif // EIGEN_EXTERN_INSTANTIATIONS
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@ -386,7 +386,7 @@ public:
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Transform& fromPositionOrientationScale(const MatrixBase<PositionDerived> &position,
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const OrientationType& orientation, const MatrixBase<ScaleDerived> &scale);
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inline const MatrixType inverse(TransformTraits traits = Mode) const;
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inline const MatrixType inverse(TransformTraits traits = (TransformTraits)Mode) const;
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/** \returns a const pointer to the column major internal matrix */
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const Scalar* data() const { return m_matrix.data(); }
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