GeneralProduct.h (21679B)
1 // This file is part of Eigen, a lightweight C++ template library 2 // for linear algebra. 3 // 4 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com> 5 // Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr> 6 // 7 // This Source Code Form is subject to the terms of the Mozilla 8 // Public License v. 2.0. If a copy of the MPL was not distributed 9 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 10 11 #ifndef EIGEN_GENERAL_PRODUCT_H 12 #define EIGEN_GENERAL_PRODUCT_H 13 14 namespace Eigen { 15 16 enum { 17 Large = 2, 18 Small = 3 19 }; 20 21 // Define the threshold value to fallback from the generic matrix-matrix product 22 // implementation (heavy) to the lightweight coeff-based product one. 23 // See generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,GemmProduct> 24 // in products/GeneralMatrixMatrix.h for more details. 25 // TODO This threshold should also be used in the compile-time selector below. 26 #ifndef EIGEN_GEMM_TO_COEFFBASED_THRESHOLD 27 // This default value has been obtained on a Haswell architecture. 28 #define EIGEN_GEMM_TO_COEFFBASED_THRESHOLD 20 29 #endif 30 31 namespace internal { 32 33 template<int Rows, int Cols, int Depth> struct product_type_selector; 34 35 template<int Size, int MaxSize> struct product_size_category 36 { 37 enum { 38 #ifndef EIGEN_GPU_COMPILE_PHASE 39 is_large = MaxSize == Dynamic || 40 Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD || 41 (Size==Dynamic && MaxSize>=EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD), 42 #else 43 is_large = 0, 44 #endif 45 value = is_large ? Large 46 : Size == 1 ? 1 47 : Small 48 }; 49 }; 50 51 template<typename Lhs, typename Rhs> struct product_type 52 { 53 typedef typename remove_all<Lhs>::type _Lhs; 54 typedef typename remove_all<Rhs>::type _Rhs; 55 enum { 56 MaxRows = traits<_Lhs>::MaxRowsAtCompileTime, 57 Rows = traits<_Lhs>::RowsAtCompileTime, 58 MaxCols = traits<_Rhs>::MaxColsAtCompileTime, 59 Cols = traits<_Rhs>::ColsAtCompileTime, 60 MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(traits<_Lhs>::MaxColsAtCompileTime, 61 traits<_Rhs>::MaxRowsAtCompileTime), 62 Depth = EIGEN_SIZE_MIN_PREFER_FIXED(traits<_Lhs>::ColsAtCompileTime, 63 traits<_Rhs>::RowsAtCompileTime) 64 }; 65 66 // the splitting into different lines of code here, introducing the _select enums and the typedef below, 67 // is to work around an internal compiler error with gcc 4.1 and 4.2. 68 private: 69 enum { 70 rows_select = product_size_category<Rows,MaxRows>::value, 71 cols_select = product_size_category<Cols,MaxCols>::value, 72 depth_select = product_size_category<Depth,MaxDepth>::value 73 }; 74 typedef product_type_selector<rows_select, cols_select, depth_select> selector; 75 76 public: 77 enum { 78 value = selector::ret, 79 ret = selector::ret 80 }; 81 #ifdef EIGEN_DEBUG_PRODUCT 82 static void debug() 83 { 84 EIGEN_DEBUG_VAR(Rows); 85 EIGEN_DEBUG_VAR(Cols); 86 EIGEN_DEBUG_VAR(Depth); 87 EIGEN_DEBUG_VAR(rows_select); 88 EIGEN_DEBUG_VAR(cols_select); 89 EIGEN_DEBUG_VAR(depth_select); 90 EIGEN_DEBUG_VAR(value); 91 } 92 #endif 93 }; 94 95 /* The following allows to select the kind of product at compile time 96 * based on the three dimensions of the product. 97 * This is a compile time mapping from {1,Small,Large}^3 -> {product types} */ 98 // FIXME I'm not sure the current mapping is the ideal one. 99 template<int M, int N> struct product_type_selector<M,N,1> { enum { ret = OuterProduct }; }; 100 template<int M> struct product_type_selector<M, 1, 1> { enum { ret = LazyCoeffBasedProductMode }; }; 101 template<int N> struct product_type_selector<1, N, 1> { enum { ret = LazyCoeffBasedProductMode }; }; 102 template<int Depth> struct product_type_selector<1, 1, Depth> { enum { ret = InnerProduct }; }; 103 template<> struct product_type_selector<1, 1, 1> { enum { ret = InnerProduct }; }; 104 template<> struct product_type_selector<Small,1, Small> { enum { ret = CoeffBasedProductMode }; }; 105 template<> struct product_type_selector<1, Small,Small> { enum { ret = CoeffBasedProductMode }; }; 106 template<> struct product_type_selector<Small,Small,Small> { enum { ret = CoeffBasedProductMode }; }; 107 template<> struct product_type_selector<Small, Small, 1> { enum { ret = LazyCoeffBasedProductMode }; }; 108 template<> struct product_type_selector<Small, Large, 1> { enum { ret = LazyCoeffBasedProductMode }; }; 109 template<> struct product_type_selector<Large, Small, 1> { enum { ret = LazyCoeffBasedProductMode }; }; 110 template<> struct product_type_selector<1, Large,Small> { enum { ret = CoeffBasedProductMode }; }; 111 template<> struct product_type_selector<1, Large,Large> { enum { ret = GemvProduct }; }; 112 template<> struct product_type_selector<1, Small,Large> { enum { ret = CoeffBasedProductMode }; }; 113 template<> struct product_type_selector<Large,1, Small> { enum { ret = CoeffBasedProductMode }; }; 114 template<> struct product_type_selector<Large,1, Large> { enum { ret = GemvProduct }; }; 115 template<> struct product_type_selector<Small,1, Large> { enum { ret = CoeffBasedProductMode }; }; 116 template<> struct product_type_selector<Small,Small,Large> { enum { ret = GemmProduct }; }; 117 template<> struct product_type_selector<Large,Small,Large> { enum { ret = GemmProduct }; }; 118 template<> struct product_type_selector<Small,Large,Large> { enum { ret = GemmProduct }; }; 119 template<> struct product_type_selector<Large,Large,Large> { enum { ret = GemmProduct }; }; 120 template<> struct product_type_selector<Large,Small,Small> { enum { ret = CoeffBasedProductMode }; }; 121 template<> struct product_type_selector<Small,Large,Small> { enum { ret = CoeffBasedProductMode }; }; 122 template<> struct product_type_selector<Large,Large,Small> { enum { ret = GemmProduct }; }; 123 124 } // end namespace internal 125 126 /*********************************************************************** 127 * Implementation of Inner Vector Vector Product 128 ***********************************************************************/ 129 130 // FIXME : maybe the "inner product" could return a Scalar 131 // instead of a 1x1 matrix ?? 132 // Pro: more natural for the user 133 // Cons: this could be a problem if in a meta unrolled algorithm a matrix-matrix 134 // product ends up to a row-vector times col-vector product... To tackle this use 135 // case, we could have a specialization for Block<MatrixType,1,1> with: operator=(Scalar x); 136 137 /*********************************************************************** 138 * Implementation of Outer Vector Vector Product 139 ***********************************************************************/ 140 141 /*********************************************************************** 142 * Implementation of General Matrix Vector Product 143 ***********************************************************************/ 144 145 /* According to the shape/flags of the matrix we have to distinghish 3 different cases: 146 * 1 - the matrix is col-major, BLAS compatible and M is large => call fast BLAS-like colmajor routine 147 * 2 - the matrix is row-major, BLAS compatible and N is large => call fast BLAS-like rowmajor routine 148 * 3 - all other cases are handled using a simple loop along the outer-storage direction. 149 * Therefore we need a lower level meta selector. 150 * Furthermore, if the matrix is the rhs, then the product has to be transposed. 151 */ 152 namespace internal { 153 154 template<int Side, int StorageOrder, bool BlasCompatible> 155 struct gemv_dense_selector; 156 157 } // end namespace internal 158 159 namespace internal { 160 161 template<typename Scalar,int Size,int MaxSize,bool Cond> struct gemv_static_vector_if; 162 163 template<typename Scalar,int Size,int MaxSize> 164 struct gemv_static_vector_if<Scalar,Size,MaxSize,false> 165 { 166 EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Scalar* data() { eigen_internal_assert(false && "should never be called"); return 0; } 167 }; 168 169 template<typename Scalar,int Size> 170 struct gemv_static_vector_if<Scalar,Size,Dynamic,true> 171 { 172 EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Scalar* data() { return 0; } 173 }; 174 175 template<typename Scalar,int Size,int MaxSize> 176 struct gemv_static_vector_if<Scalar,Size,MaxSize,true> 177 { 178 enum { 179 ForceAlignment = internal::packet_traits<Scalar>::Vectorizable, 180 PacketSize = internal::packet_traits<Scalar>::size 181 }; 182 #if EIGEN_MAX_STATIC_ALIGN_BYTES!=0 183 internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize),0,EIGEN_PLAIN_ENUM_MIN(AlignedMax,PacketSize)> m_data; 184 EIGEN_STRONG_INLINE Scalar* data() { return m_data.array; } 185 #else 186 // Some architectures cannot align on the stack, 187 // => let's manually enforce alignment by allocating more data and return the address of the first aligned element. 188 internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize)+(ForceAlignment?EIGEN_MAX_ALIGN_BYTES:0),0> m_data; 189 EIGEN_STRONG_INLINE Scalar* data() { 190 return ForceAlignment 191 ? reinterpret_cast<Scalar*>((internal::UIntPtr(m_data.array) & ~(std::size_t(EIGEN_MAX_ALIGN_BYTES-1))) + EIGEN_MAX_ALIGN_BYTES) 192 : m_data.array; 193 } 194 #endif 195 }; 196 197 // The vector is on the left => transposition 198 template<int StorageOrder, bool BlasCompatible> 199 struct gemv_dense_selector<OnTheLeft,StorageOrder,BlasCompatible> 200 { 201 template<typename Lhs, typename Rhs, typename Dest> 202 static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha) 203 { 204 Transpose<Dest> destT(dest); 205 enum { OtherStorageOrder = StorageOrder == RowMajor ? ColMajor : RowMajor }; 206 gemv_dense_selector<OnTheRight,OtherStorageOrder,BlasCompatible> 207 ::run(rhs.transpose(), lhs.transpose(), destT, alpha); 208 } 209 }; 210 211 template<> struct gemv_dense_selector<OnTheRight,ColMajor,true> 212 { 213 template<typename Lhs, typename Rhs, typename Dest> 214 static inline void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha) 215 { 216 typedef typename Lhs::Scalar LhsScalar; 217 typedef typename Rhs::Scalar RhsScalar; 218 typedef typename Dest::Scalar ResScalar; 219 typedef typename Dest::RealScalar RealScalar; 220 221 typedef internal::blas_traits<Lhs> LhsBlasTraits; 222 typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType; 223 typedef internal::blas_traits<Rhs> RhsBlasTraits; 224 typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType; 225 226 typedef Map<Matrix<ResScalar,Dynamic,1>, EIGEN_PLAIN_ENUM_MIN(AlignedMax,internal::packet_traits<ResScalar>::size)> MappedDest; 227 228 ActualLhsType actualLhs = LhsBlasTraits::extract(lhs); 229 ActualRhsType actualRhs = RhsBlasTraits::extract(rhs); 230 231 ResScalar actualAlpha = combine_scalar_factors(alpha, lhs, rhs); 232 233 // make sure Dest is a compile-time vector type (bug 1166) 234 typedef typename conditional<Dest::IsVectorAtCompileTime, Dest, typename Dest::ColXpr>::type ActualDest; 235 236 enum { 237 // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1 238 // on, the other hand it is good for the cache to pack the vector anyways... 239 EvalToDestAtCompileTime = (ActualDest::InnerStrideAtCompileTime==1), 240 ComplexByReal = (NumTraits<LhsScalar>::IsComplex) && (!NumTraits<RhsScalar>::IsComplex), 241 MightCannotUseDest = ((!EvalToDestAtCompileTime) || ComplexByReal) && (ActualDest::MaxSizeAtCompileTime!=0) 242 }; 243 244 typedef const_blas_data_mapper<LhsScalar,Index,ColMajor> LhsMapper; 245 typedef const_blas_data_mapper<RhsScalar,Index,RowMajor> RhsMapper; 246 RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha); 247 248 if(!MightCannotUseDest) 249 { 250 // shortcut if we are sure to be able to use dest directly, 251 // this ease the compiler to generate cleaner and more optimzized code for most common cases 252 general_matrix_vector_product 253 <Index,LhsScalar,LhsMapper,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run( 254 actualLhs.rows(), actualLhs.cols(), 255 LhsMapper(actualLhs.data(), actualLhs.outerStride()), 256 RhsMapper(actualRhs.data(), actualRhs.innerStride()), 257 dest.data(), 1, 258 compatibleAlpha); 259 } 260 else 261 { 262 gemv_static_vector_if<ResScalar,ActualDest::SizeAtCompileTime,ActualDest::MaxSizeAtCompileTime,MightCannotUseDest> static_dest; 263 264 const bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha)==RealScalar(0)); 265 const bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible; 266 267 ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(), 268 evalToDest ? dest.data() : static_dest.data()); 269 270 if(!evalToDest) 271 { 272 #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN 273 Index size = dest.size(); 274 EIGEN_DENSE_STORAGE_CTOR_PLUGIN 275 #endif 276 if(!alphaIsCompatible) 277 { 278 MappedDest(actualDestPtr, dest.size()).setZero(); 279 compatibleAlpha = RhsScalar(1); 280 } 281 else 282 MappedDest(actualDestPtr, dest.size()) = dest; 283 } 284 285 general_matrix_vector_product 286 <Index,LhsScalar,LhsMapper,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run( 287 actualLhs.rows(), actualLhs.cols(), 288 LhsMapper(actualLhs.data(), actualLhs.outerStride()), 289 RhsMapper(actualRhs.data(), actualRhs.innerStride()), 290 actualDestPtr, 1, 291 compatibleAlpha); 292 293 if (!evalToDest) 294 { 295 if(!alphaIsCompatible) 296 dest.matrix() += actualAlpha * MappedDest(actualDestPtr, dest.size()); 297 else 298 dest = MappedDest(actualDestPtr, dest.size()); 299 } 300 } 301 } 302 }; 303 304 template<> struct gemv_dense_selector<OnTheRight,RowMajor,true> 305 { 306 template<typename Lhs, typename Rhs, typename Dest> 307 static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha) 308 { 309 typedef typename Lhs::Scalar LhsScalar; 310 typedef typename Rhs::Scalar RhsScalar; 311 typedef typename Dest::Scalar ResScalar; 312 313 typedef internal::blas_traits<Lhs> LhsBlasTraits; 314 typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType; 315 typedef internal::blas_traits<Rhs> RhsBlasTraits; 316 typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType; 317 typedef typename internal::remove_all<ActualRhsType>::type ActualRhsTypeCleaned; 318 319 typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(lhs); 320 typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(rhs); 321 322 ResScalar actualAlpha = combine_scalar_factors(alpha, lhs, rhs); 323 324 enum { 325 // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1 326 // on, the other hand it is good for the cache to pack the vector anyways... 327 DirectlyUseRhs = ActualRhsTypeCleaned::InnerStrideAtCompileTime==1 || ActualRhsTypeCleaned::MaxSizeAtCompileTime==0 328 }; 329 330 gemv_static_vector_if<RhsScalar,ActualRhsTypeCleaned::SizeAtCompileTime,ActualRhsTypeCleaned::MaxSizeAtCompileTime,!DirectlyUseRhs> static_rhs; 331 332 ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,actualRhs.size(), 333 DirectlyUseRhs ? const_cast<RhsScalar*>(actualRhs.data()) : static_rhs.data()); 334 335 if(!DirectlyUseRhs) 336 { 337 #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN 338 Index size = actualRhs.size(); 339 EIGEN_DENSE_STORAGE_CTOR_PLUGIN 340 #endif 341 Map<typename ActualRhsTypeCleaned::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs; 342 } 343 344 typedef const_blas_data_mapper<LhsScalar,Index,RowMajor> LhsMapper; 345 typedef const_blas_data_mapper<RhsScalar,Index,ColMajor> RhsMapper; 346 general_matrix_vector_product 347 <Index,LhsScalar,LhsMapper,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run( 348 actualLhs.rows(), actualLhs.cols(), 349 LhsMapper(actualLhs.data(), actualLhs.outerStride()), 350 RhsMapper(actualRhsPtr, 1), 351 dest.data(), dest.col(0).innerStride(), //NOTE if dest is not a vector at compile-time, then dest.innerStride() might be wrong. (bug 1166) 352 actualAlpha); 353 } 354 }; 355 356 template<> struct gemv_dense_selector<OnTheRight,ColMajor,false> 357 { 358 template<typename Lhs, typename Rhs, typename Dest> 359 static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha) 360 { 361 EIGEN_STATIC_ASSERT((!nested_eval<Lhs,1>::Evaluate),EIGEN_INTERNAL_COMPILATION_ERROR_OR_YOU_MADE_A_PROGRAMMING_MISTAKE); 362 // TODO if rhs is large enough it might be beneficial to make sure that dest is sequentially stored in memory, otherwise use a temp 363 typename nested_eval<Rhs,1>::type actual_rhs(rhs); 364 const Index size = rhs.rows(); 365 for(Index k=0; k<size; ++k) 366 dest += (alpha*actual_rhs.coeff(k)) * lhs.col(k); 367 } 368 }; 369 370 template<> struct gemv_dense_selector<OnTheRight,RowMajor,false> 371 { 372 template<typename Lhs, typename Rhs, typename Dest> 373 static void run(const Lhs &lhs, const Rhs &rhs, Dest& dest, const typename Dest::Scalar& alpha) 374 { 375 EIGEN_STATIC_ASSERT((!nested_eval<Lhs,1>::Evaluate),EIGEN_INTERNAL_COMPILATION_ERROR_OR_YOU_MADE_A_PROGRAMMING_MISTAKE); 376 typename nested_eval<Rhs,Lhs::RowsAtCompileTime>::type actual_rhs(rhs); 377 const Index rows = dest.rows(); 378 for(Index i=0; i<rows; ++i) 379 dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum(); 380 } 381 }; 382 383 } // end namespace internal 384 385 /*************************************************************************** 386 * Implementation of matrix base methods 387 ***************************************************************************/ 388 389 /** \returns the matrix product of \c *this and \a other. 390 * 391 * \note If instead of the matrix product you want the coefficient-wise product, see Cwise::operator*(). 392 * 393 * \sa lazyProduct(), operator*=(const MatrixBase&), Cwise::operator*() 394 */ 395 template<typename Derived> 396 template<typename OtherDerived> 397 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 398 const Product<Derived, OtherDerived> 399 MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const 400 { 401 // A note regarding the function declaration: In MSVC, this function will sometimes 402 // not be inlined since DenseStorage is an unwindable object for dynamic 403 // matrices and product types are holding a member to store the result. 404 // Thus it does not help tagging this function with EIGEN_STRONG_INLINE. 405 enum { 406 ProductIsValid = Derived::ColsAtCompileTime==Dynamic 407 || OtherDerived::RowsAtCompileTime==Dynamic 408 || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime), 409 AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime, 410 SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived) 411 }; 412 // note to the lost user: 413 // * for a dot product use: v1.dot(v2) 414 // * for a coeff-wise product use: v1.cwiseProduct(v2) 415 EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes), 416 INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS) 417 EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors), 418 INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION) 419 EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT) 420 #ifdef EIGEN_DEBUG_PRODUCT 421 internal::product_type<Derived,OtherDerived>::debug(); 422 #endif 423 424 return Product<Derived, OtherDerived>(derived(), other.derived()); 425 } 426 427 /** \returns an expression of the matrix product of \c *this and \a other without implicit evaluation. 428 * 429 * The returned product will behave like any other expressions: the coefficients of the product will be 430 * computed once at a time as requested. This might be useful in some extremely rare cases when only 431 * a small and no coherent fraction of the result's coefficients have to be computed. 432 * 433 * \warning This version of the matrix product can be much much slower. So use it only if you know 434 * what you are doing and that you measured a true speed improvement. 435 * 436 * \sa operator*(const MatrixBase&) 437 */ 438 template<typename Derived> 439 template<typename OtherDerived> 440 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 441 const Product<Derived,OtherDerived,LazyProduct> 442 MatrixBase<Derived>::lazyProduct(const MatrixBase<OtherDerived> &other) const 443 { 444 enum { 445 ProductIsValid = Derived::ColsAtCompileTime==Dynamic 446 || OtherDerived::RowsAtCompileTime==Dynamic 447 || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime), 448 AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime, 449 SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived) 450 }; 451 // note to the lost user: 452 // * for a dot product use: v1.dot(v2) 453 // * for a coeff-wise product use: v1.cwiseProduct(v2) 454 EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes), 455 INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS) 456 EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors), 457 INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION) 458 EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT) 459 460 return Product<Derived,OtherDerived,LazyProduct>(derived(), other.derived()); 461 } 462 463 } // end namespace Eigen 464 465 #endif // EIGEN_PRODUCT_H