GeneralProduct.h
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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 ||
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 {
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 {
73  };
75 
76 public:
77  enum {
80  };
81 #ifdef EIGEN_DEBUG_PRODUCT
82  static void debug()
83  {
84  EIGEN_DEBUG_VAR(Rows);
86  EIGEN_DEBUG_VAR(Depth);
87  EIGEN_DEBUG_VAR(rows_select);
88  EIGEN_DEBUG_VAR(cols_select);
89  EIGEN_DEBUG_VAR(depth_select);
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>
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>
171 {
173 };
174 
175 template<typename Scalar,int Size,int MaxSize>
176 struct gemv_static_vector_if<Scalar,Size,MaxSize,true>
177 {
178  enum {
181  };
182  #if EIGEN_MAX_STATIC_ALIGN_BYTES!=0
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.
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 };
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 
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)
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),
241  MightCannotUseDest = ((!EvalToDestAtCompileTime) || ComplexByReal) && (ActualDest::MaxSizeAtCompileTime!=0)
242  };
243 
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
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  {
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 
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 
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 
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 
395 template<typename Derived>
396 template<typename OtherDerived>
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
422 #endif
423 
424  return Product<Derived, OtherDerived>(derived(), other.derived());
425 }
426 
438 template<typename Derived>
439 template<typename OtherDerived>
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
SCALAR Scalar
Definition: bench_gemm.cpp:46
#define EIGEN_STRONG_INLINE
Definition: Macros.h:917
Matrix< RealScalar, Dynamic, Dynamic > M
Definition: bench_gemm.cpp:51
Expression of the product of two arbitrary matrices or vectors.
Definition: Product.h:71
#define EIGEN_DEBUG_VAR(x)
Definition: Macros.h:898
#define EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
A matrix or vector expression mapping an existing array of data.
Definition: Map.h:94
Expression of the transpose of a matrix.
Definition: Transpose.h:52
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE To run(const From &x)
Definition: BlasUtil.h:43
static void run(const Lhs &lhs, const Rhs &rhs, Dest &dest, const typename Dest::Scalar &alpha)
remove_all< Lhs >::type _Lhs
Namespace containing all symbols from the Eigen library.
Definition: jet.h:637
Holds information about the various numeric (i.e. scalar) types allowed by Eigen. ...
Definition: NumTraits.h:232
#define EIGEN_STATIC_ASSERT(CONDITION, MSG)
Definition: StaticAssert.h:127
EIGEN_DEVICE_FUNC const Product< Derived, OtherDerived, LazyProduct > lazyProduct(const MatrixBase< OtherDerived > &other) const
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Scalar * data()
#define N
Definition: gksort.c:12
#define EIGEN_SIZE_MIN_PREFER_FIXED(a, b)
Definition: Macros.h:1302
EIGEN_DEVICE_FUNC const Product< Derived, OtherDerived > operator*(const MatrixBase< OtherDerived > &other) const
std::size_t UIntPtr
Definition: Meta.h:92
static constexpr bool debug
internal::plain_array< Scalar, EIGEN_SIZE_MIN_PREFER_FIXED(Size, MaxSize)+(ForceAlignment?EIGEN_MAX_ALIGN_BYTES:0), 0 > m_data
remove_all< Rhs >::type _Rhs
EIGEN_DEFAULT_DENSE_INDEX_TYPE Index
The Index type as used for the API.
Definition: Meta.h:74
static void run(const Lhs &lhs, const Rhs &rhs, Dest &dest, const typename Dest::Scalar &alpha)
int data[]
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE ResScalar combine_scalar_factors(const ResScalar &alpha, const Lhs &lhs, const Rhs &rhs)
Definition: BlasUtil.h:568
RealScalar alpha
EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Scalar * data()
NumTraits< Scalar >::Real RealScalar
Definition: bench_gemm.cpp:47
#define ei_declare_aligned_stack_constructed_variable(TYPE, NAME, SIZE, BUFFER)
Definition: Memory.h:768
DenseIndex ret
static const int Cols
EIGEN_CONSTEXPR Index size(const T &x)
Definition: Meta.h:479
#define EIGEN_DEVICE_FUNC
Definition: Macros.h:976
static void run(const Lhs &lhs, const Rhs &rhs, Dest &dest, const typename Dest::Scalar &alpha)
#define EIGEN_PREDICATE_SAME_MATRIX_SIZE(TYPE0, TYPE1)
Definition: StaticAssert.h:174
#define EIGEN_PLAIN_ENUM_MIN(a, b)
Definition: Macros.h:1288
#define EIGEN_MAX_ALIGN_BYTES
EIGEN_DEVICE_FUNC const ImagReturnType imag() const
static void run(const Lhs &lhs, const Rhs &rhs, Dest &dest, const typename Dest::Scalar &alpha)
const int Dynamic
Definition: Constants.h:22
#define eigen_internal_assert(x)
Definition: Macros.h:1043
Generic expression where a coefficient-wise unary operator is applied to an expression.
Definition: CwiseUnaryOp.h:55
static void run(const Lhs &lhs, const Rhs &rhs, Dest &dest, const typename Dest::Scalar &alpha)
product_type_selector< rows_select, cols_select, depth_select > selector
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EIGEN_CONSTEXPR Index cols() const EIGEN_NOEXCEPT
Definition: Transpose.h:71
Base class for all dense matrices, vectors, and expressions.
Definition: MatrixBase.h:48
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EIGEN_CONSTEXPR Index rows() const EIGEN_NOEXCEPT
Definition: Transpose.h:69
v setZero(3)


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