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TensorMap.h
1// This file is part of Eigen, a lightweight C++ template library
2// for linear algebra.
3//
4// Copyright (C) 2014 Benoit Steiner <benoit.steiner.goog@gmail.com>
5//
6// This Source Code Form is subject to the terms of the Mozilla
7// Public License v. 2.0. If a copy of the MPL was not distributed
8// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
9
10#ifndef EIGEN_CXX11_TENSOR_TENSOR_MAP_H
11#define EIGEN_CXX11_TENSOR_TENSOR_MAP_H
12
13namespace Eigen {
14
15// FIXME use proper doxygen documentation (e.g. \tparam MakePointer_)
16
29template<typename PlainObjectType, int Options_, template <class> class MakePointer_> class TensorMap : public TensorBase<TensorMap<PlainObjectType, Options_, MakePointer_> >
30{
31 public:
32 typedef TensorMap<PlainObjectType, Options_, MakePointer_> Self;
33 typedef typename PlainObjectType::Base Base;
34 typedef typename Eigen::internal::nested<Self>::type Nested;
35 typedef typename internal::traits<PlainObjectType>::StorageKind StorageKind;
36 typedef typename internal::traits<PlainObjectType>::Index Index;
37 typedef typename internal::traits<PlainObjectType>::Scalar Scalar;
38 typedef typename NumTraits<Scalar>::Real RealScalar;
39 typedef typename Base::CoeffReturnType CoeffReturnType;
40
41 /* typedef typename internal::conditional<
42 bool(internal::is_lvalue<PlainObjectType>::value),
43 Scalar *,
44 const Scalar *>::type
45 PointerType;*/
46 typedef typename MakePointer_<Scalar>::Type PointerType;
47 typedef PointerType PointerArgType;
48
49 static const int Options = Options_;
50
51 static const Index NumIndices = PlainObjectType::NumIndices;
52 typedef typename PlainObjectType::Dimensions Dimensions;
53
54 enum {
55 IsAligned = ((int(Options_)&Aligned)==Aligned),
56 Layout = PlainObjectType::Layout,
57 CoordAccess = true,
58 RawAccess = true
59 };
60
61 EIGEN_DEVICE_FUNC
62 EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr) : m_data(dataPtr), m_dimensions() {
63 // The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
64 EIGEN_STATIC_ASSERT((0 == NumIndices || NumIndices == Dynamic), YOU_MADE_A_PROGRAMMING_MISTAKE)
65 }
66
67#if EIGEN_HAS_VARIADIC_TEMPLATES
68 template<typename... IndexTypes> EIGEN_DEVICE_FUNC
69 EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index firstDimension, IndexTypes... otherDimensions) : m_data(dataPtr), m_dimensions(firstDimension, otherDimensions...) {
70 // The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
71 EIGEN_STATIC_ASSERT((sizeof...(otherDimensions) + 1 == NumIndices || NumIndices == Dynamic), YOU_MADE_A_PROGRAMMING_MISTAKE)
72 }
73#else
74 EIGEN_DEVICE_FUNC
75 EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index firstDimension) : m_data(dataPtr), m_dimensions(firstDimension) {
76 // The number of dimensions used to construct a tensor must be equal to the rank of the tensor.
77 EIGEN_STATIC_ASSERT((1 == NumIndices || NumIndices == Dynamic), YOU_MADE_A_PROGRAMMING_MISTAKE)
78 }
79 EIGEN_DEVICE_FUNC
80 EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2) : m_data(dataPtr), m_dimensions(dim1, dim2) {
81 EIGEN_STATIC_ASSERT(2 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
82 }
83 EIGEN_DEVICE_FUNC
84 EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2, Index dim3) : m_data(dataPtr), m_dimensions(dim1, dim2, dim3) {
85 EIGEN_STATIC_ASSERT(3 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
86 }
87 EIGEN_DEVICE_FUNC
88 EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2, Index dim3, Index dim4) : m_data(dataPtr), m_dimensions(dim1, dim2, dim3, dim4) {
89 EIGEN_STATIC_ASSERT(4 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
90 }
91 EIGEN_DEVICE_FUNC
92 EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, Index dim1, Index dim2, Index dim3, Index dim4, Index dim5) : m_data(dataPtr), m_dimensions(dim1, dim2, dim3, dim4, dim5) {
93 EIGEN_STATIC_ASSERT(5 == NumIndices || NumIndices == Dynamic, YOU_MADE_A_PROGRAMMING_MISTAKE)
94 }
95#endif
96
97 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, const array<Index, NumIndices>& dimensions)
98 : m_data(dataPtr), m_dimensions(dimensions)
99 { }
100
101 template <typename Dimensions>
102 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorMap(PointerArgType dataPtr, const Dimensions& dimensions)
103 : m_data(dataPtr), m_dimensions(dimensions)
104 { }
105
106 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorMap(PlainObjectType& tensor)
107 : m_data(tensor.data()), m_dimensions(tensor.dimensions())
108 { }
109
110 EIGEN_DEVICE_FUNC
111 EIGEN_STRONG_INLINE Index rank() const { return m_dimensions.rank(); }
112 EIGEN_DEVICE_FUNC
113 EIGEN_STRONG_INLINE Index dimension(Index n) const { return m_dimensions[n]; }
114 EIGEN_DEVICE_FUNC
115 EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
116 EIGEN_DEVICE_FUNC
117 EIGEN_STRONG_INLINE Index size() const { return m_dimensions.TotalSize(); }
118 EIGEN_DEVICE_FUNC
119 EIGEN_STRONG_INLINE PointerType data() { return m_data; }
120 EIGEN_DEVICE_FUNC
121 EIGEN_STRONG_INLINE const PointerType data() const { return m_data; }
122
123 EIGEN_DEVICE_FUNC
124 EIGEN_STRONG_INLINE const Scalar& operator()(const array<Index, NumIndices>& indices) const
125 {
126 // eigen_assert(checkIndexRange(indices));
127 if (PlainObjectType::Options&RowMajor) {
128 const Index index = m_dimensions.IndexOfRowMajor(indices);
129 return m_data[index];
130 } else {
131 const Index index = m_dimensions.IndexOfColMajor(indices);
132 return m_data[index];
133 }
134 }
135
136 EIGEN_DEVICE_FUNC
137 EIGEN_STRONG_INLINE const Scalar& operator()() const
138 {
139 EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE)
140 return m_data[0];
141 }
142
143 EIGEN_DEVICE_FUNC
144 EIGEN_STRONG_INLINE const Scalar& operator()(Index index) const
145 {
146 eigen_internal_assert(index >= 0 && index < size());
147 return m_data[index];
148 }
149
150#if EIGEN_HAS_VARIADIC_TEMPLATES
151 template<typename... IndexTypes> EIGEN_DEVICE_FUNC
152 EIGEN_STRONG_INLINE const Scalar& operator()(Index firstIndex, Index secondIndex, IndexTypes... otherIndices) const
153 {
154 EIGEN_STATIC_ASSERT(sizeof...(otherIndices) + 2 == NumIndices, YOU_MADE_A_PROGRAMMING_MISTAKE)
155 if (PlainObjectType::Options&RowMajor) {
156 const Index index = m_dimensions.IndexOfRowMajor(array<Index, NumIndices>{{firstIndex, secondIndex, otherIndices...}});
157 return m_data[index];
158 } else {
159 const Index index = m_dimensions.IndexOfColMajor(array<Index, NumIndices>{{firstIndex, secondIndex, otherIndices...}});
160 return m_data[index];
161 }
162 }
163#else
164 EIGEN_DEVICE_FUNC
165 EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1) const
166 {
167 if (PlainObjectType::Options&RowMajor) {
168 const Index index = i1 + i0 * m_dimensions[1];
169 return m_data[index];
170 } else {
171 const Index index = i0 + i1 * m_dimensions[0];
172 return m_data[index];
173 }
174 }
175 EIGEN_DEVICE_FUNC
176 EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2) const
177 {
178 if (PlainObjectType::Options&RowMajor) {
179 const Index index = i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0);
180 return m_data[index];
181 } else {
182 const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * i2);
183 return m_data[index];
184 }
185 }
186 EIGEN_DEVICE_FUNC
187 EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2, Index i3) const
188 {
189 if (PlainObjectType::Options&RowMajor) {
190 const Index index = i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0));
191 return m_data[index];
192 } else {
193 const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * i3));
194 return m_data[index];
195 }
196 }
197 EIGEN_DEVICE_FUNC
198 EIGEN_STRONG_INLINE const Scalar& operator()(Index i0, Index i1, Index i2, Index i3, Index i4) const
199 {
200 if (PlainObjectType::Options&RowMajor) {
201 const Index index = i4 + m_dimensions[4] * (i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0)));
202 return m_data[index];
203 } else {
204 const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * (i3 + m_dimensions[3] * i4)));
205 return m_data[index];
206 }
207 }
208#endif
209
210 EIGEN_DEVICE_FUNC
211 EIGEN_STRONG_INLINE Scalar& operator()(const array<Index, NumIndices>& indices)
212 {
213 // eigen_assert(checkIndexRange(indices));
214 if (PlainObjectType::Options&RowMajor) {
215 const Index index = m_dimensions.IndexOfRowMajor(indices);
216 return m_data[index];
217 } else {
218 const Index index = m_dimensions.IndexOfColMajor(indices);
219 return m_data[index];
220 }
221 }
222
223 EIGEN_DEVICE_FUNC
224 EIGEN_STRONG_INLINE Scalar& operator()()
225 {
226 EIGEN_STATIC_ASSERT(NumIndices == 0, YOU_MADE_A_PROGRAMMING_MISTAKE)
227 return m_data[0];
228 }
229
230 EIGEN_DEVICE_FUNC
231 EIGEN_STRONG_INLINE Scalar& operator()(Index index)
232 {
233 eigen_internal_assert(index >= 0 && index < size());
234 return m_data[index];
235 }
236
237#if EIGEN_HAS_VARIADIC_TEMPLATES
238 template<typename... IndexTypes> EIGEN_DEVICE_FUNC
239 EIGEN_STRONG_INLINE Scalar& operator()(Index firstIndex, Index secondIndex, IndexTypes... otherIndices)
240 {
241 static_assert(sizeof...(otherIndices) + 2 == NumIndices || NumIndices == Dynamic, "Number of indices used to access a tensor coefficient must be equal to the rank of the tensor.");
242 const std::size_t NumDims = sizeof...(otherIndices) + 2;
243 if (PlainObjectType::Options&RowMajor) {
244 const Index index = m_dimensions.IndexOfRowMajor(array<Index, NumDims>{{firstIndex, secondIndex, otherIndices...}});
245 return m_data[index];
246 } else {
247 const Index index = m_dimensions.IndexOfColMajor(array<Index, NumDims>{{firstIndex, secondIndex, otherIndices...}});
248 return m_data[index];
249 }
250 }
251#else
252 EIGEN_DEVICE_FUNC
253 EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1)
254 {
255 if (PlainObjectType::Options&RowMajor) {
256 const Index index = i1 + i0 * m_dimensions[1];
257 return m_data[index];
258 } else {
259 const Index index = i0 + i1 * m_dimensions[0];
260 return m_data[index];
261 }
262 }
263 EIGEN_DEVICE_FUNC
264 EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2)
265 {
266 if (PlainObjectType::Options&RowMajor) {
267 const Index index = i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0);
268 return m_data[index];
269 } else {
270 const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * i2);
271 return m_data[index];
272 }
273 }
274 EIGEN_DEVICE_FUNC
275 EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3)
276 {
277 if (PlainObjectType::Options&RowMajor) {
278 const Index index = i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0));
279 return m_data[index];
280 } else {
281 const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * i3));
282 return m_data[index];
283 }
284 }
285 EIGEN_DEVICE_FUNC
286 EIGEN_STRONG_INLINE Scalar& operator()(Index i0, Index i1, Index i2, Index i3, Index i4)
287 {
288 if (PlainObjectType::Options&RowMajor) {
289 const Index index = i4 + m_dimensions[4] * (i3 + m_dimensions[3] * (i2 + m_dimensions[2] * (i1 + m_dimensions[1] * i0)));
290 return m_data[index];
291 } else {
292 const Index index = i0 + m_dimensions[0] * (i1 + m_dimensions[1] * (i2 + m_dimensions[2] * (i3 + m_dimensions[3] * i4)));
293 return m_data[index];
294 }
295 }
296#endif
297
298 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Self& operator=(const Self& other)
299 {
300 typedef TensorAssignOp<Self, const Self> Assign;
301 Assign assign(*this, other);
302 internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
303 return *this;
304 }
305
306 template<typename OtherDerived>
307 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
308 Self& operator=(const OtherDerived& other)
309 {
310 typedef TensorAssignOp<Self, const OtherDerived> Assign;
311 Assign assign(*this, other);
312 internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
313 return *this;
314 }
315
316 private:
317 typename MakePointer_<Scalar>::Type m_data;
318 Dimensions m_dimensions;
319};
320
321} // end namespace Eigen
322
323#endif // EIGEN_CXX11_TENSOR_TENSOR_MAP_H
Eigen::TensorAssignOp
Definition TensorAssign.h:56
Eigen::TensorBase
The tensor base class.
Definition TensorForwardDeclarations.h:29
Eigen::Aligned
Aligned
Eigen::RowMajor
RowMajor
Eigen
Namespace containing all symbols from the Eigen library.
Eigen::Dynamic
const int Dynamic