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TensorPadding.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_PADDING_H
11#define EIGEN_CXX11_TENSOR_TENSOR_PADDING_H
12
13namespace Eigen {
14
22namespace internal {
23template<typename PaddingDimensions, typename XprType>
24struct traits<TensorPaddingOp<PaddingDimensions, XprType> > : public traits<XprType>
25{
26 typedef typename XprType::Scalar Scalar;
27 typedef traits<XprType> XprTraits;
28 typedef typename XprTraits::StorageKind StorageKind;
29 typedef typename XprTraits::Index Index;
30 typedef typename XprType::Nested Nested;
31 typedef typename remove_reference<Nested>::type _Nested;
32 static const int NumDimensions = XprTraits::NumDimensions;
33 static const int Layout = XprTraits::Layout;
34};
35
36template<typename PaddingDimensions, typename XprType>
37struct eval<TensorPaddingOp<PaddingDimensions, XprType>, Eigen::Dense>
38{
39 typedef const TensorPaddingOp<PaddingDimensions, XprType>& type;
40};
41
42template<typename PaddingDimensions, typename XprType>
43struct nested<TensorPaddingOp<PaddingDimensions, XprType>, 1, typename eval<TensorPaddingOp<PaddingDimensions, XprType> >::type>
44{
45 typedef TensorPaddingOp<PaddingDimensions, XprType> type;
46};
47
48} // end namespace internal
49
50
51
52template<typename PaddingDimensions, typename XprType>
53class TensorPaddingOp : public TensorBase<TensorPaddingOp<PaddingDimensions, XprType>, ReadOnlyAccessors>
54{
55 public:
56 typedef typename Eigen::internal::traits<TensorPaddingOp>::Scalar Scalar;
57 typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
58 typedef typename XprType::CoeffReturnType CoeffReturnType;
59 typedef typename Eigen::internal::nested<TensorPaddingOp>::type Nested;
60 typedef typename Eigen::internal::traits<TensorPaddingOp>::StorageKind StorageKind;
61 typedef typename Eigen::internal::traits<TensorPaddingOp>::Index Index;
62
63 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorPaddingOp(const XprType& expr, const PaddingDimensions& padding_dims, const Scalar padding_value)
64 : m_xpr(expr), m_padding_dims(padding_dims), m_padding_value(padding_value) {}
65
66 EIGEN_DEVICE_FUNC
67 const PaddingDimensions& padding() const { return m_padding_dims; }
68 EIGEN_DEVICE_FUNC
69 Scalar padding_value() const { return m_padding_value; }
70
71 EIGEN_DEVICE_FUNC
72 const typename internal::remove_all<typename XprType::Nested>::type&
73 expression() const { return m_xpr; }
74
75 protected:
76 typename XprType::Nested m_xpr;
77 const PaddingDimensions m_padding_dims;
78 const Scalar m_padding_value;
79};
80
81
82// Eval as rvalue
83template<typename PaddingDimensions, typename ArgType, typename Device>
84struct TensorEvaluator<const TensorPaddingOp<PaddingDimensions, ArgType>, Device>
85{
86 typedef TensorPaddingOp<PaddingDimensions, ArgType> XprType;
87 typedef typename XprType::Index Index;
88 static const int NumDims = internal::array_size<PaddingDimensions>::value;
89 typedef DSizes<Index, NumDims> Dimensions;
90 typedef typename XprType::Scalar Scalar;
91 typedef typename XprType::CoeffReturnType CoeffReturnType;
92 typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
93 static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
94
95 enum {
96 IsAligned = true,
97 PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
98 Layout = TensorEvaluator<ArgType, Device>::Layout,
99 CoordAccess = true,
100 RawAccess = false
101 };
102
103 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
104 : m_impl(op.expression(), device), m_padding(op.padding()), m_paddingValue(op.padding_value())
105 {
106 // The padding op doesn't change the rank of the tensor. Directly padding a scalar would lead
107 // to a vector, which doesn't make sense. Instead one should reshape the scalar into a vector
108 // of 1 element first and then pad.
109 EIGEN_STATIC_ASSERT((NumDims > 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
110
111 // Compute dimensions
112 m_dimensions = m_impl.dimensions();
113 for (int i = 0; i < NumDims; ++i) {
114 m_dimensions[i] += m_padding[i].first + m_padding[i].second;
115 }
116 const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
117 if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
118 m_inputStrides[0] = 1;
119 m_outputStrides[0] = 1;
120 for (int i = 1; i < NumDims; ++i) {
121 m_inputStrides[i] = m_inputStrides[i-1] * input_dims[i-1];
122 m_outputStrides[i] = m_outputStrides[i-1] * m_dimensions[i-1];
123 }
124 m_outputStrides[NumDims] = m_outputStrides[NumDims-1] * m_dimensions[NumDims-1];
125 } else {
126 m_inputStrides[NumDims - 1] = 1;
127 m_outputStrides[NumDims] = 1;
128 for (int i = NumDims - 2; i >= 0; --i) {
129 m_inputStrides[i] = m_inputStrides[i+1] * input_dims[i+1];
130 m_outputStrides[i+1] = m_outputStrides[i+2] * m_dimensions[i+1];
131 }
132 m_outputStrides[0] = m_outputStrides[1] * m_dimensions[0];
133 }
134 }
135
136 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
137
138 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar*) {
139 m_impl.evalSubExprsIfNeeded(NULL);
140 return true;
141 }
142 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
143 m_impl.cleanup();
144 }
145
146 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
147 {
148 eigen_assert(index < dimensions().TotalSize());
149 Index inputIndex = 0;
150 if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
151 for (int i = NumDims - 1; i > 0; --i) {
152 const Index idx = index / m_outputStrides[i];
153 if (isPaddingAtIndexForDim(idx, i)) {
154 return m_paddingValue;
155 }
156 inputIndex += (idx - m_padding[i].first) * m_inputStrides[i];
157 index -= idx * m_outputStrides[i];
158 }
159 if (isPaddingAtIndexForDim(index, 0)) {
160 return m_paddingValue;
161 }
162 inputIndex += (index - m_padding[0].first);
163 } else {
164 for (int i = 0; i < NumDims - 1; ++i) {
165 const Index idx = index / m_outputStrides[i+1];
166 if (isPaddingAtIndexForDim(idx, i)) {
167 return m_paddingValue;
168 }
169 inputIndex += (idx - m_padding[i].first) * m_inputStrides[i];
170 index -= idx * m_outputStrides[i+1];
171 }
172 if (isPaddingAtIndexForDim(index, NumDims-1)) {
173 return m_paddingValue;
174 }
175 inputIndex += (index - m_padding[NumDims-1].first);
176 }
177 return m_impl.coeff(inputIndex);
178 }
179
180 template<int LoadMode>
181 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
182 {
183 if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
184 return packetColMajor(index);
185 }
186 return packetRowMajor(index);
187 }
188
189 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
190 TensorOpCost cost = m_impl.costPerCoeff(vectorized);
191 if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
192 for (int i = 0; i < NumDims; ++i)
193 updateCostPerDimension(cost, i, i == 0);
194 } else {
195 for (int i = NumDims - 1; i >= 0; --i)
196 updateCostPerDimension(cost, i, i == NumDims - 1);
197 }
198 return cost;
199 }
200
201 EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
202
203 private:
204 EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool isPaddingAtIndexForDim(
205 Index index, int dim_index) const {
206#if defined(EIGEN_HAS_INDEX_LIST)
207 return (!internal::index_pair_first_statically_eq<PaddingDimensions>(dim_index, 0) &&
208 index < m_padding[dim_index].first) ||
209 (!internal::index_pair_second_statically_eq<PaddingDimensions>(dim_index, 0) &&
210 index >= m_dimensions[dim_index] - m_padding[dim_index].second);
211#else
212 return (index < m_padding[dim_index].first) ||
213 (index >= m_dimensions[dim_index] - m_padding[dim_index].second);
214#endif
215 }
216
217 EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool isLeftPaddingCompileTimeZero(
218 int dim_index) const {
219#if defined(EIGEN_HAS_INDEX_LIST)
220 return internal::index_pair_first_statically_eq<PaddingDimensions>(dim_index, 0);
221#else
222 EIGEN_UNUSED_VARIABLE(dim_index);
223 return false;
224#endif
225 }
226
227 EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE bool isRightPaddingCompileTimeZero(
228 int dim_index) const {
229#if defined(EIGEN_HAS_INDEX_LIST)
230 return internal::index_pair_second_statically_eq<PaddingDimensions>(dim_index, 0);
231#else
232 EIGEN_UNUSED_VARIABLE(dim_index);
233 return false;
234#endif
235 }
236
237
238 void updateCostPerDimension(TensorOpCost& cost, int i, bool first) const {
239 const double in = static_cast<double>(m_impl.dimensions()[i]);
240 const double out = in + m_padding[i].first + m_padding[i].second;
241 if (out == 0)
242 return;
243 const double reduction = in / out;
244 cost *= reduction;
245 if (first) {
246 cost += TensorOpCost(0, 0, 2 * TensorOpCost::AddCost<Index>() +
247 reduction * (1 * TensorOpCost::AddCost<Index>()));
248 } else {
249 cost += TensorOpCost(0, 0, 2 * TensorOpCost::AddCost<Index>() +
250 2 * TensorOpCost::MulCost<Index>() +
251 reduction * (2 * TensorOpCost::MulCost<Index>() +
252 1 * TensorOpCost::DivCost<Index>()));
253 }
254 }
255
256 protected:
257
258 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetColMajor(Index index) const
259 {
260 EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
261 eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
262
263 const Index initialIndex = index;
264 Index inputIndex = 0;
265 for (int i = NumDims - 1; i > 0; --i) {
266 const Index first = index;
267 const Index last = index + PacketSize - 1;
268 const Index lastPaddedLeft = m_padding[i].first * m_outputStrides[i];
269 const Index firstPaddedRight = (m_dimensions[i] - m_padding[i].second) * m_outputStrides[i];
270 const Index lastPaddedRight = m_outputStrides[i+1];
271
272 if (!isLeftPaddingCompileTimeZero(i) && last < lastPaddedLeft) {
273 // all the coefficient are in the padding zone.
274 return internal::pset1<PacketReturnType>(m_paddingValue);
275 }
276 else if (!isRightPaddingCompileTimeZero(i) && first >= firstPaddedRight && last < lastPaddedRight) {
277 // all the coefficient are in the padding zone.
278 return internal::pset1<PacketReturnType>(m_paddingValue);
279 }
280 else if ((isLeftPaddingCompileTimeZero(i) && isRightPaddingCompileTimeZero(i)) || (first >= lastPaddedLeft && last < firstPaddedRight)) {
281 // all the coefficient are between the 2 padding zones.
282 const Index idx = index / m_outputStrides[i];
283 inputIndex += (idx - m_padding[i].first) * m_inputStrides[i];
284 index -= idx * m_outputStrides[i];
285 }
286 else {
287 // Every other case
288 return packetWithPossibleZero(initialIndex);
289 }
290 }
291
292 const Index last = index + PacketSize - 1;
293 const Index first = index;
294 const Index lastPaddedLeft = m_padding[0].first;
295 const Index firstPaddedRight = (m_dimensions[0] - m_padding[0].second);
296 const Index lastPaddedRight = m_outputStrides[1];
297
298 if (!isLeftPaddingCompileTimeZero(0) && last < lastPaddedLeft) {
299 // all the coefficient are in the padding zone.
300 return internal::pset1<PacketReturnType>(m_paddingValue);
301 }
302 else if (!isRightPaddingCompileTimeZero(0) && first >= firstPaddedRight && last < lastPaddedRight) {
303 // all the coefficient are in the padding zone.
304 return internal::pset1<PacketReturnType>(m_paddingValue);
305 }
306 else if ((isLeftPaddingCompileTimeZero(0) && isRightPaddingCompileTimeZero(0)) || (first >= lastPaddedLeft && last < firstPaddedRight)) {
307 // all the coefficient are between the 2 padding zones.
308 inputIndex += (index - m_padding[0].first);
309 return m_impl.template packet<Unaligned>(inputIndex);
310 }
311 // Every other case
312 return packetWithPossibleZero(initialIndex);
313 }
314
315 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetRowMajor(Index index) const
316 {
317 EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
318 eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
319
320 const Index initialIndex = index;
321 Index inputIndex = 0;
322
323 for (int i = 0; i < NumDims - 1; ++i) {
324 const Index first = index;
325 const Index last = index + PacketSize - 1;
326 const Index lastPaddedLeft = m_padding[i].first * m_outputStrides[i+1];
327 const Index firstPaddedRight = (m_dimensions[i] - m_padding[i].second) * m_outputStrides[i+1];
328 const Index lastPaddedRight = m_outputStrides[i];
329
330 if (!isLeftPaddingCompileTimeZero(i) && last < lastPaddedLeft) {
331 // all the coefficient are in the padding zone.
332 return internal::pset1<PacketReturnType>(m_paddingValue);
333 }
334 else if (!isRightPaddingCompileTimeZero(i) && first >= firstPaddedRight && last < lastPaddedRight) {
335 // all the coefficient are in the padding zone.
336 return internal::pset1<PacketReturnType>(m_paddingValue);
337 }
338 else if ((isLeftPaddingCompileTimeZero(i) && isRightPaddingCompileTimeZero(i)) || (first >= lastPaddedLeft && last < firstPaddedRight)) {
339 // all the coefficient are between the 2 padding zones.
340 const Index idx = index / m_outputStrides[i+1];
341 inputIndex += (idx - m_padding[i].first) * m_inputStrides[i];
342 index -= idx * m_outputStrides[i+1];
343 }
344 else {
345 // Every other case
346 return packetWithPossibleZero(initialIndex);
347 }
348 }
349
350 const Index last = index + PacketSize - 1;
351 const Index first = index;
352 const Index lastPaddedLeft = m_padding[NumDims-1].first;
353 const Index firstPaddedRight = (m_dimensions[NumDims-1] - m_padding[NumDims-1].second);
354 const Index lastPaddedRight = m_outputStrides[NumDims-1];
355
356 if (!isLeftPaddingCompileTimeZero(NumDims-1) && last < lastPaddedLeft) {
357 // all the coefficient are in the padding zone.
358 return internal::pset1<PacketReturnType>(m_paddingValue);
359 }
360 else if (!isRightPaddingCompileTimeZero(NumDims-1) && first >= firstPaddedRight && last < lastPaddedRight) {
361 // all the coefficient are in the padding zone.
362 return internal::pset1<PacketReturnType>(m_paddingValue);
363 }
364 else if ((isLeftPaddingCompileTimeZero(NumDims-1) && isRightPaddingCompileTimeZero(NumDims-1)) || (first >= lastPaddedLeft && last < firstPaddedRight)) {
365 // all the coefficient are between the 2 padding zones.
366 inputIndex += (index - m_padding[NumDims-1].first);
367 return m_impl.template packet<Unaligned>(inputIndex);
368 }
369 // Every other case
370 return packetWithPossibleZero(initialIndex);
371 }
372
373 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetWithPossibleZero(Index index) const
374 {
375 EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
376 for (int i = 0; i < PacketSize; ++i) {
377 values[i] = coeff(index+i);
378 }
379 PacketReturnType rslt = internal::pload<PacketReturnType>(values);
380 return rslt;
381 }
382
383 Dimensions m_dimensions;
384 array<Index, NumDims+1> m_outputStrides;
385 array<Index, NumDims> m_inputStrides;
386 TensorEvaluator<ArgType, Device> m_impl;
387 PaddingDimensions m_padding;
388
389 Scalar m_paddingValue;
390};
391
392
393
394
395} // end namespace Eigen
396
397#endif // EIGEN_CXX11_TENSOR_TENSOR_PADDING_H
Namespace containing all symbols from the Eigen library.
Definition: AdolcForward:45
const Device & device() const
required by sycl in order to construct sycl buffer from raw pointer
Definition: TensorEvaluator.h:114