Loading...
Searching...
No Matches
TensorReverse.h
1// This file is part of Eigen, a lightweight C++ template library
2// for linear algebra.
3//
4// Copyright (C) 2014 Navdeep Jaitly <ndjaitly@google.com>
5// Benoit Steiner <benoit.steiner.goog@gmail.com>
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_CXX11_TENSOR_TENSOR_REVERSE_H
12#define EIGEN_CXX11_TENSOR_TENSOR_REVERSE_H
13namespace Eigen {
14
21namespace internal {
22template<typename ReverseDimensions, typename XprType>
23struct traits<TensorReverseOp<ReverseDimensions,
24 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 ReverseDimensions, typename XprType>
37struct eval<TensorReverseOp<ReverseDimensions, XprType>, Eigen::Dense>
38{
39 typedef const TensorReverseOp<ReverseDimensions, XprType>& type;
40};
41
42template<typename ReverseDimensions, typename XprType>
43struct nested<TensorReverseOp<ReverseDimensions, XprType>, 1,
44 typename eval<TensorReverseOp<ReverseDimensions, XprType> >::type>
45{
46 typedef TensorReverseOp<ReverseDimensions, XprType> type;
47};
48
49} // end namespace internal
50
51template<typename ReverseDimensions, typename XprType>
52class TensorReverseOp : public TensorBase<TensorReverseOp<ReverseDimensions,
53 XprType>, WriteAccessors>
54{
55 public:
56 typedef typename Eigen::internal::traits<TensorReverseOp>::Scalar Scalar;
57 typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
58 typedef typename XprType::CoeffReturnType CoeffReturnType;
59 typedef typename Eigen::internal::nested<TensorReverseOp>::type Nested;
60 typedef typename Eigen::internal::traits<TensorReverseOp>::StorageKind
61 StorageKind;
62 typedef typename Eigen::internal::traits<TensorReverseOp>::Index Index;
63
64 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorReverseOp(
65 const XprType& expr, const ReverseDimensions& reverse_dims)
66 : m_xpr(expr), m_reverse_dims(reverse_dims) { }
67
68 EIGEN_DEVICE_FUNC
69 const ReverseDimensions& reverse() const { return m_reverse_dims; }
70
71 EIGEN_DEVICE_FUNC
72 const typename internal::remove_all<typename XprType::Nested>::type&
73 expression() const { return m_xpr; }
74
75 EIGEN_DEVICE_FUNC
76 EIGEN_STRONG_INLINE TensorReverseOp& operator = (const TensorReverseOp& other)
77 {
78 typedef TensorAssignOp<TensorReverseOp, const TensorReverseOp> Assign;
79 Assign assign(*this, other);
80 internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
81 return *this;
82 }
83
84 template<typename OtherDerived>
85 EIGEN_DEVICE_FUNC
86 EIGEN_STRONG_INLINE TensorReverseOp& operator = (const OtherDerived& other)
87 {
88 typedef TensorAssignOp<TensorReverseOp, const OtherDerived> Assign;
89 Assign assign(*this, other);
90 internal::TensorExecutor<const Assign, DefaultDevice>::run(assign, DefaultDevice());
91 return *this;
92 }
93
94 protected:
95 typename XprType::Nested m_xpr;
96 const ReverseDimensions m_reverse_dims;
97};
98
99// Eval as rvalue
100template<typename ReverseDimensions, typename ArgType, typename Device>
101struct TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>, Device>
102{
103 typedef TensorReverseOp<ReverseDimensions, ArgType> XprType;
104 typedef typename XprType::Index Index;
105 static const int NumDims = internal::array_size<ReverseDimensions>::value;
106 typedef DSizes<Index, NumDims> Dimensions;
107 typedef typename XprType::Scalar Scalar;
108 typedef typename XprType::CoeffReturnType CoeffReturnType;
109 typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
110 static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
111
112 enum {
113 IsAligned = false,
114 PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
115 Layout = TensorEvaluator<ArgType, Device>::Layout,
116 CoordAccess = false, // to be implemented
117 RawAccess = false
118 };
119
120 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op,
121 const Device& device)
122 : m_impl(op.expression(), device), m_reverse(op.reverse())
123 {
124 // Reversing a scalar isn't supported yet. It would be a no-op anyway.
125 EIGEN_STATIC_ASSERT((NumDims > 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
126
127 // Compute strides
128 m_dimensions = m_impl.dimensions();
129 if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
130 m_strides[0] = 1;
131 for (int i = 1; i < NumDims; ++i) {
132 m_strides[i] = m_strides[i-1] * m_dimensions[i-1];
133 }
134 } else {
135 m_strides[NumDims-1] = 1;
136 for (int i = NumDims - 2; i >= 0; --i) {
137 m_strides[i] = m_strides[i+1] * m_dimensions[i+1];
138 }
139 }
140 }
141
142 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
143 const Dimensions& dimensions() const { return m_dimensions; }
144
145 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar*) {
146 m_impl.evalSubExprsIfNeeded(NULL);
147 return true;
148 }
149 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
150 m_impl.cleanup();
151 }
152
153 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index reverseIndex(
154 Index index) const {
155 eigen_assert(index < dimensions().TotalSize());
156 Index inputIndex = 0;
157 if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
158 for (int i = NumDims - 1; i > 0; --i) {
159 Index idx = index / m_strides[i];
160 index -= idx * m_strides[i];
161 if (m_reverse[i]) {
162 idx = m_dimensions[i] - idx - 1;
163 }
164 inputIndex += idx * m_strides[i] ;
165 }
166 if (m_reverse[0]) {
167 inputIndex += (m_dimensions[0] - index - 1);
168 } else {
169 inputIndex += index;
170 }
171 } else {
172 for (int i = 0; i < NumDims - 1; ++i) {
173 Index idx = index / m_strides[i];
174 index -= idx * m_strides[i];
175 if (m_reverse[i]) {
176 idx = m_dimensions[i] - idx - 1;
177 }
178 inputIndex += idx * m_strides[i] ;
179 }
180 if (m_reverse[NumDims-1]) {
181 inputIndex += (m_dimensions[NumDims-1] - index - 1);
182 } else {
183 inputIndex += index;
184 }
185 }
186 return inputIndex;
187 }
188
189 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(
190 Index index) const {
191 return m_impl.coeff(reverseIndex(index));
192 }
193
194 template<int LoadMode>
195 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
196 PacketReturnType packet(Index index) const
197 {
198 EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
199 eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
200
201 // TODO(ndjaitly): write a better packing routine that uses
202 // local structure.
203 EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type
204 values[PacketSize];
205 for (int i = 0; i < PacketSize; ++i) {
206 values[i] = coeff(index+i);
207 }
208 PacketReturnType rslt = internal::pload<PacketReturnType>(values);
209 return rslt;
210 }
211
212 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
213 double compute_cost = NumDims * (2 * TensorOpCost::AddCost<Index>() +
214 2 * TensorOpCost::MulCost<Index>() +
215 TensorOpCost::DivCost<Index>());
216 for (int i = 0; i < NumDims; ++i) {
217 if (m_reverse[i]) {
218 compute_cost += 2 * TensorOpCost::AddCost<Index>();
219 }
220 }
221 return m_impl.costPerCoeff(vectorized) +
222 TensorOpCost(0, 0, compute_cost, false /* vectorized */, PacketSize);
223 }
224
225 EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
226
227 protected:
228 Dimensions m_dimensions;
229 array<Index, NumDims> m_strides;
230 TensorEvaluator<ArgType, Device> m_impl;
231 ReverseDimensions m_reverse;
232};
233
234// Eval as lvalue
235
236template <typename ReverseDimensions, typename ArgType, typename Device>
237struct TensorEvaluator<TensorReverseOp<ReverseDimensions, ArgType>, Device>
238 : public TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>,
239 Device> {
240 typedef TensorEvaluator<const TensorReverseOp<ReverseDimensions, ArgType>,
241 Device> Base;
242 typedef TensorReverseOp<ReverseDimensions, ArgType> XprType;
243 typedef typename XprType::Index Index;
244 static const int NumDims = internal::array_size<ReverseDimensions>::value;
245 typedef DSizes<Index, NumDims> Dimensions;
246
247 enum {
248 IsAligned = false,
249 PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
250 Layout = TensorEvaluator<ArgType, Device>::Layout,
251 CoordAccess = false, // to be implemented
252 RawAccess = false
253 };
254 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op,
255 const Device& device)
256 : Base(op, device) {}
257
258 typedef typename XprType::Scalar Scalar;
259 typedef typename XprType::CoeffReturnType CoeffReturnType;
260 typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
261 static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
262
263 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
264 const Dimensions& dimensions() const { return this->m_dimensions; }
265
266 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) {
267 return this->m_impl.coeffRef(this->reverseIndex(index));
268 }
269
270 template <int StoreMode> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
271 void writePacket(Index index, const PacketReturnType& x) {
272 EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
273 eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
274
275 // This code is pilfered from TensorMorphing.h
276 EIGEN_ALIGN_MAX CoeffReturnType values[PacketSize];
277 internal::pstore<CoeffReturnType, PacketReturnType>(values, x);
278 for (int i = 0; i < PacketSize; ++i) {
279 this->coeffRef(index+i) = values[i];
280 }
281 }
282
283};
284
285
286} // end namespace Eigen
287
288#endif // EIGEN_CXX11_TENSOR_TENSOR_REVERSE_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