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TensorAssign.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_ASSIGN_H
11#define EIGEN_CXX11_TENSOR_TENSOR_ASSIGN_H
12
13namespace Eigen {
14
23namespace internal {
24template<typename LhsXprType, typename RhsXprType>
25struct traits<TensorAssignOp<LhsXprType, RhsXprType> >
26{
27 typedef typename LhsXprType::Scalar Scalar;
28 typedef typename traits<LhsXprType>::StorageKind StorageKind;
29 typedef typename promote_index_type<typename traits<LhsXprType>::Index,
30 typename traits<RhsXprType>::Index>::type Index;
31 typedef typename LhsXprType::Nested LhsNested;
32 typedef typename RhsXprType::Nested RhsNested;
33 typedef typename remove_reference<LhsNested>::type _LhsNested;
34 typedef typename remove_reference<RhsNested>::type _RhsNested;
35 static const std::size_t NumDimensions = internal::traits<LhsXprType>::NumDimensions;
36 static const int Layout = internal::traits<LhsXprType>::Layout;
37 typedef typename traits<LhsXprType>::PointerType PointerType;
38
39 enum {
40 Flags = 0
41 };
42};
43
44template<typename LhsXprType, typename RhsXprType>
45struct eval<TensorAssignOp<LhsXprType, RhsXprType>, Eigen::Dense>
46{
47 typedef const TensorAssignOp<LhsXprType, RhsXprType>& type;
48};
49
50template<typename LhsXprType, typename RhsXprType>
51struct nested<TensorAssignOp<LhsXprType, RhsXprType>, 1, typename eval<TensorAssignOp<LhsXprType, RhsXprType> >::type>
52{
53 typedef TensorAssignOp<LhsXprType, RhsXprType> type;
54};
55
56} // end namespace internal
57
58
59
60template<typename LhsXprType, typename RhsXprType>
61class TensorAssignOp : public TensorBase<TensorAssignOp<LhsXprType, RhsXprType> >
62{
63 public:
64 typedef typename Eigen::internal::traits<TensorAssignOp>::Scalar Scalar;
65 typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
66 typedef typename LhsXprType::CoeffReturnType CoeffReturnType;
67 typedef typename Eigen::internal::nested<TensorAssignOp>::type Nested;
68 typedef typename Eigen::internal::traits<TensorAssignOp>::StorageKind StorageKind;
69 typedef typename Eigen::internal::traits<TensorAssignOp>::Index Index;
70
71 static const int NumDims = Eigen::internal::traits<TensorAssignOp>::NumDimensions;
72
73 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorAssignOp(LhsXprType& lhs, const RhsXprType& rhs)
74 : m_lhs_xpr(lhs), m_rhs_xpr(rhs) {}
75
77 EIGEN_DEVICE_FUNC
78 typename internal::remove_all<typename LhsXprType::Nested>::type&
79 lhsExpression() const { return *((typename internal::remove_all<typename LhsXprType::Nested>::type*)&m_lhs_xpr); }
80
81 EIGEN_DEVICE_FUNC
82 const typename internal::remove_all<typename RhsXprType::Nested>::type&
83 rhsExpression() const { return m_rhs_xpr; }
84
85 protected:
86 typename internal::remove_all<typename LhsXprType::Nested>::type& m_lhs_xpr;
87 const typename internal::remove_all<typename RhsXprType::Nested>::type& m_rhs_xpr;
88};
89
90
91template<typename LeftArgType, typename RightArgType, typename Device>
92struct TensorEvaluator<const TensorAssignOp<LeftArgType, RightArgType>, Device>
93{
94 typedef TensorAssignOp<LeftArgType, RightArgType> XprType;
95 typedef typename XprType::Index Index;
96 typedef typename XprType::Scalar Scalar;
97 typedef typename XprType::CoeffReturnType CoeffReturnType;
98 typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
99 typedef typename TensorEvaluator<RightArgType, Device>::Dimensions Dimensions;
100 typedef StorageMemory<CoeffReturnType, Device> Storage;
101 typedef typename Storage::Type EvaluatorPointerType;
102
103 static const int PacketSize = PacketType<CoeffReturnType, Device>::size;
104 static const int NumDims = XprType::NumDims;
105
106 enum {
107 IsAligned = int(TensorEvaluator<LeftArgType, Device>::IsAligned) &
108 int(TensorEvaluator<RightArgType, Device>::IsAligned),
109 PacketAccess = int(TensorEvaluator<LeftArgType, Device>::PacketAccess) &
110 int(TensorEvaluator<RightArgType, Device>::PacketAccess),
111 BlockAccess = int(TensorEvaluator<LeftArgType, Device>::BlockAccess) &
112 int(TensorEvaluator<RightArgType, Device>::BlockAccess),
113 PreferBlockAccess = int(TensorEvaluator<LeftArgType, Device>::PreferBlockAccess) |
114 int(TensorEvaluator<RightArgType, Device>::PreferBlockAccess),
115 Layout = TensorEvaluator<LeftArgType, Device>::Layout,
116 RawAccess = TensorEvaluator<LeftArgType, Device>::RawAccess
117 };
118
119 //===- Tensor block evaluation strategy (see TensorBlock.h) -------------===//
120 typedef internal::TensorBlockDescriptor<NumDims, Index> TensorBlockDesc;
121 typedef internal::TensorBlockScratchAllocator<Device> TensorBlockScratch;
122
123 typedef typename TensorEvaluator<const RightArgType, Device>::TensorBlock
124 RightTensorBlock;
125 //===--------------------------------------------------------------------===//
126
127 TensorEvaluator(const XprType& op, const Device& device) :
128 m_leftImpl(op.lhsExpression(), device),
129 m_rightImpl(op.rhsExpression(), device)
130 {
131 EIGEN_STATIC_ASSERT(
132 (static_cast<int>(TensorEvaluator<LeftArgType, Device>::Layout) ==
133 static_cast<int>(TensorEvaluator<RightArgType, Device>::Layout)),
134 YOU_MADE_A_PROGRAMMING_MISTAKE);
135 }
136
137 EIGEN_DEVICE_FUNC const Dimensions& dimensions() const
138 {
139 // The dimensions of the lhs and the rhs tensors should be equal to prevent
140 // overflows and ensure the result is fully initialized.
141 // TODO: use left impl instead if right impl dimensions are known at compile time.
142 return m_rightImpl.dimensions();
143 }
144
145 EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(EvaluatorPointerType) {
146 eigen_assert(dimensions_match(m_leftImpl.dimensions(), m_rightImpl.dimensions()));
147 m_leftImpl.evalSubExprsIfNeeded(NULL);
148 // If the lhs provides raw access to its storage area (i.e. if m_leftImpl.data() returns a non
149 // null value), attempt to evaluate the rhs expression in place. Returns true iff in place
150 // evaluation isn't supported and the caller still needs to manually assign the values generated
151 // by the rhs to the lhs.
152 return m_rightImpl.evalSubExprsIfNeeded(m_leftImpl.data());
153 }
154
155#ifdef EIGEN_USE_THREADS
156 template <typename EvalSubExprsCallback>
157 EIGEN_STRONG_INLINE void evalSubExprsIfNeededAsync(
158 EvaluatorPointerType, EvalSubExprsCallback done) {
159 m_leftImpl.evalSubExprsIfNeededAsync(nullptr, [this, done](bool) {
160 m_rightImpl.evalSubExprsIfNeededAsync(
161 m_leftImpl.data(), [done](bool need_assign) { done(need_assign); });
162 });
163 }
164#endif // EIGEN_USE_THREADS
165
166 EIGEN_STRONG_INLINE void cleanup() {
167 m_leftImpl.cleanup();
168 m_rightImpl.cleanup();
169 }
170
171 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalScalar(Index i) {
172 m_leftImpl.coeffRef(i) = m_rightImpl.coeff(i);
173 }
174 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalPacket(Index i) {
175
176 const int LhsStoreMode = TensorEvaluator<LeftArgType, Device>::IsAligned ? Aligned : Unaligned;
177 const int RhsLoadMode = TensorEvaluator<RightArgType, Device>::IsAligned ? Aligned : Unaligned;
178 m_leftImpl.template writePacket<LhsStoreMode>(i, m_rightImpl.template packet<RhsLoadMode>(i));
179 }
180 EIGEN_DEVICE_FUNC CoeffReturnType coeff(Index index) const
181 {
182 return m_leftImpl.coeff(index);
183 }
184 template<int LoadMode>
185 EIGEN_DEVICE_FUNC PacketReturnType packet(Index index) const
186 {
187 return m_leftImpl.template packet<LoadMode>(index);
188 }
189
190 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
191 costPerCoeff(bool vectorized) const {
192 // We assume that evalPacket or evalScalar is called to perform the
193 // assignment and account for the cost of the write here, but reduce left
194 // cost by one load because we are using m_leftImpl.coeffRef.
195 TensorOpCost left = m_leftImpl.costPerCoeff(vectorized);
196 return m_rightImpl.costPerCoeff(vectorized) +
197 TensorOpCost(
198 numext::maxi(0.0, left.bytes_loaded() - sizeof(CoeffReturnType)),
199 left.bytes_stored(), left.compute_cycles()) +
200 TensorOpCost(0, sizeof(CoeffReturnType), 0, vectorized, PacketSize);
201 }
202
203 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
204 internal::TensorBlockResourceRequirements getResourceRequirements() const {
205 return internal::TensorBlockResourceRequirements::merge(
206 m_leftImpl.getResourceRequirements(),
207 m_rightImpl.getResourceRequirements());
208 }
209
210 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalBlock(
211 TensorBlockDesc& desc, TensorBlockScratch& scratch) {
212 if (TensorEvaluator<LeftArgType, Device>::RawAccess &&
213 m_leftImpl.data() != NULL) {
214 // If destination has raw data access, we pass it as a potential
215 // destination for a block descriptor evaluation.
216 desc.template AddDestinationBuffer<Layout>(
217 /*dst_base=*/m_leftImpl.data() + desc.offset(),
218 /*dst_strides=*/internal::strides<Layout>(m_leftImpl.dimensions()));
219 }
220
221 RightTensorBlock block = m_rightImpl.block(desc, scratch, /*root_of_expr_ast=*/true);
222 // If block was evaluated into a destination, there is no need to do assignment.
223 if (block.kind() != internal::TensorBlockKind::kMaterializedInOutput) {
224 m_leftImpl.writeBlock(desc, block);
225 }
226 block.cleanup();
227 }
228
229#ifdef EIGEN_USE_SYCL
230 // binding placeholder accessors to a command group handler for SYCL
231 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void bind(cl::sycl::handler &cgh) const {
232 m_leftImpl.bind(cgh);
233 m_rightImpl.bind(cgh);
234 }
235#endif
236
237 EIGEN_DEVICE_FUNC EvaluatorPointerType data() const { return m_leftImpl.data(); }
238
239 private:
240 TensorEvaluator<LeftArgType, Device> m_leftImpl;
241 TensorEvaluator<RightArgType, Device> m_rightImpl;
242};
243
244}
245
246
247#endif // EIGEN_CXX11_TENSOR_TENSOR_ASSIGN_H
Namespace containing all symbols from the Eigen library.
EIGEN_DEFAULT_DENSE_INDEX_TYPE Index