TensorPatch.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) 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_PATCH_H
11 #define EIGEN_CXX11_TENSOR_TENSOR_PATCH_H
12 
13 namespace Eigen {
14 
22 namespace internal {
23 template<typename PatchDim, typename XprType>
24 struct traits<TensorPatchOp<PatchDim, XprType> > : public traits<XprType>
25 {
26  typedef typename XprType::Scalar Scalar;
28  typedef typename XprTraits::StorageKind StorageKind;
29  typedef typename XprTraits::Index Index;
30  typedef typename XprType::Nested Nested;
32  static const int NumDimensions = XprTraits::NumDimensions + 1;
33  static const int Layout = XprTraits::Layout;
34 };
35 
36 template<typename PatchDim, typename XprType>
37 struct eval<TensorPatchOp<PatchDim, XprType>, Eigen::Dense>
38 {
40 };
41 
42 template<typename PatchDim, typename XprType>
43 struct nested<TensorPatchOp<PatchDim, XprType>, 1, typename eval<TensorPatchOp<PatchDim, XprType> >::type>
44 {
46 };
47 
48 } // end namespace internal
49 
50 
51 
52 template<typename PatchDim, typename XprType>
53 class TensorPatchOp : public TensorBase<TensorPatchOp<PatchDim, XprType>, ReadOnlyAccessors>
54 {
55  public:
58  typedef typename XprType::CoeffReturnType CoeffReturnType;
62 
63  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorPatchOp(const XprType& expr, const PatchDim& patch_dims)
64  : m_xpr(expr), m_patch_dims(patch_dims) {}
65 
66  EIGEN_DEVICE_FUNC
67  const PatchDim& patch_dims() const { return m_patch_dims; }
68 
69  EIGEN_DEVICE_FUNC
71  expression() const { return m_xpr; }
72 
73  protected:
74  typename XprType::Nested m_xpr;
75  const PatchDim m_patch_dims;
76 };
77 
78 
79 // Eval as rvalue
80 template<typename PatchDim, typename ArgType, typename Device>
81 struct TensorEvaluator<const TensorPatchOp<PatchDim, ArgType>, Device>
82 {
84  typedef typename XprType::Index Index;
87  typedef typename XprType::Scalar Scalar;
91 
92 
93  enum {
94  IsAligned = false,
97  CoordAccess = false,
98  RawAccess = false
99  };
100 
101  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
102  : m_impl(op.expression(), device)
103  {
104  Index num_patches = 1;
105  const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
106  const PatchDim& patch_dims = op.patch_dims();
107  if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
108  for (int i = 0; i < NumDims-1; ++i) {
109  m_dimensions[i] = patch_dims[i];
110  num_patches *= (input_dims[i] - patch_dims[i] + 1);
111  }
112  m_dimensions[NumDims-1] = num_patches;
113 
114  m_inputStrides[0] = 1;
115  m_patchStrides[0] = 1;
116  for (int i = 1; i < NumDims-1; ++i) {
117  m_inputStrides[i] = m_inputStrides[i-1] * input_dims[i-1];
118  m_patchStrides[i] = m_patchStrides[i-1] * (input_dims[i-1] - patch_dims[i-1] + 1);
119  }
120  m_outputStrides[0] = 1;
121  for (int i = 1; i < NumDims; ++i) {
122  m_outputStrides[i] = m_outputStrides[i-1] * m_dimensions[i-1];
123  }
124  } else {
125  for (int i = 0; i < NumDims-1; ++i) {
126  m_dimensions[i+1] = patch_dims[i];
127  num_patches *= (input_dims[i] - patch_dims[i] + 1);
128  }
129  m_dimensions[0] = num_patches;
130 
131  m_inputStrides[NumDims-2] = 1;
132  m_patchStrides[NumDims-2] = 1;
133  for (int i = NumDims-3; i >= 0; --i) {
134  m_inputStrides[i] = m_inputStrides[i+1] * input_dims[i+1];
135  m_patchStrides[i] = m_patchStrides[i+1] * (input_dims[i+1] - patch_dims[i+1] + 1);
136  }
137  m_outputStrides[NumDims-1] = 1;
138  for (int i = NumDims-2; i >= 0; --i) {
139  m_outputStrides[i] = m_outputStrides[i+1] * m_dimensions[i+1];
140  }
141  }
142  }
143 
144  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
145 
146  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
147  m_impl.evalSubExprsIfNeeded(NULL);
148  return true;
149  }
150 
151  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
152  m_impl.cleanup();
153  }
154 
155  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
156  {
157  Index output_stride_index = (static_cast<int>(Layout) == static_cast<int>(ColMajor)) ? NumDims - 1 : 0;
158  // Find the location of the first element of the patch.
159  Index patchIndex = index / m_outputStrides[output_stride_index];
160  // Find the offset of the element wrt the location of the first element.
161  Index patchOffset = index - patchIndex * m_outputStrides[output_stride_index];
162  Index inputIndex = 0;
163  if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
164  for (int i = NumDims - 2; i > 0; --i) {
165  const Index patchIdx = patchIndex / m_patchStrides[i];
166  patchIndex -= patchIdx * m_patchStrides[i];
167  const Index offsetIdx = patchOffset / m_outputStrides[i];
168  patchOffset -= offsetIdx * m_outputStrides[i];
169  inputIndex += (patchIdx + offsetIdx) * m_inputStrides[i];
170  }
171  } else {
172  for (int i = 0; i < NumDims - 2; ++i) {
173  const Index patchIdx = patchIndex / m_patchStrides[i];
174  patchIndex -= patchIdx * m_patchStrides[i];
175  const Index offsetIdx = patchOffset / m_outputStrides[i+1];
176  patchOffset -= offsetIdx * m_outputStrides[i+1];
177  inputIndex += (patchIdx + offsetIdx) * m_inputStrides[i];
178  }
179  }
180  inputIndex += (patchIndex + patchOffset);
181  return m_impl.coeff(inputIndex);
182  }
183 
184  template<int LoadMode>
185  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
186  {
187  EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
188  eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
189 
190  Index output_stride_index = (static_cast<int>(Layout) == static_cast<int>(ColMajor)) ? NumDims - 1 : 0;
191  Index indices[2] = {index, index + PacketSize - 1};
192  Index patchIndices[2] = {indices[0] / m_outputStrides[output_stride_index],
193  indices[1] / m_outputStrides[output_stride_index]};
194  Index patchOffsets[2] = {indices[0] - patchIndices[0] * m_outputStrides[output_stride_index],
195  indices[1] - patchIndices[1] * m_outputStrides[output_stride_index]};
196 
197  Index inputIndices[2] = {0, 0};
198  if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
199  for (int i = NumDims - 2; i > 0; --i) {
200  const Index patchIdx[2] = {patchIndices[0] / m_patchStrides[i],
201  patchIndices[1] / m_patchStrides[i]};
202  patchIndices[0] -= patchIdx[0] * m_patchStrides[i];
203  patchIndices[1] -= patchIdx[1] * m_patchStrides[i];
204 
205  const Index offsetIdx[2] = {patchOffsets[0] / m_outputStrides[i],
206  patchOffsets[1] / m_outputStrides[i]};
207  patchOffsets[0] -= offsetIdx[0] * m_outputStrides[i];
208  patchOffsets[1] -= offsetIdx[1] * m_outputStrides[i];
209 
210  inputIndices[0] += (patchIdx[0] + offsetIdx[0]) * m_inputStrides[i];
211  inputIndices[1] += (patchIdx[1] + offsetIdx[1]) * m_inputStrides[i];
212  }
213  } else {
214  for (int i = 0; i < NumDims - 2; ++i) {
215  const Index patchIdx[2] = {patchIndices[0] / m_patchStrides[i],
216  patchIndices[1] / m_patchStrides[i]};
217  patchIndices[0] -= patchIdx[0] * m_patchStrides[i];
218  patchIndices[1] -= patchIdx[1] * m_patchStrides[i];
219 
220  const Index offsetIdx[2] = {patchOffsets[0] / m_outputStrides[i+1],
221  patchOffsets[1] / m_outputStrides[i+1]};
222  patchOffsets[0] -= offsetIdx[0] * m_outputStrides[i+1];
223  patchOffsets[1] -= offsetIdx[1] * m_outputStrides[i+1];
224 
225  inputIndices[0] += (patchIdx[0] + offsetIdx[0]) * m_inputStrides[i];
226  inputIndices[1] += (patchIdx[1] + offsetIdx[1]) * m_inputStrides[i];
227  }
228  }
229  inputIndices[0] += (patchIndices[0] + patchOffsets[0]);
230  inputIndices[1] += (patchIndices[1] + patchOffsets[1]);
231 
232  if (inputIndices[1] - inputIndices[0] == PacketSize - 1) {
233  PacketReturnType rslt = m_impl.template packet<Unaligned>(inputIndices[0]);
234  return rslt;
235  }
236  else {
237  EIGEN_ALIGN_MAX CoeffReturnType values[PacketSize];
238  values[0] = m_impl.coeff(inputIndices[0]);
239  values[PacketSize-1] = m_impl.coeff(inputIndices[1]);
240  for (int i = 1; i < PacketSize-1; ++i) {
241  values[i] = coeff(index+i);
242  }
243  PacketReturnType rslt = internal::pload<PacketReturnType>(values);
244  return rslt;
245  }
246  }
247 
248  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const {
249  const double compute_cost = NumDims * (TensorOpCost::DivCost<Index>() +
250  TensorOpCost::MulCost<Index>() +
251  2 * TensorOpCost::AddCost<Index>());
252  return m_impl.costPerCoeff(vectorized) +
253  TensorOpCost(0, 0, compute_cost, vectorized, PacketSize);
254  }
255 
256  EIGEN_DEVICE_FUNC Scalar* data() const { return NULL; }
257 
258  protected:
259  Dimensions m_dimensions;
263 
265 };
266 
267 } // end namespace Eigen
268 
269 #endif // EIGEN_CXX11_TENSOR_TENSOR_PATCH_H
SCALAR Scalar
Definition: bench_gemm.cpp:33
Eigen::internal::nested< TensorPatchOp >::type Nested
Definition: TensorPatch.h:59
#define EIGEN_STRONG_INLINE
Definition: Macros.h:494
XprType::Nested m_xpr
Definition: TensorPatch.h:74
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions & dimensions() const
XprType::CoeffReturnType CoeffReturnType
Definition: TensorPatch.h:58
EIGEN_DEVICE_FUNC const PatchDim & patch_dims() const
Definition: TensorPatch.h:67
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType &op, const Device &device)
Definition: TensorPatch.h:101
leaf::MyValues values
Namespace containing all symbols from the Eigen library.
Definition: jet.h:637
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar *)
Definition: TensorPatch.h:146
A cost model used to limit the number of threads used for evaluating tensor expression.
#define EIGEN_STATIC_ASSERT(CONDITION, MSG)
Definition: StaticAssert.h:124
vector< size_t > dimensions(L.begin(), L.end())
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
Definition: TensorPatch.h:155
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorPatchOp(const XprType &expr, const PatchDim &patch_dims)
Definition: TensorPatch.h:63
EIGEN_DEFAULT_DENSE_INDEX_TYPE Index
The Index type as used for the API.
Definition: Meta.h:33
#define eigen_assert(x)
Definition: Macros.h:579
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
Definition: TensorPatch.h:185
Eigen::internal::traits< TensorPatchOp >::StorageKind StorageKind
Definition: TensorPatch.h:60
EIGEN_DEVICE_FUNC const internal::remove_all< typename XprType::Nested >::type & expression() const
Definition: TensorPatch.h:71
#define NULL
Definition: ccolamd.c:609
Eigen::internal::traits< TensorPatchOp >::Scalar Scalar
Definition: TensorPatch.h:56
The tensor base class.
Definition: TensorBase.h:829
const PatchDim m_patch_dims
Definition: TensorPatch.h:75
Eigen::internal::traits< TensorPatchOp >::Index Index
Definition: TensorPatch.h:61
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions & dimensions() const
Definition: TensorPatch.h:144
#define EIGEN_ALIGN_MAX
Definition: Macros.h:757
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost costPerCoeff(bool vectorized) const
Definition: TensorPatch.h:248
Eigen::NumTraits< Scalar >::Real RealScalar
Definition: TensorPatch.h:57
PacketType< CoeffReturnType, Device >::type PacketReturnType
Definition: TensorPatch.h:89


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autogenerated on Sat May 8 2021 02:45:40