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TensorVolumePatch.h
1// This file is part of Eigen, a lightweight C++ template library
2// for linear algebra.
3
4#ifndef EIGEN_CXX11_TENSOR_TENSOR_VOLUME_PATCH_H
5#define EIGEN_CXX11_TENSOR_TENSOR_VOLUME_PATCH_H
6
7namespace Eigen {
8
24namespace internal {
25
26template<DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename XprType>
27struct traits<TensorVolumePatchOp<Planes, Rows, Cols, XprType> > : public traits<XprType>
28{
29 typedef typename internal::remove_const<typename XprType::Scalar>::type Scalar;
30 typedef traits<XprType> XprTraits;
31 typedef typename XprTraits::StorageKind StorageKind;
32 typedef typename XprTraits::Index Index;
33 typedef typename XprType::Nested Nested;
34 typedef typename remove_reference<Nested>::type _Nested;
35 static const int NumDimensions = XprTraits::NumDimensions + 1;
36 static const int Layout = XprTraits::Layout;
37 typedef typename XprTraits::PointerType PointerType;
38
39};
40
41template<DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename XprType>
42struct eval<TensorVolumePatchOp<Planes, Rows, Cols, XprType>, Eigen::Dense>
43{
44 typedef const TensorVolumePatchOp<Planes, Rows, Cols, XprType>& type;
45};
46
47template<DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename XprType>
48struct nested<TensorVolumePatchOp<Planes, Rows, Cols, XprType>, 1, typename eval<TensorVolumePatchOp<Planes, Rows, Cols, XprType> >::type>
49{
50 typedef TensorVolumePatchOp<Planes, Rows, Cols, XprType> type;
51};
52
53} // end namespace internal
54
55template<DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename XprType>
56class TensorVolumePatchOp : public TensorBase<TensorVolumePatchOp<Planes, Rows, Cols, XprType>, ReadOnlyAccessors>
57{
58 public:
59 typedef typename Eigen::internal::traits<TensorVolumePatchOp>::Scalar Scalar;
60 typedef typename Eigen::NumTraits<Scalar>::Real RealScalar;
61 typedef typename XprType::CoeffReturnType CoeffReturnType;
62 typedef typename Eigen::internal::nested<TensorVolumePatchOp>::type Nested;
63 typedef typename Eigen::internal::traits<TensorVolumePatchOp>::StorageKind StorageKind;
64 typedef typename Eigen::internal::traits<TensorVolumePatchOp>::Index Index;
65
66 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorVolumePatchOp(const XprType& expr, DenseIndex patch_planes, DenseIndex patch_rows, DenseIndex patch_cols,
67 DenseIndex plane_strides, DenseIndex row_strides, DenseIndex col_strides,
68 DenseIndex in_plane_strides, DenseIndex in_row_strides, DenseIndex in_col_strides,
69 DenseIndex plane_inflate_strides, DenseIndex row_inflate_strides, DenseIndex col_inflate_strides,
70 PaddingType padding_type, Scalar padding_value)
71 : m_xpr(expr), m_patch_planes(patch_planes), m_patch_rows(patch_rows), m_patch_cols(patch_cols),
72 m_plane_strides(plane_strides), m_row_strides(row_strides), m_col_strides(col_strides),
73 m_in_plane_strides(in_plane_strides), m_in_row_strides(in_row_strides), m_in_col_strides(in_col_strides),
74 m_plane_inflate_strides(plane_inflate_strides), m_row_inflate_strides(row_inflate_strides), m_col_inflate_strides(col_inflate_strides),
75 m_padding_explicit(false), m_padding_top_z(0), m_padding_bottom_z(0), m_padding_top(0), m_padding_bottom(0), m_padding_left(0), m_padding_right(0),
76 m_padding_type(padding_type), m_padding_value(padding_value) {}
77
78 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorVolumePatchOp(const XprType& expr, DenseIndex patch_planes, DenseIndex patch_rows, DenseIndex patch_cols,
79 DenseIndex plane_strides, DenseIndex row_strides, DenseIndex col_strides,
80 DenseIndex in_plane_strides, DenseIndex in_row_strides, DenseIndex in_col_strides,
81 DenseIndex plane_inflate_strides, DenseIndex row_inflate_strides, DenseIndex col_inflate_strides,
82 DenseIndex padding_top_z, DenseIndex padding_bottom_z,
83 DenseIndex padding_top, DenseIndex padding_bottom,
84 DenseIndex padding_left, DenseIndex padding_right,
85 Scalar padding_value)
86 : m_xpr(expr), m_patch_planes(patch_planes), m_patch_rows(patch_rows), m_patch_cols(patch_cols),
87 m_plane_strides(plane_strides), m_row_strides(row_strides), m_col_strides(col_strides),
88 m_in_plane_strides(in_plane_strides), m_in_row_strides(in_row_strides), m_in_col_strides(in_col_strides),
89 m_plane_inflate_strides(plane_inflate_strides), m_row_inflate_strides(row_inflate_strides), m_col_inflate_strides(col_inflate_strides),
90 m_padding_explicit(true), m_padding_top_z(padding_top_z), m_padding_bottom_z(padding_bottom_z), m_padding_top(padding_top), m_padding_bottom(padding_bottom),
91 m_padding_left(padding_left), m_padding_right(padding_right),
92 m_padding_type(PADDING_VALID), m_padding_value(padding_value) {}
93
94 EIGEN_DEVICE_FUNC
95 DenseIndex patch_planes() const { return m_patch_planes; }
96 EIGEN_DEVICE_FUNC
97 DenseIndex patch_rows() const { return m_patch_rows; }
98 EIGEN_DEVICE_FUNC
99 DenseIndex patch_cols() const { return m_patch_cols; }
100 EIGEN_DEVICE_FUNC
101 DenseIndex plane_strides() const { return m_plane_strides; }
102 EIGEN_DEVICE_FUNC
103 DenseIndex row_strides() const { return m_row_strides; }
104 EIGEN_DEVICE_FUNC
105 DenseIndex col_strides() const { return m_col_strides; }
106 EIGEN_DEVICE_FUNC
107 DenseIndex in_plane_strides() const { return m_in_plane_strides; }
108 EIGEN_DEVICE_FUNC
109 DenseIndex in_row_strides() const { return m_in_row_strides; }
110 EIGEN_DEVICE_FUNC
111 DenseIndex in_col_strides() const { return m_in_col_strides; }
112 EIGEN_DEVICE_FUNC
113 DenseIndex plane_inflate_strides() const { return m_plane_inflate_strides; }
114 EIGEN_DEVICE_FUNC
115 DenseIndex row_inflate_strides() const { return m_row_inflate_strides; }
116 EIGEN_DEVICE_FUNC
117 DenseIndex col_inflate_strides() const { return m_col_inflate_strides; }
118 EIGEN_DEVICE_FUNC
119 bool padding_explicit() const { return m_padding_explicit; }
120 EIGEN_DEVICE_FUNC
121 DenseIndex padding_top_z() const { return m_padding_top_z; }
122 EIGEN_DEVICE_FUNC
123 DenseIndex padding_bottom_z() const { return m_padding_bottom_z; }
124 EIGEN_DEVICE_FUNC
125 DenseIndex padding_top() const { return m_padding_top; }
126 EIGEN_DEVICE_FUNC
127 DenseIndex padding_bottom() const { return m_padding_bottom; }
128 EIGEN_DEVICE_FUNC
129 DenseIndex padding_left() const { return m_padding_left; }
130 EIGEN_DEVICE_FUNC
131 DenseIndex padding_right() const { return m_padding_right; }
132 EIGEN_DEVICE_FUNC
133 PaddingType padding_type() const { return m_padding_type; }
134 EIGEN_DEVICE_FUNC
135 Scalar padding_value() const { return m_padding_value; }
136
137 EIGEN_DEVICE_FUNC
138 const typename internal::remove_all<typename XprType::Nested>::type&
139 expression() const { return m_xpr; }
140
141 protected:
142 typename XprType::Nested m_xpr;
143 const DenseIndex m_patch_planes;
144 const DenseIndex m_patch_rows;
145 const DenseIndex m_patch_cols;
146 const DenseIndex m_plane_strides;
147 const DenseIndex m_row_strides;
148 const DenseIndex m_col_strides;
149 const DenseIndex m_in_plane_strides;
150 const DenseIndex m_in_row_strides;
151 const DenseIndex m_in_col_strides;
152 const DenseIndex m_plane_inflate_strides;
153 const DenseIndex m_row_inflate_strides;
154 const DenseIndex m_col_inflate_strides;
155 const bool m_padding_explicit;
156 const DenseIndex m_padding_top_z;
157 const DenseIndex m_padding_bottom_z;
158 const DenseIndex m_padding_top;
159 const DenseIndex m_padding_bottom;
160 const DenseIndex m_padding_left;
161 const DenseIndex m_padding_right;
162 const PaddingType m_padding_type;
163 const Scalar m_padding_value;
164};
165
166
167// Eval as rvalue
168template<DenseIndex Planes, DenseIndex Rows, DenseIndex Cols, typename ArgType, typename Device>
169struct TensorEvaluator<const TensorVolumePatchOp<Planes, Rows, Cols, ArgType>, Device>
170{
171 typedef TensorVolumePatchOp<Planes, Rows, Cols, ArgType> XprType;
172 typedef typename XprType::Index Index;
173 static const int NumInputDims = internal::array_size<typename TensorEvaluator<ArgType, Device>::Dimensions>::value;
174 static const int NumDims = NumInputDims + 1;
175 typedef DSizes<Index, NumDims> Dimensions;
176 typedef typename internal::remove_const<typename XprType::Scalar>::type Scalar;
177 typedef typename XprType::CoeffReturnType CoeffReturnType;
178 typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
179 static const int PacketSize = PacketType<CoeffReturnType, Device>::size;
180 typedef StorageMemory<CoeffReturnType, Device> Storage;
181 typedef typename Storage::Type EvaluatorPointerType;
182
183 enum {
184 IsAligned = false,
185 PacketAccess = TensorEvaluator<ArgType, Device>::PacketAccess,
186 BlockAccess = false,
187 PreferBlockAccess = TensorEvaluator<ArgType, Device>::PreferBlockAccess,
188 Layout = TensorEvaluator<ArgType, Device>::Layout,
189 CoordAccess = false,
190 RawAccess = false
191 };
192
193 //===- Tensor block evaluation strategy (see TensorBlock.h) -------------===//
194 typedef internal::TensorBlockNotImplemented TensorBlock;
195 //===--------------------------------------------------------------------===//
196
197 EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device) :
198 m_impl(op.expression(), device)
199 {
200 EIGEN_STATIC_ASSERT((NumDims >= 5), YOU_MADE_A_PROGRAMMING_MISTAKE);
201
202 m_paddingValue = op.padding_value();
203
204 const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
205
206 // Cache a few variables.
207 if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
208 m_inputDepth = input_dims[0];
209 m_inputPlanes = input_dims[1];
210 m_inputRows = input_dims[2];
211 m_inputCols = input_dims[3];
212 } else {
213 m_inputDepth = input_dims[NumInputDims-1];
214 m_inputPlanes = input_dims[NumInputDims-2];
215 m_inputRows = input_dims[NumInputDims-3];
216 m_inputCols = input_dims[NumInputDims-4];
217 }
218
219 m_plane_strides = op.plane_strides();
220 m_row_strides = op.row_strides();
221 m_col_strides = op.col_strides();
222
223 // Input strides and effective input/patch size
224 m_in_plane_strides = op.in_plane_strides();
225 m_in_row_strides = op.in_row_strides();
226 m_in_col_strides = op.in_col_strides();
227 m_plane_inflate_strides = op.plane_inflate_strides();
228 m_row_inflate_strides = op.row_inflate_strides();
229 m_col_inflate_strides = op.col_inflate_strides();
230
231 // The "effective" spatial size after inflating data with zeros.
232 m_input_planes_eff = (m_inputPlanes - 1) * m_plane_inflate_strides + 1;
233 m_input_rows_eff = (m_inputRows - 1) * m_row_inflate_strides + 1;
234 m_input_cols_eff = (m_inputCols - 1) * m_col_inflate_strides + 1;
235 m_patch_planes_eff = op.patch_planes() + (op.patch_planes() - 1) * (m_in_plane_strides - 1);
236 m_patch_rows_eff = op.patch_rows() + (op.patch_rows() - 1) * (m_in_row_strides - 1);
237 m_patch_cols_eff = op.patch_cols() + (op.patch_cols() - 1) * (m_in_col_strides - 1);
238
239 if (op.padding_explicit()) {
240 m_outputPlanes = numext::ceil((m_input_planes_eff + op.padding_top_z() + op.padding_bottom_z() - m_patch_planes_eff + 1.f) / static_cast<float>(m_plane_strides));
241 m_outputRows = numext::ceil((m_input_rows_eff + op.padding_top() + op.padding_bottom() - m_patch_rows_eff + 1.f) / static_cast<float>(m_row_strides));
242 m_outputCols = numext::ceil((m_input_cols_eff + op.padding_left() + op.padding_right() - m_patch_cols_eff + 1.f) / static_cast<float>(m_col_strides));
243 m_planePaddingTop = op.padding_top_z();
244 m_rowPaddingTop = op.padding_top();
245 m_colPaddingLeft = op.padding_left();
246 } else {
247 // Computing padding from the type
248 switch (op.padding_type()) {
249 case PADDING_VALID:
250 m_outputPlanes = numext::ceil((m_input_planes_eff - m_patch_planes_eff + 1.f) / static_cast<float>(m_plane_strides));
251 m_outputRows = numext::ceil((m_input_rows_eff - m_patch_rows_eff + 1.f) / static_cast<float>(m_row_strides));
252 m_outputCols = numext::ceil((m_input_cols_eff - m_patch_cols_eff + 1.f) / static_cast<float>(m_col_strides));
253 m_planePaddingTop = 0;
254 m_rowPaddingTop = 0;
255 m_colPaddingLeft = 0;
256 break;
257 case PADDING_SAME: {
258 m_outputPlanes = numext::ceil(m_input_planes_eff / static_cast<float>(m_plane_strides));
259 m_outputRows = numext::ceil(m_input_rows_eff / static_cast<float>(m_row_strides));
260 m_outputCols = numext::ceil(m_input_cols_eff / static_cast<float>(m_col_strides));
261 const Index dz = (m_outputPlanes - 1) * m_plane_strides + m_patch_planes_eff - m_input_planes_eff;
262 const Index dy = (m_outputRows - 1) * m_row_strides + m_patch_rows_eff - m_input_rows_eff;
263 const Index dx = (m_outputCols - 1) * m_col_strides + m_patch_cols_eff - m_input_cols_eff;
264 m_planePaddingTop = dz / 2;
265 m_rowPaddingTop = dy / 2;
266 m_colPaddingLeft = dx / 2;
267 break;
268 }
269 default:
270 eigen_assert(false && "unexpected padding");
271 }
272 }
273 eigen_assert(m_outputRows > 0);
274 eigen_assert(m_outputCols > 0);
275 eigen_assert(m_outputPlanes > 0);
276
277 // Dimensions for result of extraction.
278 if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
279 // ColMajor
280 // 0: depth
281 // 1: patch_planes
282 // 2: patch_rows
283 // 3: patch_cols
284 // 4: number of patches
285 // 5 and beyond: anything else (such as batch).
286 m_dimensions[0] = input_dims[0];
287 m_dimensions[1] = op.patch_planes();
288 m_dimensions[2] = op.patch_rows();
289 m_dimensions[3] = op.patch_cols();
290 m_dimensions[4] = m_outputPlanes * m_outputRows * m_outputCols;
291 for (int i = 5; i < NumDims; ++i) {
292 m_dimensions[i] = input_dims[i-1];
293 }
294 } else {
295 // RowMajor
296 // NumDims-1: depth
297 // NumDims-2: patch_planes
298 // NumDims-3: patch_rows
299 // NumDims-4: patch_cols
300 // NumDims-5: number of patches
301 // NumDims-6 and beyond: anything else (such as batch).
302 m_dimensions[NumDims-1] = input_dims[NumInputDims-1];
303 m_dimensions[NumDims-2] = op.patch_planes();
304 m_dimensions[NumDims-3] = op.patch_rows();
305 m_dimensions[NumDims-4] = op.patch_cols();
306 m_dimensions[NumDims-5] = m_outputPlanes * m_outputRows * m_outputCols;
307 for (int i = NumDims-6; i >= 0; --i) {
308 m_dimensions[i] = input_dims[i];
309 }
310 }
311
312 // Strides for the output tensor.
313 if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
314 m_rowStride = m_dimensions[1];
315 m_colStride = m_dimensions[2] * m_rowStride;
316 m_patchStride = m_colStride * m_dimensions[3] * m_dimensions[0];
317 m_otherStride = m_patchStride * m_dimensions[4];
318 } else {
319 m_rowStride = m_dimensions[NumDims-2];
320 m_colStride = m_dimensions[NumDims-3] * m_rowStride;
321 m_patchStride = m_colStride * m_dimensions[NumDims-4] * m_dimensions[NumDims-1];
322 m_otherStride = m_patchStride * m_dimensions[NumDims-5];
323 }
324
325 // Strides for navigating through the input tensor.
326 m_planeInputStride = m_inputDepth;
327 m_rowInputStride = m_inputDepth * m_inputPlanes;
328 m_colInputStride = m_inputDepth * m_inputRows * m_inputPlanes;
329 m_otherInputStride = m_inputDepth * m_inputRows * m_inputCols * m_inputPlanes;
330
331 m_outputPlanesRows = m_outputPlanes * m_outputRows;
332
333 // Fast representations of different variables.
334 m_fastOtherStride = internal::TensorIntDivisor<Index>(m_otherStride);
335
336 m_fastPatchStride = internal::TensorIntDivisor<Index>(m_patchStride);
337 m_fastColStride = internal::TensorIntDivisor<Index>(m_colStride);
338 m_fastRowStride = internal::TensorIntDivisor<Index>(m_rowStride);
339 m_fastInputRowStride = internal::TensorIntDivisor<Index>(m_row_inflate_strides);
340 m_fastInputColStride = internal::TensorIntDivisor<Index>(m_col_inflate_strides);
341 m_fastInputPlaneStride = internal::TensorIntDivisor<Index>(m_plane_inflate_strides);
342 m_fastInputColsEff = internal::TensorIntDivisor<Index>(m_input_cols_eff);
343 m_fastOutputPlanes = internal::TensorIntDivisor<Index>(m_outputPlanes);
344 m_fastOutputPlanesRows = internal::TensorIntDivisor<Index>(m_outputPlanesRows);
345
346 if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
347 m_fastOutputDepth = internal::TensorIntDivisor<Index>(m_dimensions[0]);
348 } else {
349 m_fastOutputDepth = internal::TensorIntDivisor<Index>(m_dimensions[NumDims-1]);
350 }
351 }
352
353 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
354
355 EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(EvaluatorPointerType /*data*/) {
356 m_impl.evalSubExprsIfNeeded(NULL);
357 return true;
358 }
359
360 EIGEN_STRONG_INLINE void cleanup() {
361 m_impl.cleanup();
362 }
363
364 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
365 {
366 // Patch index corresponding to the passed in index.
367 const Index patchIndex = index / m_fastPatchStride;
368
369 // Spatial offset within the patch. This has to be translated into 3D
370 // coordinates within the patch.
371 const Index patchOffset = (index - patchIndex * m_patchStride) / m_fastOutputDepth;
372
373 // Batch, etc.
374 const Index otherIndex = (NumDims == 5) ? 0 : index / m_fastOtherStride;
375 const Index patch3DIndex = (NumDims == 5) ? patchIndex : (index - otherIndex * m_otherStride) / m_fastPatchStride;
376
377 // Calculate column index in the input original tensor.
378 const Index colIndex = patch3DIndex / m_fastOutputPlanesRows;
379 const Index colOffset = patchOffset / m_fastColStride;
380 const Index inputCol = colIndex * m_col_strides + colOffset * m_in_col_strides - m_colPaddingLeft;
381 const Index origInputCol = (m_col_inflate_strides == 1) ? inputCol : ((inputCol >= 0) ? (inputCol / m_fastInputColStride) : 0);
382 if (inputCol < 0 || inputCol >= m_input_cols_eff ||
383 ((m_col_inflate_strides != 1) && (inputCol != origInputCol * m_col_inflate_strides))) {
384 return Scalar(m_paddingValue);
385 }
386
387 // Calculate row index in the original input tensor.
388 const Index rowIndex = (patch3DIndex - colIndex * m_outputPlanesRows) / m_fastOutputPlanes;
389 const Index rowOffset = (patchOffset - colOffset * m_colStride) / m_fastRowStride;
390 const Index inputRow = rowIndex * m_row_strides + rowOffset * m_in_row_strides - m_rowPaddingTop;
391 const Index origInputRow = (m_row_inflate_strides == 1) ? inputRow : ((inputRow >= 0) ? (inputRow / m_fastInputRowStride) : 0);
392 if (inputRow < 0 || inputRow >= m_input_rows_eff ||
393 ((m_row_inflate_strides != 1) && (inputRow != origInputRow * m_row_inflate_strides))) {
394 return Scalar(m_paddingValue);
395 }
396
397 // Calculate plane index in the original input tensor.
398 const Index planeIndex = (patch3DIndex - m_outputPlanes * (colIndex * m_outputRows + rowIndex));
399 const Index planeOffset = patchOffset - colOffset * m_colStride - rowOffset * m_rowStride;
400 const Index inputPlane = planeIndex * m_plane_strides + planeOffset * m_in_plane_strides - m_planePaddingTop;
401 const Index origInputPlane = (m_plane_inflate_strides == 1) ? inputPlane : ((inputPlane >= 0) ? (inputPlane / m_fastInputPlaneStride) : 0);
402 if (inputPlane < 0 || inputPlane >= m_input_planes_eff ||
403 ((m_plane_inflate_strides != 1) && (inputPlane != origInputPlane * m_plane_inflate_strides))) {
404 return Scalar(m_paddingValue);
405 }
406
407 const int depth_index = static_cast<int>(Layout) == static_cast<int>(ColMajor) ? 0 : NumDims - 1;
408 const Index depth = index - (index / m_fastOutputDepth) * m_dimensions[depth_index];
409
410 const Index inputIndex = depth +
411 origInputRow * m_rowInputStride +
412 origInputCol * m_colInputStride +
413 origInputPlane * m_planeInputStride +
414 otherIndex * m_otherInputStride;
415
416 return m_impl.coeff(inputIndex);
417 }
418
419 template<int LoadMode>
420 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
421 {
422 EIGEN_STATIC_ASSERT((PacketSize > 1), YOU_MADE_A_PROGRAMMING_MISTAKE)
423 eigen_assert(index+PacketSize-1 < dimensions().TotalSize());
424
425 if (m_in_row_strides != 1 || m_in_col_strides != 1 || m_row_inflate_strides != 1 || m_col_inflate_strides != 1 ||
426 m_in_plane_strides != 1 || m_plane_inflate_strides != 1) {
427 return packetWithPossibleZero(index);
428 }
429
430 const Index indices[2] = {index, index + PacketSize - 1};
431 const Index patchIndex = indices[0] / m_fastPatchStride;
432 if (patchIndex != indices[1] / m_fastPatchStride) {
433 return packetWithPossibleZero(index);
434 }
435 const Index otherIndex = (NumDims == 5) ? 0 : indices[0] / m_fastOtherStride;
436 eigen_assert(otherIndex == indices[1] / m_fastOtherStride);
437
438 // Find the offset of the element wrt the location of the first element.
439 const Index patchOffsets[2] = {(indices[0] - patchIndex * m_patchStride) / m_fastOutputDepth,
440 (indices[1] - patchIndex * m_patchStride) / m_fastOutputDepth};
441
442 const Index patch3DIndex = (NumDims == 5) ? patchIndex : (indices[0] - otherIndex * m_otherStride) / m_fastPatchStride;
443 eigen_assert(patch3DIndex == (indices[1] - otherIndex * m_otherStride) / m_fastPatchStride);
444
445 const Index colIndex = patch3DIndex / m_fastOutputPlanesRows;
446 const Index colOffsets[2] = {
447 patchOffsets[0] / m_fastColStride,
448 patchOffsets[1] / m_fastColStride};
449
450 // Calculate col indices in the original input tensor.
451 const Index inputCols[2] = {
452 colIndex * m_col_strides + colOffsets[0] - m_colPaddingLeft,
453 colIndex * m_col_strides + colOffsets[1] - m_colPaddingLeft};
454 if (inputCols[1] < 0 || inputCols[0] >= m_inputCols) {
455 return internal::pset1<PacketReturnType>(Scalar(m_paddingValue));
456 }
457
458 if (inputCols[0] != inputCols[1]) {
459 return packetWithPossibleZero(index);
460 }
461
462 const Index rowIndex = (patch3DIndex - colIndex * m_outputPlanesRows) / m_fastOutputPlanes;
463 const Index rowOffsets[2] = {
464 (patchOffsets[0] - colOffsets[0] * m_colStride) / m_fastRowStride,
465 (patchOffsets[1] - colOffsets[1] * m_colStride) / m_fastRowStride};
466 eigen_assert(rowOffsets[0] <= rowOffsets[1]);
467 // Calculate col indices in the original input tensor.
468 const Index inputRows[2] = {
469 rowIndex * m_row_strides + rowOffsets[0] - m_rowPaddingTop,
470 rowIndex * m_row_strides + rowOffsets[1] - m_rowPaddingTop};
471
472 if (inputRows[1] < 0 || inputRows[0] >= m_inputRows) {
473 return internal::pset1<PacketReturnType>(Scalar(m_paddingValue));
474 }
475
476 if (inputRows[0] != inputRows[1]) {
477 return packetWithPossibleZero(index);
478 }
479
480 const Index planeIndex = (patch3DIndex - m_outputPlanes * (colIndex * m_outputRows + rowIndex));
481 const Index planeOffsets[2] = {
482 patchOffsets[0] - colOffsets[0] * m_colStride - rowOffsets[0] * m_rowStride,
483 patchOffsets[1] - colOffsets[1] * m_colStride - rowOffsets[1] * m_rowStride};
484 eigen_assert(planeOffsets[0] <= planeOffsets[1]);
485 const Index inputPlanes[2] = {
486 planeIndex * m_plane_strides + planeOffsets[0] - m_planePaddingTop,
487 planeIndex * m_plane_strides + planeOffsets[1] - m_planePaddingTop};
488
489 if (inputPlanes[1] < 0 || inputPlanes[0] >= m_inputPlanes) {
490 return internal::pset1<PacketReturnType>(Scalar(m_paddingValue));
491 }
492
493 if (inputPlanes[0] >= 0 && inputPlanes[1] < m_inputPlanes) {
494 // no padding
495 const int depth_index = static_cast<int>(Layout) == static_cast<int>(ColMajor) ? 0 : NumDims - 1;
496 const Index depth = index - (index / m_fastOutputDepth) * m_dimensions[depth_index];
497 const Index inputIndex = depth +
498 inputRows[0] * m_rowInputStride +
499 inputCols[0] * m_colInputStride +
500 m_planeInputStride * inputPlanes[0] +
501 otherIndex * m_otherInputStride;
502 return m_impl.template packet<Unaligned>(inputIndex);
503 }
504
505 return packetWithPossibleZero(index);
506 }
507
508 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
509 costPerCoeff(bool vectorized) const {
510 const double compute_cost =
511 10 * TensorOpCost::DivCost<Index>() + 21 * TensorOpCost::MulCost<Index>() +
512 8 * TensorOpCost::AddCost<Index>();
513 return TensorOpCost(0, 0, compute_cost, vectorized, PacketSize);
514 }
515
516 EIGEN_DEVICE_FUNC EvaluatorPointerType data() const { return NULL; }
517
518 const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; }
519
520
521 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index planePaddingTop() const { return m_planePaddingTop; }
522 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index rowPaddingTop() const { return m_rowPaddingTop; }
523 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index colPaddingLeft() const { return m_colPaddingLeft; }
524 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index outputPlanes() const { return m_outputPlanes; }
525 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index outputRows() const { return m_outputRows; }
526 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index outputCols() const { return m_outputCols; }
527 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index userPlaneStride() const { return m_plane_strides; }
528 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index userRowStride() const { return m_row_strides; }
529 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index userColStride() const { return m_col_strides; }
530 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index userInPlaneStride() const { return m_in_plane_strides; }
531 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index userInRowStride() const { return m_in_row_strides; }
532 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index userInColStride() const { return m_in_col_strides; }
533 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index planeInflateStride() const { return m_plane_inflate_strides; }
534 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index rowInflateStride() const { return m_row_inflate_strides; }
535 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index colInflateStride() const { return m_col_inflate_strides; }
536
537#ifdef EIGEN_USE_SYCL
538 // binding placeholder accessors to a command group handler for SYCL
539 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void bind(cl::sycl::handler &cgh) const {
540 m_impl.bind(cgh);
541 }
542#endif
543 protected:
544 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetWithPossibleZero(Index index) const
545 {
546 EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
547 EIGEN_UNROLL_LOOP
548 for (int i = 0; i < PacketSize; ++i) {
549 values[i] = coeff(index+i);
550 }
551 PacketReturnType rslt = internal::pload<PacketReturnType>(values);
552 return rslt;
553 }
554
555 Dimensions m_dimensions;
556
557 // Parameters passed to the constructor.
558 Index m_plane_strides;
559 Index m_row_strides;
560 Index m_col_strides;
561
562 Index m_outputPlanes;
563 Index m_outputRows;
564 Index m_outputCols;
565
566 Index m_planePaddingTop;
567 Index m_rowPaddingTop;
568 Index m_colPaddingLeft;
569
570 Index m_in_plane_strides;
571 Index m_in_row_strides;
572 Index m_in_col_strides;
573
574 Index m_plane_inflate_strides;
575 Index m_row_inflate_strides;
576 Index m_col_inflate_strides;
577
578 // Cached input size.
579 Index m_inputDepth;
580 Index m_inputPlanes;
581 Index m_inputRows;
582 Index m_inputCols;
583
584 // Other cached variables.
585 Index m_outputPlanesRows;
586
587 // Effective input/patch post-inflation size.
588 Index m_input_planes_eff;
589 Index m_input_rows_eff;
590 Index m_input_cols_eff;
591 Index m_patch_planes_eff;
592 Index m_patch_rows_eff;
593 Index m_patch_cols_eff;
594
595 // Strides for the output tensor.
596 Index m_otherStride;
597 Index m_patchStride;
598 Index m_rowStride;
599 Index m_colStride;
600
601 // Strides for the input tensor.
602 Index m_planeInputStride;
603 Index m_rowInputStride;
604 Index m_colInputStride;
605 Index m_otherInputStride;
606
607 internal::TensorIntDivisor<Index> m_fastOtherStride;
608 internal::TensorIntDivisor<Index> m_fastPatchStride;
609 internal::TensorIntDivisor<Index> m_fastColStride;
610 internal::TensorIntDivisor<Index> m_fastRowStride;
611 internal::TensorIntDivisor<Index> m_fastInputPlaneStride;
612 internal::TensorIntDivisor<Index> m_fastInputRowStride;
613 internal::TensorIntDivisor<Index> m_fastInputColStride;
614 internal::TensorIntDivisor<Index> m_fastInputColsEff;
615 internal::TensorIntDivisor<Index> m_fastOutputPlanesRows;
616 internal::TensorIntDivisor<Index> m_fastOutputPlanes;
617 internal::TensorIntDivisor<Index> m_fastOutputDepth;
618
619 Scalar m_paddingValue;
620
621 TensorEvaluator<ArgType, Device> m_impl;
622
623
624};
625
626
627} // end namespace Eigen
628
629#endif // EIGEN_CXX11_TENSOR_TENSOR_VOLUME_PATCH_H
Namespace containing all symbols from the Eigen library.
EIGEN_DEFAULT_DENSE_INDEX_TYPE Index