cxx11_tensor_morphing.cpp
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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 #include "main.h"
11 
12 #include <Eigen/CXX11/Tensor>
13 
14 using Eigen::Tensor;
15 
16 template<typename>
17 static void test_simple_reshape()
18 {
19  Tensor<float, 5> tensor1(2,3,1,7,1);
20  tensor1.setRandom();
21 
22  Tensor<float, 3> tensor2(2,3,7);
23  Tensor<float, 2> tensor3(6,7);
24  Tensor<float, 2> tensor4(2,21);
25 
26  Tensor<float, 3>::Dimensions dim1(2,3,7);
27  tensor2 = tensor1.reshape(dim1);
29  tensor3 = tensor1.reshape(dim2);
31  tensor4 = tensor1.reshape(dim1).reshape(dim3);
32 
33  for (int i = 0; i < 2; ++i) {
34  for (int j = 0; j < 3; ++j) {
35  for (int k = 0; k < 7; ++k) {
36  VERIFY_IS_EQUAL(tensor1(i,j,0,k,0), tensor2(i,j,k));
37  VERIFY_IS_EQUAL(tensor1(i,j,0,k,0), tensor3(i+2*j,k));
38  VERIFY_IS_EQUAL(tensor1(i,j,0,k,0), tensor4(i,j+3*k));
39  }
40  }
41  }
42 }
43 
44 template <typename>
45 static void test_static_reshape() {
46 #if defined(EIGEN_HAS_INDEX_LIST)
47  using Eigen::type2index;
48 
49  Tensor<float, 5> tensor(2, 3, 1, 7, 1);
50  tensor.setRandom();
51 
52  // New dimensions: [2, 3, 7]
53  Eigen::IndexList<type2index<2>, type2index<3>, type2index<7>> dim;
54  Tensor<float, 3> reshaped = tensor.reshape(static_cast<Eigen::DSizes<ptrdiff_t,3>>(dim));
55 
56  for (int i = 0; i < 2; ++i) {
57  for (int j = 0; j < 3; ++j) {
58  for (int k = 0; k < 7; ++k) {
59  VERIFY_IS_EQUAL(tensor(i, j, 0, k, 0), reshaped(i, j, k));
60  }
61  }
62  }
63 #endif
64 }
65 
66 template <typename>
67 static void test_reshape_in_expr() {
68  MatrixXf m1(2,3*5*7*11);
69  MatrixXf m2(3*5*7*11,13);
70  m1.setRandom();
71  m2.setRandom();
72  MatrixXf m3 = m1 * m2;
73 
74  TensorMap<Tensor<float, 5>> tensor1(m1.data(), 2,3,5,7,11);
75  TensorMap<Tensor<float, 5>> tensor2(m2.data(), 3,5,7,11,13);
76  Tensor<float, 2>::Dimensions newDims1(2,3*5*7*11);
77  Tensor<float, 2>::Dimensions newDims2(3*5*7*11,13);
79  array<DimPair, 1> contract_along{{DimPair(1, 0)}};
80  Tensor<float, 2> tensor3(2,13);
81  tensor3 = tensor1.reshape(newDims1).contract(tensor2.reshape(newDims2), contract_along);
82 
83  Map<MatrixXf> res(tensor3.data(), 2, 13);
84  for (int i = 0; i < 2; ++i) {
85  for (int j = 0; j < 13; ++j) {
86  VERIFY_IS_APPROX(res(i,j), m3(i,j));
87  }
88  }
89 }
90 
91 template<typename>
93 {
94  Tensor<float, 3> tensor(2,3,7);
95  tensor.setRandom();
96 
97  Tensor<float, 2> tensor2d(6,7);
99  tensor2d.reshape(dim) = tensor;
100 
101  float scratch[2*3*1*7*1];
102  TensorMap<Tensor<float, 5>> tensor5d(scratch, 2,3,1,7,1);
103  tensor5d.reshape(dim).device(Eigen::DefaultDevice()) = tensor;
104 
105  for (int i = 0; i < 2; ++i) {
106  for (int j = 0; j < 3; ++j) {
107  for (int k = 0; k < 7; ++k) {
108  VERIFY_IS_EQUAL(tensor2d(i+2*j,k), tensor(i,j,k));
109  VERIFY_IS_EQUAL(tensor5d(i,j,0,k,0), tensor(i,j,k));
110  }
111  }
112  }
113 }
114 
115 template<typename T, int DataLayout>
116 static void test_simple_slice()
117 {
118  Tensor<T, 5, DataLayout> tensor(2,3,5,7,11);
119  tensor.setRandom();
120 
121  Tensor<T, 5, DataLayout> slice1(1,1,1,1,1);
124  slice1 = tensor.slice(indices, sizes);
125  VERIFY_IS_EQUAL(slice1(0,0,0,0,0), tensor(1,2,3,4,5));
126 
127  Tensor<T, 5, DataLayout> slice2(1,1,2,2,3);
128  Eigen::DSizes<ptrdiff_t, 5> indices2(1,1,3,4,5);
129  Eigen::DSizes<ptrdiff_t, 5> sizes2(1,1,2,2,3);
130  slice2 = tensor.slice(indices2, sizes2);
131  for (int i = 0; i < 2; ++i) {
132  for (int j = 0; j < 2; ++j) {
133  for (int k = 0; k < 3; ++k) {
134  VERIFY_IS_EQUAL(slice2(0,0,i,j,k), tensor(1,1,3+i,4+j,5+k));
135  }
136  }
137  }
138 }
139 
140 template<typename T>
141 static void test_const_slice()
142 {
143  const T b[1] = {42};
146  offsets[0] = 0;
147  TensorRef<Tensor<const T, 1> > slice_ref(m.slice(offsets, m.dimensions()));
148  VERIFY_IS_EQUAL(slice_ref(0), 42);
149 }
150 
151 template<typename T, int DataLayout>
152 static void test_slice_in_expr() {
154  Mtx m1(7,7);
155  Mtx m2(3,3);
156  m1.setRandom();
157  m2.setRandom();
158 
159  Mtx m3 = m1.block(1, 2, 3, 3) * m2.block(0, 2, 3, 1);
160 
161  TensorMap<Tensor<T, 2, DataLayout>> tensor1(m1.data(), 7, 7);
162  TensorMap<Tensor<T, 2, DataLayout>> tensor2(m2.data(), 3, 3);
163  Tensor<T, 2, DataLayout> tensor3(3,1);
164  typedef typename Tensor<T, 1>::DimensionPair DimPair;
165  array<DimPair, 1> contract_along{{DimPair(1, 0)}};
166 
167  Eigen::DSizes<ptrdiff_t, 2> indices1(1,2);
168  Eigen::DSizes<ptrdiff_t, 2> sizes1(3,3);
169  Eigen::DSizes<ptrdiff_t, 2> indices2(0,2);
170  Eigen::DSizes<ptrdiff_t, 2> sizes2(3,1);
171  tensor3 = tensor1.slice(indices1, sizes1).contract(tensor2.slice(indices2, sizes2), contract_along);
172 
173  Map<Mtx> res(tensor3.data(), 3, 1);
174  for (int i = 0; i < 3; ++i) {
175  for (int j = 0; j < 1; ++j) {
176  VERIFY_IS_APPROX(res(i,j), m3(i,j));
177  }
178  }
179 
180  // Take an arbitrary slice of an arbitrarily sized tensor.
181  TensorMap<Tensor<const T, 2, DataLayout>> tensor4(m1.data(), 7, 7);
182  Tensor<T, 1, DataLayout> tensor6 = tensor4.reshape(DSizes<ptrdiff_t, 1>(7*7)).exp().slice(DSizes<ptrdiff_t, 1>(0), DSizes<ptrdiff_t, 1>(35));
183  for (int i = 0; i < 35; ++i) {
184  VERIFY_IS_APPROX(tensor6(i), expf(tensor4.data()[i]));
185  }
186 }
187 
188 template<typename T, int DataLayout>
189 static void test_slice_as_lvalue()
190 {
191  Tensor<T, 3, DataLayout> tensor1(2,2,7);
192  tensor1.setRandom();
193  Tensor<T, 3, DataLayout> tensor2(2,2,7);
194  tensor2.setRandom();
195  Tensor<T, 3, DataLayout> tensor3(4,3,5);
196  tensor3.setRandom();
197  Tensor<T, 3, DataLayout> tensor4(4,3,2);
198  tensor4.setRandom();
199  Tensor<T, 3, DataLayout> tensor5(10,13,12);
200  tensor5.setRandom();
201 
203  Eigen::DSizes<ptrdiff_t, 3> sizes12(2,2,7);
204  Eigen::DSizes<ptrdiff_t, 3> first_slice(0,0,0);
205  result.slice(first_slice, sizes12) = tensor1;
206  Eigen::DSizes<ptrdiff_t, 3> second_slice(2,0,0);
207  result.slice(second_slice, sizes12).device(Eigen::DefaultDevice()) = tensor2;
208 
209  Eigen::DSizes<ptrdiff_t, 3> sizes3(4,3,5);
210  Eigen::DSizes<ptrdiff_t, 3> third_slice(0,2,0);
211  result.slice(third_slice, sizes3) = tensor3;
212 
213  Eigen::DSizes<ptrdiff_t, 3> sizes4(4,3,2);
214  Eigen::DSizes<ptrdiff_t, 3> fourth_slice(0,2,5);
215  result.slice(fourth_slice, sizes4) = tensor4;
216 
217  for (int j = 0; j < 2; ++j) {
218  for (int k = 0; k < 7; ++k) {
219  for (int i = 0; i < 2; ++i) {
220  VERIFY_IS_EQUAL(result(i,j,k), tensor1(i,j,k));
221  VERIFY_IS_EQUAL(result(i+2,j,k), tensor2(i,j,k));
222  }
223  }
224  }
225  for (int i = 0; i < 4; ++i) {
226  for (int j = 2; j < 5; ++j) {
227  for (int k = 0; k < 5; ++k) {
228  VERIFY_IS_EQUAL(result(i,j,k), tensor3(i,j-2,k));
229  }
230  for (int k = 5; k < 7; ++k) {
231  VERIFY_IS_EQUAL(result(i,j,k), tensor4(i,j-2,k-5));
232  }
233  }
234  }
235 
236  Eigen::DSizes<ptrdiff_t, 3> sizes5(4,5,7);
237  Eigen::DSizes<ptrdiff_t, 3> fifth_slice(0,0,0);
238  result.slice(fifth_slice, sizes5) = tensor5.slice(fifth_slice, sizes5);
239  for (int i = 0; i < 4; ++i) {
240  for (int j = 2; j < 5; ++j) {
241  for (int k = 0; k < 7; ++k) {
242  VERIFY_IS_EQUAL(result(i,j,k), tensor5(i,j,k));
243  }
244  }
245  }
246 }
247 
248 template<typename T, int DataLayout>
249 static void test_slice_raw_data()
250 {
251  Tensor<T, 4, DataLayout> tensor(3,5,7,11);
252  tensor.setRandom();
253 
255  Eigen::DSizes<ptrdiff_t, 4> extents(1,1,1,1);
256  typedef TensorEvaluator<decltype(tensor.slice(offsets, extents)), DefaultDevice> SliceEvaluator;
257  auto slice1 = SliceEvaluator(tensor.slice(offsets, extents), DefaultDevice());
258  VERIFY_IS_EQUAL(slice1.dimensions().TotalSize(), 1);
259  VERIFY_IS_EQUAL(slice1.data()[0], tensor(1,2,3,4));
260 
261  if (DataLayout == ColMajor) {
262  extents = Eigen::DSizes<ptrdiff_t, 4>(2,1,1,1);
263  auto slice2 = SliceEvaluator(tensor.slice(offsets, extents), DefaultDevice());
264  VERIFY_IS_EQUAL(slice2.dimensions().TotalSize(), 2);
265  VERIFY_IS_EQUAL(slice2.data()[0], tensor(1,2,3,4));
266  VERIFY_IS_EQUAL(slice2.data()[1], tensor(2,2,3,4));
267  } else {
268  extents = Eigen::DSizes<ptrdiff_t, 4>(1,1,1,2);
269  auto slice2 = SliceEvaluator(tensor.slice(offsets, extents), DefaultDevice());
270  VERIFY_IS_EQUAL(slice2.dimensions().TotalSize(), 2);
271  VERIFY_IS_EQUAL(slice2.data()[0], tensor(1,2,3,4));
272  VERIFY_IS_EQUAL(slice2.data()[1], tensor(1,2,3,5));
273  }
274 
275  extents = Eigen::DSizes<ptrdiff_t, 4>(1,2,1,1);
276  auto slice3 = SliceEvaluator(tensor.slice(offsets, extents), DefaultDevice());
277  VERIFY_IS_EQUAL(slice3.dimensions().TotalSize(), 2);
278  VERIFY_IS_EQUAL(slice3.data(), static_cast<T*>(0));
279 
280  if (DataLayout == ColMajor) {
282  extents = Eigen::DSizes<ptrdiff_t, 4>(3,2,1,1);
283  auto slice4 = SliceEvaluator(tensor.slice(offsets, extents), DefaultDevice());
284  VERIFY_IS_EQUAL(slice4.dimensions().TotalSize(), 6);
285  for (int i = 0; i < 3; ++i) {
286  for (int j = 0; j < 2; ++j) {
287  VERIFY_IS_EQUAL(slice4.data()[i+3*j], tensor(i,2+j,3,4));
288  }
289  }
290  } else {
292  extents = Eigen::DSizes<ptrdiff_t, 4>(1,1,2,11);
293  auto slice4 = SliceEvaluator(tensor.slice(offsets, extents), DefaultDevice());
294  VERIFY_IS_EQUAL(slice4.dimensions().TotalSize(), 22);
295  for (int l = 0; l < 11; ++l) {
296  for (int k = 0; k < 2; ++k) {
297  VERIFY_IS_EQUAL(slice4.data()[l+11*k], tensor(1,2,3+k,l));
298  }
299  }
300  }
301 
302  if (DataLayout == ColMajor) {
304  extents = Eigen::DSizes<ptrdiff_t, 4>(3,5,7,2);
305  auto slice5 = SliceEvaluator(tensor.slice(offsets, extents), DefaultDevice());
306  VERIFY_IS_EQUAL(slice5.dimensions().TotalSize(), 210);
307  for (int i = 0; i < 3; ++i) {
308  for (int j = 0; j < 5; ++j) {
309  for (int k = 0; k < 7; ++k) {
310  for (int l = 0; l < 2; ++l) {
311  int slice_index = i + 3 * (j + 5 * (k + 7 * l));
312  VERIFY_IS_EQUAL(slice5.data()[slice_index], tensor(i,j,k,l+4));
313  }
314  }
315  }
316  }
317  } else {
319  extents = Eigen::DSizes<ptrdiff_t, 4>(2,5,7,11);
320  auto slice5 = SliceEvaluator(tensor.slice(offsets, extents), DefaultDevice());
321  VERIFY_IS_EQUAL(slice5.dimensions().TotalSize(), 770);
322  for (int l = 0; l < 11; ++l) {
323  for (int k = 0; k < 7; ++k) {
324  for (int j = 0; j < 5; ++j) {
325  for (int i = 0; i < 2; ++i) {
326  int slice_index = l + 11 * (k + 7 * (j + 5 * i));
327  VERIFY_IS_EQUAL(slice5.data()[slice_index], tensor(i+1,j,k,l));
328  }
329  }
330  }
331  }
332 
333  }
334 
336  extents = Eigen::DSizes<ptrdiff_t, 4>(3,5,7,11);
337  auto slice6 = SliceEvaluator(tensor.slice(offsets, extents), DefaultDevice());
338  VERIFY_IS_EQUAL(slice6.dimensions().TotalSize(), 3*5*7*11);
339  VERIFY_IS_EQUAL(slice6.data(), tensor.data());
340 }
341 
342 
343 template<typename T, int DataLayout>
344 static void test_strided_slice()
345 {
346  typedef Tensor<T, 5, DataLayout> Tensor5f;
348  typedef Tensor<T, 2, DataLayout> Tensor2f;
350  Tensor<T, 5, DataLayout> tensor(2,3,5,7,11);
351  Tensor<T, 2, DataLayout> tensor2(7,11);
352  tensor.setRandom();
353  tensor2.setRandom();
354 
355  if (true) {
356  Tensor2f slice(2,3);
357  Index2 strides(-2,-1);
358  Index2 indicesStart(5,7);
359  Index2 indicesStop(0,4);
360  slice = tensor2.stridedSlice(indicesStart, indicesStop, strides);
361  for (int j = 0; j < 2; ++j) {
362  for (int k = 0; k < 3; ++k) {
363  VERIFY_IS_EQUAL(slice(j,k), tensor2(5-2*j,7-k));
364  }
365  }
366  }
367 
368  if(true) {
369  Tensor2f slice(0,1);
370  Index2 strides(1,1);
371  Index2 indicesStart(5,4);
372  Index2 indicesStop(5,5);
373  slice = tensor2.stridedSlice(indicesStart, indicesStop, strides);
374  }
375 
376  if(true) { // test clamped degenerate interavls
377  Tensor2f slice(7,11);
378  Index2 strides(1,-1);
379  Index2 indicesStart(-3,20); // should become 0,10
380  Index2 indicesStop(20,-11); // should become 11, -1
381  slice = tensor2.stridedSlice(indicesStart, indicesStop, strides);
382  for (int j = 0; j < 7; ++j) {
383  for (int k = 0; k < 11; ++k) {
384  VERIFY_IS_EQUAL(slice(j,k), tensor2(j,10-k));
385  }
386  }
387  }
388 
389  if(true) {
390  Tensor5f slice1(1,1,1,1,1);
391  Eigen::DSizes<Eigen::DenseIndex, 5> indicesStart(1, 2, 3, 4, 5);
392  Eigen::DSizes<Eigen::DenseIndex, 5> indicesStop(2, 3, 4, 5, 6);
394  slice1 = tensor.stridedSlice(indicesStart, indicesStop, strides);
395  VERIFY_IS_EQUAL(slice1(0,0,0,0,0), tensor(1,2,3,4,5));
396  }
397 
398  if(true) {
399  Tensor5f slice(1,1,2,2,3);
400  Index5 start(1, 1, 3, 4, 5);
401  Index5 stop(2, 2, 5, 6, 8);
402  Index5 strides(1, 1, 1, 1, 1);
403  slice = tensor.stridedSlice(start, stop, strides);
404  for (int i = 0; i < 2; ++i) {
405  for (int j = 0; j < 2; ++j) {
406  for (int k = 0; k < 3; ++k) {
407  VERIFY_IS_EQUAL(slice(0,0,i,j,k), tensor(1,1,3+i,4+j,5+k));
408  }
409  }
410  }
411  }
412 
413  if(true) {
414  Tensor5f slice(1,1,2,2,3);
415  Index5 strides3(1, 1, -2, 1, -1);
416  Index5 indices3Start(1, 1, 4, 4, 7);
417  Index5 indices3Stop(2, 2, 0, 6, 4);
418  slice = tensor.stridedSlice(indices3Start, indices3Stop, strides3);
419  for (int i = 0; i < 2; ++i) {
420  for (int j = 0; j < 2; ++j) {
421  for (int k = 0; k < 3; ++k) {
422  VERIFY_IS_EQUAL(slice(0,0,i,j,k), tensor(1,1,4-2*i,4+j,7-k));
423  }
424  }
425  }
426  }
427 
428  if(false) { // tests degenerate interval
429  Tensor5f slice(1,1,2,2,3);
430  Index5 strides3(1, 1, 2, 1, 1);
431  Index5 indices3Start(1, 1, 4, 4, 7);
432  Index5 indices3Stop(2, 2, 0, 6, 4);
433  slice = tensor.stridedSlice(indices3Start, indices3Stop, strides3);
434  }
435 }
436 
437 template<typename T, int DataLayout>
439 {
440  typedef Tensor<T, 2, DataLayout> Tensor2f;
442 
443  Tensor<T, 2, DataLayout> tensor(7,11),tensor2(7,11);
444  tensor.setRandom();
445  tensor2=tensor;
446  Tensor2f slice(2,3);
447 
448  slice.setRandom();
449 
450  Index2 strides(1,1);
451  Index2 indicesStart(3,4);
452  Index2 indicesStop(5,7);
453  Index2 lengths(2,3);
454 
455  tensor.slice(indicesStart,lengths)=slice;
456  tensor2.stridedSlice(indicesStart,indicesStop,strides)=slice;
457 
458  for(int i=0;i<7;i++) for(int j=0;j<11;j++){
459  VERIFY_IS_EQUAL(tensor(i,j), tensor2(i,j));
460  }
461 }
462 
463 template<typename T, int DataLayout>
464 static void test_composition()
465 {
467  matrix.setRandom();
468 
469  const DSizes<ptrdiff_t, 3> newDims(1, 1, 11);
471  matrix.slice(DSizes<ptrdiff_t, 2>(2, 0), DSizes<ptrdiff_t, 2>(1, 11)).reshape(newDims);
472 
473  VERIFY_IS_EQUAL(tensor.dimensions().TotalSize(), 11);
474  VERIFY_IS_EQUAL(tensor.dimension(0), 1);
475  VERIFY_IS_EQUAL(tensor.dimension(1), 1);
476  VERIFY_IS_EQUAL(tensor.dimension(2), 11);
477  for (int i = 0; i < 11; ++i) {
478  VERIFY_IS_EQUAL(tensor(0,0,i), matrix(2,i));
479  }
480 }
481 
482 template<typename T, int DataLayout>
483 static void test_empty_slice()
484 {
485  Tensor<T, 3, DataLayout> tensor(2,3,5);
486  tensor.setRandom();
488 
489  // empty size in first dimension
490  Eigen::DSizes<ptrdiff_t, 3> indices1(1,2,3);
491  Eigen::DSizes<ptrdiff_t, 3> sizes1(0,1,2);
492  Tensor<T, 3, DataLayout> slice1(0,1,2);
493  slice1.setRandom();
494  tensor.slice(indices1, sizes1) = slice1;
495 
496  // empty size in second dimension
497  Eigen::DSizes<ptrdiff_t, 3> indices2(1,2,3);
498  Eigen::DSizes<ptrdiff_t, 3> sizes2(1,0,2);
499  Tensor<T, 3, DataLayout> slice2(1,0,2);
500  slice2.setRandom();
501  tensor.slice(indices2, sizes2) = slice2;
502 
503  // empty size in third dimension
504  Eigen::DSizes<ptrdiff_t, 3> indices3(1,2,3);
505  Eigen::DSizes<ptrdiff_t, 3> sizes3(1,1,0);
506  Tensor<T, 3, DataLayout> slice3(1,1,0);
507  slice3.setRandom();
508  tensor.slice(indices3, sizes3) = slice3;
509 
510  // empty size in first and second dimension
511  Eigen::DSizes<ptrdiff_t, 3> indices4(1,2,3);
512  Eigen::DSizes<ptrdiff_t, 3> sizes4(0,0,2);
513  Tensor<T, 3, DataLayout> slice4(0,0,2);
514  slice4.setRandom();
515  tensor.slice(indices4, sizes4) = slice4;
516 
517  // empty size in second and third dimension
518  Eigen::DSizes<ptrdiff_t, 3> indices5(1,2,3);
519  Eigen::DSizes<ptrdiff_t, 3> sizes5(1,0,0);
520  Tensor<T, 3, DataLayout> slice5(1,0,0);
521  slice5.setRandom();
522  tensor.slice(indices5, sizes5) = slice5;
523 
524  // empty size in all dimensions
525  Eigen::DSizes<ptrdiff_t, 3> indices6(1,2,3);
526  Eigen::DSizes<ptrdiff_t, 3> sizes6(0,0,0);
527  Tensor<T, 3, DataLayout> slice6(0,0,0);
528  slice6.setRandom();
529  tensor.slice(indices6, sizes6) = slice6;
530 
531  // none of these operations should change the tensor's components
532  // because all of the rvalue slices have at least one zero dimension
533  for (int i = 0; i < 2; ++i) {
534  for (int j = 0; j < 3; ++j) {
535  for (int k = 0; k < 5; ++k) {
536  VERIFY_IS_EQUAL(tensor(i,j,k), copy(i,j,k));
537  }
538  }
539  }
540 }
541 
542 #define CALL_SUBTEST_PART(PART) \
543  CALL_SUBTEST_##PART
544 
545 #define CALL_SUBTESTS_TYPES_LAYOUTS(PART, NAME) \
546  CALL_SUBTEST_PART(PART)((NAME<float, ColMajor>())); \
547  CALL_SUBTEST_PART(PART)((NAME<float, RowMajor>())); \
548  CALL_SUBTEST_PART(PART)((NAME<bool, ColMajor>())); \
549  CALL_SUBTEST_PART(PART)((NAME<bool, RowMajor>()))
550 
551 EIGEN_DECLARE_TEST(cxx11_tensor_morphing)
552 {
553  CALL_SUBTEST_1(test_simple_reshape<void>());
554  CALL_SUBTEST_1(test_static_reshape<void>());
555  CALL_SUBTEST_1(test_reshape_as_lvalue<void>());
556  CALL_SUBTEST_1(test_reshape_in_expr<void>());
557  CALL_SUBTEST_1(test_const_slice<float>());
558 
565 }
Eigen::Tensor::dimension
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index dimension(std::size_t n) const
Definition: Tensor.h:101
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Definition: Tensor.h:63
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Definition: cxx11_tensor_morphing.cpp:551
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A reference to a tensor expression The expression will be evaluated lazily (as much as possible).
Definition: TensorForwardDeclarations.h:55
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Definition: TensorBlock.h:26
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Definition: cxx11_tensor_morphing.cpp:483
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Definition: EmulateArray.h:21
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE TensorReshapingOp< const NewDimensions, const Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > reshape(const NewDimensions &newDimensions) const
Definition: TensorBase.h:1055
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Definition: cxx11_tensor_morphing.cpp:92
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Definition: IOFormat.cpp:2
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Definition: level1_impl.h:29
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Definition: cxx11_tensor_morphing.cpp:545
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Definition: cxx11_tensor_morphing.cpp:464
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Definition: TensorDeviceDefault.h:17
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Definition: TensorMap.h:137
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Definition: Map.h:94
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set noclip points set clip one set noclip two set bar set border lt lw set xdata set ydata set zdata set x2data set y2data set boxwidth set dummy y set format x g set format y g set format x2 g set format y2 g set format z g set angles radians set nogrid set key title set key left top Right noreverse box linetype linewidth samplen spacing width set nolabel set noarrow set nologscale set logscale x set offsets
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Definition: Tensor.h:104
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Definition: TensorEvaluator.h:28
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Definition: 3rdparty/Eigen/Eigen/src/Core/Matrix.h:178
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Definition: cxx11_tensor_morphing.cpp:45
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE TensorSlicingOp< const StartIndices, const Sizes, const Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > slice(const StartIndices &startIndices, const Sizes &sizes) const
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