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Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +01001/*
Michalis Spyroud466c2d2018-01-30 10:54:39 +00002 * Copyright (c) 2017-2018 ARM Limited.
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +01003 *
4 * SPDX-License-Identifier: MIT
5 *
6 * Permission is hereby granted, free of charge, to any person obtaining a copy
7 * of this software and associated documentation files (the "Software"), to
8 * deal in the Software without restriction, including without limitation the
9 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
10 * sell copies of the Software, and to permit persons to whom the Software is
11 * furnished to do so, subject to the following conditions:
12 *
13 * The above copyright notice and this permission notice shall be included in all
14 * copies or substantial portions of the Software.
15 *
16 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
17 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
18 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
19 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
20 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
21 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
22 * SOFTWARE.
23 */
24#ifndef __ARM_COMPUTE_TEST_SHAPE_DATASETS_H__
25#define __ARM_COMPUTE_TEST_SHAPE_DATASETS_H__
26
27#include "arm_compute/core/TensorShape.h"
Moritz Pflanzera09de0c2017-09-01 20:41:12 +010028#include "tests/framework/datasets/Datasets.h"
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +010029
30#include <type_traits>
31
32namespace arm_compute
33{
34namespace test
35{
36namespace datasets
37{
Gian Marco5420b282017-11-29 10:41:38 +000038/** Parent type for all for shape datasets. */
39using ShapeDataset = framework::dataset::ContainerDataset<std::vector<TensorShape>>;
40
41/** Data set containing small 1D tensor shapes. */
42class Small1DShapes final : public ShapeDataset
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +010043{
44public:
Gian Marco5420b282017-11-29 10:41:38 +000045 Small1DShapes()
46 : ShapeDataset("Shape",
47 {
48 TensorShape{ 256U }
49 })
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +010050 {
51 }
52};
53
Anthony Barbier1c0d0ff2018-01-31 13:05:09 +000054/** Data set containing tiny 2D tensor shapes. */
55class Tiny2DShapes final : public ShapeDataset
56{
57public:
58 Tiny2DShapes()
59 : ShapeDataset("Shape",
60 {
61 TensorShape{ 7U, 7U },
62 TensorShape{ 11U, 13U },
63 })
64 {
65 }
66};
Moritz Pflanzerb3d25792017-07-26 11:49:37 +010067/** Data set containing small 2D tensor shapes. */
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +010068class Small2DShapes final : public ShapeDataset
69{
70public:
71 Small2DShapes()
72 : ShapeDataset("Shape",
73 {
Moritz Pflanzer3ce3ff42017-07-21 17:41:02 +010074 TensorShape{ 7U, 7U },
75 TensorShape{ 27U, 13U },
76 TensorShape{ 128U, 64U }
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +010077 })
78 {
79 }
80};
81
Anthony Barbier1c0d0ff2018-01-31 13:05:09 +000082/** Data set containing tiny 3D tensor shapes. */
83class Tiny3DShapes final : public ShapeDataset
84{
85public:
86 Tiny3DShapes()
87 : ShapeDataset("Shape",
88 {
89 TensorShape{ 7U, 7U, 5U },
90 TensorShape{ 23U, 13U, 9U },
91 })
92 {
93 }
94};
95
Gian Marco Iodice06b184a2017-08-29 16:05:25 +010096/** Data set containing small 3D tensor shapes. */
97class Small3DShapes final : public ShapeDataset
98{
99public:
100 Small3DShapes()
101 : ShapeDataset("Shape",
102 {
Georgios Pinitas02ee4292018-02-15 17:22:36 +0000103 TensorShape{ 1U, 7U, 7U },
104 TensorShape{ 7U, 7U, 5U },
Gian Marco Iodice06b184a2017-08-29 16:05:25 +0100105 TensorShape{ 27U, 13U, 37U },
106 TensorShape{ 128U, 64U, 21U }
107 })
108 {
109 }
110};
111
Anthony Barbier1c0d0ff2018-01-31 13:05:09 +0000112/** Data set containing tiny 4D tensor shapes. */
113class Tiny4DShapes final : public ShapeDataset
114{
115public:
116 Tiny4DShapes()
117 : ShapeDataset("Shape",
118 {
119 TensorShape{ 7U, 7U, 5U, 3U },
120 TensorShape{ 17U, 13U, 7U, 2U },
121 })
122 {
123 }
124};
Gian Marco Iodice06b184a2017-08-29 16:05:25 +0100125/** Data set containing small 4D tensor shapes. */
126class Small4DShapes final : public ShapeDataset
127{
128public:
129 Small4DShapes()
130 : ShapeDataset("Shape",
131 {
Georgios Pinitas02ee4292018-02-15 17:22:36 +0000132 TensorShape{ 1U, 7U, 1U, 3U },
133 TensorShape{ 7U, 7U, 5U, 3U },
Gian Marco Iodice06b184a2017-08-29 16:05:25 +0100134 TensorShape{ 27U, 13U, 37U, 2U },
135 TensorShape{ 128U, 64U, 21U, 3U }
136 })
137 {
138 }
139};
140
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +0100141/** Data set containing small tensor shapes. */
Anthony Barbier1c0d0ff2018-01-31 13:05:09 +0000142class TinyShapes final : public ShapeDataset
143{
144public:
145 TinyShapes()
146 : ShapeDataset("Shape",
147 {
148 // Batch size 1
149 TensorShape{ 9U, 9U },
150 TensorShape{ 27U, 13U, 2U },
151 })
152 {
153 }
154};
155/** Data set containing small tensor shapes. */
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +0100156class SmallShapes final : public ShapeDataset
157{
158public:
159 SmallShapes()
160 : ShapeDataset("Shape",
161 {
SiCong Licaf8c5e2017-08-21 13:12:52 +0100162 // Batch size 1
Gian Marco Iodicebf179552017-09-05 13:51:21 +0100163 TensorShape{ 9U, 9U },
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +0100164 TensorShape{ 27U, 13U, 2U },
SiCong Licaf8c5e2017-08-21 13:12:52 +0100165 TensorShape{ 128U, 64U, 1U, 3U },
166 // Batch size 4
Gian Marco Iodicebf179552017-09-05 13:51:21 +0100167 TensorShape{ 9U, 9U, 3U, 4U },
SiCong Licaf8c5e2017-08-21 13:12:52 +0100168 TensorShape{ 27U, 13U, 2U, 4U },
SiCong Licaf8c5e2017-08-21 13:12:52 +0100169 // Arbitrary batch size
Gian Marco Iodicebf179552017-09-05 13:51:21 +0100170 TensorShape{ 9U, 9U, 3U, 5U }
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +0100171 })
172 {
173 }
174};
175
Diego Lopez Recas0021d752017-12-18 14:42:56 +0000176/** Data set containing pairs of small tensor shapes that are broadcast compatible. */
177class SmallShapesBroadcast final : public framework::dataset::ZipDataset<ShapeDataset, ShapeDataset>
178{
179public:
180 SmallShapesBroadcast()
181 : ZipDataset<ShapeDataset, ShapeDataset>(
182 ShapeDataset("Shape0",
183 {
184 TensorShape{ 9U, 9U },
185 TensorShape{ 27U, 13U, 2U },
186 TensorShape{ 128U, 1U, 5U, 3U },
187 TensorShape{ 9U, 9U, 3U, 4U },
188 TensorShape{ 27U, 13U, 2U, 4U },
189 TensorShape{ 1U, 1U, 1U, 5U }
190 }),
191 ShapeDataset("Shape1",
192 {
193 TensorShape{ 9U, 1U, 2U },
194 TensorShape{ 1U, 13U, 2U },
195 TensorShape{ 128U, 64U, 1U, 3U },
196 TensorShape{ 9U, 1U, 3U },
197 TensorShape{ 1U },
198 TensorShape{ 9U, 9U, 3U, 5U }
199 }))
200 {
201 }
202};
203
steniu01f81652d2017-09-11 15:29:12 +0100204/** Data set containing medium tensor shapes. */
205class MediumShapes final : public ShapeDataset
206{
207public:
208 MediumShapes()
209 : ShapeDataset("Shape",
210 {
211 // Batch size 1
212 TensorShape{ 37U, 37U },
213 TensorShape{ 27U, 33U, 2U },
214 TensorShape{ 128U, 64U, 1U, 3U },
215 // Batch size 4
216 TensorShape{ 37U, 37U, 3U, 4U },
217 TensorShape{ 27U, 33U, 2U, 4U },
218 // Arbitrary batch size
219 TensorShape{ 37U, 37U, 3U, 5U }
220 })
221 {
222 }
223};
224
Gian Marco37908d92017-11-07 14:38:22 +0000225/** Data set containing medium 2D tensor shapes. */
226class Medium2DShapes final : public ShapeDataset
227{
228public:
229 Medium2DShapes()
230 : ShapeDataset("Shape",
231 {
232 TensorShape{ 42U, 37U },
233 TensorShape{ 57U, 60U },
234 TensorShape{ 128U, 64U },
Gian Marco Iodice2abb2162018-04-11 10:49:04 +0100235 TensorShape{ 83U, 72U },
236 TensorShape{ 40U, 40U }
Gian Marco37908d92017-11-07 14:38:22 +0000237 })
238 {
239 }
240};
241
Gian Marco Iodice7e4b2392018-02-22 16:17:20 +0000242/** Data set containing medium 3D tensor shapes. */
243class Medium3DShapes final : public ShapeDataset
244{
245public:
246 Medium3DShapes()
247 : ShapeDataset("Shape",
248 {
249 TensorShape{ 42U, 37U, 8U },
250 TensorShape{ 57U, 60U, 13U },
251 TensorShape{ 128U, 64U, 21U },
252 TensorShape{ 83U, 72U, 14U }
253 })
254 {
255 }
256};
257
258/** Data set containing medium 4D tensor shapes. */
259class Medium4DShapes final : public ShapeDataset
260{
261public:
262 Medium4DShapes()
263 : ShapeDataset("Shape",
264 {
265 TensorShape{ 42U, 37U, 8U, 15U },
266 TensorShape{ 57U, 60U, 13U, 8U },
267 TensorShape{ 128U, 64U, 21U, 13U },
268 TensorShape{ 83U, 72U, 14U, 5U }
269 })
270 {
271 }
272};
273
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +0100274/** Data set containing large tensor shapes. */
275class LargeShapes final : public ShapeDataset
276{
277public:
278 LargeShapes()
279 : ShapeDataset("Shape",
280 {
SiCong Licaf8c5e2017-08-21 13:12:52 +0100281 // Batch size 1
Gian Marco7f0f7902017-12-07 09:26:56 +0000282 TensorShape{ 1921U, 1083U },
283 TensorShape{ 641U, 485U, 2U, 3U },
SiCong Licaf8c5e2017-08-21 13:12:52 +0100284 // Batch size 4
Gian Marco7f0f7902017-12-07 09:26:56 +0000285 TensorShape{ 799U, 595U, 1U, 4U },
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +0100286 })
287 {
288 }
289};
290
Diego Lopez Recas0021d752017-12-18 14:42:56 +0000291/** Data set containing pairs of large tensor shapes that are broadcast compatible. */
292class LargeShapesBroadcast final : public framework::dataset::ZipDataset<ShapeDataset, ShapeDataset>
293{
294public:
295 LargeShapesBroadcast()
296 : ZipDataset<ShapeDataset, ShapeDataset>(
297 ShapeDataset("Shape0",
298 {
299 TensorShape{ 1921U, 541U },
300 TensorShape{ 1U, 485U, 2U, 3U },
301 TensorShape{ 4159U, 1U },
302 TensorShape{ 799U }
303 }),
304 ShapeDataset("Shape1",
305 {
306 TensorShape{ 1921U, 1U, 2U },
307 TensorShape{ 641U, 1U, 2U, 3U },
308 TensorShape{ 1U, 127U, 25U },
309 TensorShape{ 799U, 595U, 1U, 4U }
310 }))
311 {
312 }
313};
314
Gian Marco5420b282017-11-29 10:41:38 +0000315/** Data set containing large 1D tensor shapes. */
316class Large1DShapes final : public ShapeDataset
317{
318public:
319 Large1DShapes()
320 : ShapeDataset("Shape",
321 {
322 TensorShape{ 1921U },
323 TensorShape{ 1245U },
324 TensorShape{ 4160U }
325 })
326 {
327 }
328};
329
Moritz Pflanzerb3d25792017-07-26 11:49:37 +0100330/** Data set containing large 2D tensor shapes. */
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +0100331class Large2DShapes final : public ShapeDataset
332{
333public:
334 Large2DShapes()
335 : ShapeDataset("Shape",
336 {
337 TensorShape{ 1920U, 1080U },
Moritz Pflanzer3ce3ff42017-07-21 17:41:02 +0100338 TensorShape{ 1245U, 652U },
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +0100339 TensorShape{ 4160U, 3120U }
340 })
341 {
342 }
343};
Moritz Pflanzerb3d25792017-07-26 11:49:37 +0100344
Gian Marco Iodice06b184a2017-08-29 16:05:25 +0100345/** Data set containing large 3D tensor shapes. */
346class Large3DShapes final : public ShapeDataset
347{
348public:
349 Large3DShapes()
350 : ShapeDataset("Shape",
351 {
352 TensorShape{ 320U, 240U, 3U },
353 TensorShape{ 383U, 653U, 2U },
354 TensorShape{ 721U, 123U, 13U }
355 })
356 {
357 }
358};
359
360/** Data set containing large 4D tensor shapes. */
361class Large4DShapes final : public ShapeDataset
362{
363public:
364 Large4DShapes()
365 : ShapeDataset("Shape",
366 {
367 TensorShape{ 320U, 123U, 3U, 3U },
368 TensorShape{ 383U, 413U, 2U, 3U },
369 TensorShape{ 517U, 123U, 13U, 2U }
370 })
371 {
372 }
373};
374
Gian Marco Iodice247f52c2018-03-22 11:24:56 +0000375/** Data set containing small 3x3 tensor shapes. */
376class Small3x3Shapes final : public ShapeDataset
377{
378public:
379 Small3x3Shapes()
380 : ShapeDataset("Shape",
381 {
382 TensorShape{ 3U, 3U, 7U, 4U },
383 TensorShape{ 3U, 3U, 4U, 13U },
384 TensorShape{ 3U, 3U, 9U, 2U },
385 TensorShape{ 3U, 3U, 3U, 5U },
386 })
387 {
388 }
389};
390
Gian Marco Iodicef1c2bf02018-06-13 14:05:54 +0100391/** Data set containing small 3x1 tensor shapes. */
392class Small3x1Shapes final : public ShapeDataset
393{
394public:
395 Small3x1Shapes()
396 : ShapeDataset("Shape",
397 {
398 TensorShape{ 3U, 1U, 7U, 4U },
399 TensorShape{ 3U, 1U, 4U, 13U },
400 TensorShape{ 3U, 1U, 9U, 2U },
401 TensorShape{ 3U, 1U, 3U, 5U },
402 })
403 {
404 }
405};
406
407/** Data set containing small 1x3 tensor shapes. */
408class Small1x3Shapes final : public ShapeDataset
409{
410public:
411 Small1x3Shapes()
412 : ShapeDataset("Shape",
413 {
414 TensorShape{ 1U, 3U, 7U, 4U },
415 TensorShape{ 1U, 3U, 4U, 13U },
416 TensorShape{ 1U, 3U, 9U, 2U },
417 TensorShape{ 1U, 3U, 3U, 5U },
418 })
419 {
420 }
421};
422
Gian Marco Iodice247f52c2018-03-22 11:24:56 +0000423/** Data set containing large 3x3 tensor shapes. */
424class Large3x3Shapes final : public ShapeDataset
425{
426public:
427 Large3x3Shapes()
428 : ShapeDataset("Shape",
429 {
430 TensorShape{ 3U, 3U, 32U, 64U },
431 TensorShape{ 3U, 3U, 51U, 13U },
432 TensorShape{ 3U, 3U, 53U, 47U },
433 TensorShape{ 3U, 3U, 128U, 384U },
434 })
435 {
436 }
437};
438
Gian Marco Iodicef1c2bf02018-06-13 14:05:54 +0100439/** Data set containing large 3x1 tensor shapes. */
440class Large3x1Shapes final : public ShapeDataset
441{
442public:
443 Large3x1Shapes()
444 : ShapeDataset("Shape",
445 {
446 TensorShape{ 3U, 1U, 32U, 64U },
447 TensorShape{ 3U, 1U, 51U, 13U },
448 TensorShape{ 3U, 1U, 53U, 47U },
449 TensorShape{ 3U, 1U, 128U, 384U },
450 })
451 {
452 }
453};
454
455/** Data set containing large 1x3 tensor shapes. */
456class Large1x3Shapes final : public ShapeDataset
457{
458public:
459 Large1x3Shapes()
460 : ShapeDataset("Shape",
461 {
462 TensorShape{ 1U, 3U, 32U, 64U },
463 TensorShape{ 1U, 3U, 51U, 13U },
464 TensorShape{ 1U, 3U, 53U, 47U },
465 TensorShape{ 1U, 3U, 128U, 384U },
466 })
467 {
468 }
469};
470
Giorgio Arena9373c8b2018-04-11 19:07:17 +0100471/** Data set containing small 5x5 tensor shapes. */
472class Small5x5Shapes final : public ShapeDataset
473{
474public:
475 Small5x5Shapes()
476 : ShapeDataset("Shape",
477 {
478 TensorShape{ 5U, 5U, 7U, 4U },
479 TensorShape{ 5U, 5U, 4U, 13U },
480 TensorShape{ 5U, 5U, 9U, 2U },
481 TensorShape{ 5U, 5U, 3U, 5U },
482 })
483 {
484 }
485};
486
487/** Data set containing large 5x5 tensor shapes. */
488class Large5x5Shapes final : public ShapeDataset
489{
490public:
491 Large5x5Shapes()
492 : ShapeDataset("Shape",
493 {
494 TensorShape{ 5U, 5U, 32U, 64U },
495 TensorShape{ 5U, 5U, 51U, 13U },
496 TensorShape{ 5U, 5U, 53U, 47U },
497 TensorShape{ 5U, 5U, 128U, 384U },
498 })
499 {
500 }
501};
502
Pablo Tellof5f34bb2017-08-22 13:34:13 +0100503/** Data set containing small tensor shapes for deconvolution. */
504class SmallDeconvolutionShapes final : public ShapeDataset
505{
506public:
507 SmallDeconvolutionShapes()
508 : ShapeDataset("InputShape",
509 {
Georgios Pinitasced7a8d2018-02-01 16:31:33 +0000510 TensorShape{ 5U, 4U, 3U, 2U },
Pablo Tellof5f34bb2017-08-22 13:34:13 +0100511 TensorShape{ 5U, 5U, 3U },
512 TensorShape{ 11U, 13U, 4U, 3U }
513 })
514 {
515 }
516};
517
Anthony Barbier1c0d0ff2018-01-31 13:05:09 +0000518/** Data set containing tiny tensor shapes for direct convolution. */
519class TinyDirectConvolutionShapes final : public ShapeDataset
520{
521public:
522 TinyDirectConvolutionShapes()
523 : ShapeDataset("InputShape",
524 {
525 // Batch size 1
526 TensorShape{ 11U, 13U, 3U },
527 TensorShape{ 7U, 27U, 3U }
528 })
529 {
530 }
531};
Moritz Pflanzerb3d25792017-07-26 11:49:37 +0100532/** Data set containing small tensor shapes for direct convolution. */
533class SmallDirectConvolutionShapes final : public ShapeDataset
534{
535public:
536 SmallDirectConvolutionShapes()
537 : ShapeDataset("InputShape",
538 {
SiCong Licaf8c5e2017-08-21 13:12:52 +0100539 // Batch size 1
steniu01f81652d2017-09-11 15:29:12 +0100540 TensorShape{ 35U, 35U, 3U },
Moritz Pflanzerb3d25792017-07-26 11:49:37 +0100541 TensorShape{ 32U, 37U, 3U },
SiCong Licaf8c5e2017-08-21 13:12:52 +0100542 // Batch size 4
SiCong Licaf8c5e2017-08-21 13:12:52 +0100543 TensorShape{ 32U, 37U, 3U, 4U },
SiCong Licaf8c5e2017-08-21 13:12:52 +0100544 // Batch size 8
SiCong Licaf8c5e2017-08-21 13:12:52 +0100545 TensorShape{ 32U, 37U, 3U, 8U },
Michalis Spyroud466c2d2018-01-30 10:54:39 +0000546 TensorShape{ 33U, 35U, 8U, 8U }
Moritz Pflanzerb3d25792017-07-26 11:49:37 +0100547 })
548 {
549 }
550};
Gian Marco Iodiceb2833b82017-09-13 16:23:18 +0100551
Xinghang Zhou33ff9ef2018-01-17 11:23:39 +0800552/** Data set containing small tensor shapes for direct convolution. */
553class SmallDirectConvolutionTensorShiftShapes final : public ShapeDataset
554{
555public:
556 SmallDirectConvolutionTensorShiftShapes()
557 : ShapeDataset("InputShape",
558 {
559 // Batch size 1
560 TensorShape{ 35U, 35U, 3U },
561 TensorShape{ 32U, 37U, 3U },
562 // Batch size 4
563 TensorShape{ 32U, 37U, 3U, 4U },
564 // Batch size 8
565 TensorShape{ 32U, 37U, 3U, 8U },
566 TensorShape{ 33U, 35U, 3U, 8U },
567 // Arbitrary batch size
568 TensorShape{ 32U, 37U, 3U, 8U }
569 })
570 {
571 }
572};
573
Giorgio Arena04a8f8c2017-11-23 11:45:24 +0000574/** Data set containing 2D tensor shapes for DepthConcatenateLayer. */
575class DepthConcatenateLayerShapes final : public ShapeDataset
Gian Marco Iodiceb2833b82017-09-13 16:23:18 +0100576{
577public:
Giorgio Arena04a8f8c2017-11-23 11:45:24 +0000578 DepthConcatenateLayerShapes()
Gian Marco Iodiceb2833b82017-09-13 16:23:18 +0100579 : ShapeDataset("Shape",
580 {
581 TensorShape{ 322U, 243U },
582 TensorShape{ 463U, 879U },
583 TensorShape{ 416U, 651U }
584 })
585 {
586 }
587};
588
Michalis Spyrou55b3d122018-05-09 09:59:23 +0100589/** Data set containing tensor shapes for WidthConcatenateLayer. */
590class WidthConcatenateLayerShapes final : public ShapeDataset
591{
592public:
593 WidthConcatenateLayerShapes()
594 : ShapeDataset("Shape",
595 {
596 TensorShape{ 232U, 65U, 3U },
597 TensorShape{ 432U, 65U, 3U },
598 TensorShape{ 124U, 65U, 3U }
599 })
600 {
601 }
602};
603
Gian Marco Iodicebf179552017-09-05 13:51:21 +0100604/** Data set containing global pooling tensor shapes. */
605class GlobalPoolingShapes final : public ShapeDataset
606{
607public:
608 GlobalPoolingShapes()
609 : ShapeDataset("Shape",
610 {
611 // Batch size 1
612 TensorShape{ 9U, 9U },
613 TensorShape{ 13U, 13U, 2U },
614 TensorShape{ 27U, 27U, 1U, 3U },
615 // Batch size 4
616 TensorShape{ 31U, 31U, 3U, 4U },
617 TensorShape{ 34U, 34U, 2U, 4U }
618 })
619 {
620 }
621};
Anthony Barbier1c0d0ff2018-01-31 13:05:09 +0000622/** Data set containing tiny softmax layer shapes. */
623class SoftmaxLayerTinyShapes final : public ShapeDataset
624{
625public:
626 SoftmaxLayerTinyShapes()
627 : ShapeDataset("Shape",
628 {
629 TensorShape{ 9U, 9U },
Georgios Pinitas17d6d3c2018-07-02 17:52:40 +0100630 TensorShape{ 128U, 10U },
Anthony Barbier1c0d0ff2018-01-31 13:05:09 +0000631 })
632 {
633 }
634};
Gian Marco Iodicebf179552017-09-05 13:51:21 +0100635
Chunosovd6afedc2017-11-06 22:09:45 +0700636/** Data set containing small softmax layer shapes. */
637class SoftmaxLayerSmallShapes final : public ShapeDataset
638{
639public:
640 SoftmaxLayerSmallShapes()
641 : ShapeDataset("Shape",
642 {
643 TensorShape{ 9U, 9U },
Georgios Pinitas17d6d3c2018-07-02 17:52:40 +0100644 TensorShape{ 256U, 10U },
645 TensorShape{ 353U, 8U },
646 TensorShape{ 781U, 5U },
Chunosovd6afedc2017-11-06 22:09:45 +0700647 })
648 {
649 }
650};
651
652/** Data set containing large softmax layer shapes. */
653class SoftmaxLayerLargeShapes final : public ShapeDataset
654{
655public:
656 SoftmaxLayerLargeShapes()
657 : ShapeDataset("Shape",
658 {
659 TensorShape{ 1000U, 10U },
Georgios Pinitas17d6d3c2018-07-02 17:52:40 +0100660 TensorShape{ 3989U, 10U },
Chunosovd6afedc2017-11-06 22:09:45 +0700661 TensorShape{ 7339U, 11U },
662 })
663 {
664 }
665};
666
Ioan-Cristian Szabo2c350182017-12-20 16:27:37 +0000667/** Data set containing 2D tensor shapes relative to an image size. */
668class SmallImageShapes final : public ShapeDataset
669{
670public:
671 SmallImageShapes()
672 : ShapeDataset("Shape",
673 {
674 TensorShape{ 640U, 480U },
675 TensorShape{ 800U, 600U },
676 TensorShape{ 1200U, 800U }
677 })
678 {
679 }
680};
681
682/** Data set containing 2D tensor shapes relative to an image size. */
683class LargeImageShapes final : public ShapeDataset
684{
685public:
686 LargeImageShapes()
687 : ShapeDataset("Shape",
688 {
689 TensorShape{ 1920U, 1080U },
690 TensorShape{ 2560U, 1536U },
691 TensorShape{ 3584U, 2048U }
692 })
693 {
694 }
695};
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +0100696} // namespace datasets
697} // namespace test
698} // namespace arm_compute
699#endif /* __ARM_COMPUTE_TEST_SHAPE_DATASETS_H__ */