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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 },
284 TensorShape{ 4159U, 3117U },
SiCong Licaf8c5e2017-08-21 13:12:52 +0100285 // Batch size 4
Gian Marco7f0f7902017-12-07 09:26:56 +0000286 TensorShape{ 799U, 595U, 1U, 4U },
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +0100287 })
288 {
289 }
290};
291
Diego Lopez Recas0021d752017-12-18 14:42:56 +0000292/** Data set containing pairs of large tensor shapes that are broadcast compatible. */
293class LargeShapesBroadcast final : public framework::dataset::ZipDataset<ShapeDataset, ShapeDataset>
294{
295public:
296 LargeShapesBroadcast()
297 : ZipDataset<ShapeDataset, ShapeDataset>(
298 ShapeDataset("Shape0",
299 {
300 TensorShape{ 1921U, 541U },
301 TensorShape{ 1U, 485U, 2U, 3U },
302 TensorShape{ 4159U, 1U },
303 TensorShape{ 799U }
304 }),
305 ShapeDataset("Shape1",
306 {
307 TensorShape{ 1921U, 1U, 2U },
308 TensorShape{ 641U, 1U, 2U, 3U },
309 TensorShape{ 1U, 127U, 25U },
310 TensorShape{ 799U, 595U, 1U, 4U }
311 }))
312 {
313 }
314};
315
Gian Marco5420b282017-11-29 10:41:38 +0000316/** Data set containing large 1D tensor shapes. */
317class Large1DShapes final : public ShapeDataset
318{
319public:
320 Large1DShapes()
321 : ShapeDataset("Shape",
322 {
323 TensorShape{ 1921U },
324 TensorShape{ 1245U },
325 TensorShape{ 4160U }
326 })
327 {
328 }
329};
330
Moritz Pflanzerb3d25792017-07-26 11:49:37 +0100331/** Data set containing large 2D tensor shapes. */
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +0100332class Large2DShapes final : public ShapeDataset
333{
334public:
335 Large2DShapes()
336 : ShapeDataset("Shape",
337 {
338 TensorShape{ 1920U, 1080U },
Moritz Pflanzer3ce3ff42017-07-21 17:41:02 +0100339 TensorShape{ 1245U, 652U },
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +0100340 TensorShape{ 4160U, 3120U }
341 })
342 {
343 }
344};
Moritz Pflanzerb3d25792017-07-26 11:49:37 +0100345
Gian Marco Iodice06b184a2017-08-29 16:05:25 +0100346/** Data set containing large 3D tensor shapes. */
347class Large3DShapes final : public ShapeDataset
348{
349public:
350 Large3DShapes()
351 : ShapeDataset("Shape",
352 {
353 TensorShape{ 320U, 240U, 3U },
354 TensorShape{ 383U, 653U, 2U },
355 TensorShape{ 721U, 123U, 13U }
356 })
357 {
358 }
359};
360
361/** Data set containing large 4D tensor shapes. */
362class Large4DShapes final : public ShapeDataset
363{
364public:
365 Large4DShapes()
366 : ShapeDataset("Shape",
367 {
368 TensorShape{ 320U, 123U, 3U, 3U },
369 TensorShape{ 383U, 413U, 2U, 3U },
370 TensorShape{ 517U, 123U, 13U, 2U }
371 })
372 {
373 }
374};
375
Gian Marco Iodice247f52c2018-03-22 11:24:56 +0000376/** Data set containing small 3x3 tensor shapes. */
377class Small3x3Shapes final : public ShapeDataset
378{
379public:
380 Small3x3Shapes()
381 : ShapeDataset("Shape",
382 {
383 TensorShape{ 3U, 3U, 7U, 4U },
384 TensorShape{ 3U, 3U, 4U, 13U },
385 TensorShape{ 3U, 3U, 9U, 2U },
386 TensorShape{ 3U, 3U, 3U, 5U },
387 })
388 {
389 }
390};
391
392/** Data set containing large 3x3 tensor shapes. */
393class Large3x3Shapes final : public ShapeDataset
394{
395public:
396 Large3x3Shapes()
397 : ShapeDataset("Shape",
398 {
399 TensorShape{ 3U, 3U, 32U, 64U },
400 TensorShape{ 3U, 3U, 51U, 13U },
401 TensorShape{ 3U, 3U, 53U, 47U },
402 TensorShape{ 3U, 3U, 128U, 384U },
403 })
404 {
405 }
406};
407
Giorgio Arena9373c8b2018-04-11 19:07:17 +0100408/** Data set containing small 5x5 tensor shapes. */
409class Small5x5Shapes final : public ShapeDataset
410{
411public:
412 Small5x5Shapes()
413 : ShapeDataset("Shape",
414 {
415 TensorShape{ 5U, 5U, 7U, 4U },
416 TensorShape{ 5U, 5U, 4U, 13U },
417 TensorShape{ 5U, 5U, 9U, 2U },
418 TensorShape{ 5U, 5U, 3U, 5U },
419 })
420 {
421 }
422};
423
424/** Data set containing large 5x5 tensor shapes. */
425class Large5x5Shapes final : public ShapeDataset
426{
427public:
428 Large5x5Shapes()
429 : ShapeDataset("Shape",
430 {
431 TensorShape{ 5U, 5U, 32U, 64U },
432 TensorShape{ 5U, 5U, 51U, 13U },
433 TensorShape{ 5U, 5U, 53U, 47U },
434 TensorShape{ 5U, 5U, 128U, 384U },
435 })
436 {
437 }
438};
439
Pablo Tellof5f34bb2017-08-22 13:34:13 +0100440/** Data set containing small tensor shapes for deconvolution. */
441class SmallDeconvolutionShapes final : public ShapeDataset
442{
443public:
444 SmallDeconvolutionShapes()
445 : ShapeDataset("InputShape",
446 {
Georgios Pinitasced7a8d2018-02-01 16:31:33 +0000447 TensorShape{ 5U, 4U, 3U, 2U },
Pablo Tellof5f34bb2017-08-22 13:34:13 +0100448 TensorShape{ 5U, 5U, 3U },
449 TensorShape{ 11U, 13U, 4U, 3U }
450 })
451 {
452 }
453};
454
Anthony Barbier1c0d0ff2018-01-31 13:05:09 +0000455/** Data set containing tiny tensor shapes for direct convolution. */
456class TinyDirectConvolutionShapes final : public ShapeDataset
457{
458public:
459 TinyDirectConvolutionShapes()
460 : ShapeDataset("InputShape",
461 {
462 // Batch size 1
463 TensorShape{ 11U, 13U, 3U },
464 TensorShape{ 7U, 27U, 3U }
465 })
466 {
467 }
468};
Moritz Pflanzerb3d25792017-07-26 11:49:37 +0100469/** Data set containing small tensor shapes for direct convolution. */
470class SmallDirectConvolutionShapes final : public ShapeDataset
471{
472public:
473 SmallDirectConvolutionShapes()
474 : ShapeDataset("InputShape",
475 {
SiCong Licaf8c5e2017-08-21 13:12:52 +0100476 // Batch size 1
steniu01f81652d2017-09-11 15:29:12 +0100477 TensorShape{ 35U, 35U, 3U },
Moritz Pflanzerb3d25792017-07-26 11:49:37 +0100478 TensorShape{ 32U, 37U, 3U },
SiCong Licaf8c5e2017-08-21 13:12:52 +0100479 // Batch size 4
SiCong Licaf8c5e2017-08-21 13:12:52 +0100480 TensorShape{ 32U, 37U, 3U, 4U },
SiCong Licaf8c5e2017-08-21 13:12:52 +0100481 // Batch size 8
SiCong Licaf8c5e2017-08-21 13:12:52 +0100482 TensorShape{ 32U, 37U, 3U, 8U },
Michalis Spyroud466c2d2018-01-30 10:54:39 +0000483 TensorShape{ 33U, 35U, 8U, 8U }
Moritz Pflanzerb3d25792017-07-26 11:49:37 +0100484 })
485 {
486 }
487};
Gian Marco Iodiceb2833b82017-09-13 16:23:18 +0100488
Xinghang Zhou33ff9ef2018-01-17 11:23:39 +0800489/** Data set containing small tensor shapes for direct convolution. */
490class SmallDirectConvolutionTensorShiftShapes final : public ShapeDataset
491{
492public:
493 SmallDirectConvolutionTensorShiftShapes()
494 : ShapeDataset("InputShape",
495 {
496 // Batch size 1
497 TensorShape{ 35U, 35U, 3U },
498 TensorShape{ 32U, 37U, 3U },
499 // Batch size 4
500 TensorShape{ 32U, 37U, 3U, 4U },
501 // Batch size 8
502 TensorShape{ 32U, 37U, 3U, 8U },
503 TensorShape{ 33U, 35U, 3U, 8U },
504 // Arbitrary batch size
505 TensorShape{ 32U, 37U, 3U, 8U }
506 })
507 {
508 }
509};
510
Giorgio Arena04a8f8c2017-11-23 11:45:24 +0000511/** Data set containing 2D tensor shapes for DepthConcatenateLayer. */
512class DepthConcatenateLayerShapes final : public ShapeDataset
Gian Marco Iodiceb2833b82017-09-13 16:23:18 +0100513{
514public:
Giorgio Arena04a8f8c2017-11-23 11:45:24 +0000515 DepthConcatenateLayerShapes()
Gian Marco Iodiceb2833b82017-09-13 16:23:18 +0100516 : ShapeDataset("Shape",
517 {
518 TensorShape{ 322U, 243U },
519 TensorShape{ 463U, 879U },
520 TensorShape{ 416U, 651U }
521 })
522 {
523 }
524};
525
Gian Marco Iodicebf179552017-09-05 13:51:21 +0100526/** Data set containing global pooling tensor shapes. */
527class GlobalPoolingShapes final : public ShapeDataset
528{
529public:
530 GlobalPoolingShapes()
531 : ShapeDataset("Shape",
532 {
533 // Batch size 1
534 TensorShape{ 9U, 9U },
535 TensorShape{ 13U, 13U, 2U },
536 TensorShape{ 27U, 27U, 1U, 3U },
537 // Batch size 4
538 TensorShape{ 31U, 31U, 3U, 4U },
539 TensorShape{ 34U, 34U, 2U, 4U }
540 })
541 {
542 }
543};
Anthony Barbier1c0d0ff2018-01-31 13:05:09 +0000544/** Data set containing tiny softmax layer shapes. */
545class SoftmaxLayerTinyShapes final : public ShapeDataset
546{
547public:
548 SoftmaxLayerTinyShapes()
549 : ShapeDataset("Shape",
550 {
551 TensorShape{ 9U, 9U },
552 TensorShape{ 128U, 10U, 2U },
553 })
554 {
555 }
556};
Gian Marco Iodicebf179552017-09-05 13:51:21 +0100557
Chunosovd6afedc2017-11-06 22:09:45 +0700558/** Data set containing small softmax layer shapes. */
559class SoftmaxLayerSmallShapes final : public ShapeDataset
560{
561public:
562 SoftmaxLayerSmallShapes()
563 : ShapeDataset("Shape",
564 {
565 TensorShape{ 9U, 9U },
566 TensorShape{ 256U, 10U, 2U },
567 TensorShape{ 353U, 8U, 2U, 2U },
568 TensorShape{ 512U, 7U, 2U, 2U },
569 TensorShape{ 633U, 10U, 1U, 2U },
570 TensorShape{ 781U, 5U, 2U },
571 })
572 {
573 }
574};
575
576/** Data set containing large softmax layer shapes. */
577class SoftmaxLayerLargeShapes final : public ShapeDataset
578{
579public:
580 SoftmaxLayerLargeShapes()
581 : ShapeDataset("Shape",
582 {
583 TensorShape{ 1000U, 10U },
584 TensorShape{ 3989U, 10U, 2U },
585 TensorShape{ 4098U, 8U, 1U, 2U },
586 TensorShape{ 7339U, 11U },
587 })
588 {
589 }
590};
591
Ioan-Cristian Szabo2c350182017-12-20 16:27:37 +0000592/** Data set containing 2D tensor shapes relative to an image size. */
593class SmallImageShapes final : public ShapeDataset
594{
595public:
596 SmallImageShapes()
597 : ShapeDataset("Shape",
598 {
599 TensorShape{ 640U, 480U },
600 TensorShape{ 800U, 600U },
601 TensorShape{ 1200U, 800U }
602 })
603 {
604 }
605};
606
607/** Data set containing 2D tensor shapes relative to an image size. */
608class LargeImageShapes final : public ShapeDataset
609{
610public:
611 LargeImageShapes()
612 : ShapeDataset("Shape",
613 {
614 TensorShape{ 1920U, 1080U },
615 TensorShape{ 2560U, 1536U },
616 TensorShape{ 3584U, 2048U }
617 })
618 {
619 }
620};
Moritz Pflanzerf6ad98a2017-07-21 17:19:58 +0100621} // namespace datasets
622} // namespace test
623} // namespace arm_compute
624#endif /* __ARM_COMPUTE_TEST_SHAPE_DATASETS_H__ */