blob: b24955d778bb16cda4d6c8f22da9b677eafb87a1 [file] [log] [blame]
Anthony Barbier6ff3b192017-09-04 18:44:23 +01001/*
Giorgio Arena5ae8d802021-11-18 18:02:13 +00002 * Copyright (c) 2016-2022 Arm Limited.
Anthony Barbier6ff3b192017-09-04 18:44:23 +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 */
Michalis Spyrouf4643372019-11-29 16:17:13 +000024#ifndef ARM_COMPUTE_UTILS_H
25#define ARM_COMPUTE_UTILS_H
Anthony Barbier6ff3b192017-09-04 18:44:23 +010026
27#include "arm_compute/core/Error.h"
Giuseppe Rossinid7647d42018-07-17 18:13:13 +010028#include "arm_compute/core/PixelValue.h"
Michel Iwaniec5dfeae62017-11-29 10:48:23 +000029#include "arm_compute/core/Rounding.h"
Anthony Barbier6ff3b192017-09-04 18:44:23 +010030#include "arm_compute/core/Types.h"
Georgios Pinitas51545e42020-02-11 15:29:01 +000031#include "arm_compute/core/Version.h"
Anthony Barbier6ff3b192017-09-04 18:44:23 +010032
33#include <algorithm>
34#include <cstdint>
35#include <cstdlib>
Michalis Spyrou53860dd2019-07-01 14:20:56 +010036#include <iomanip>
Anthony Barbier6ff3b192017-09-04 18:44:23 +010037#include <numeric>
38#include <sstream>
39#include <string>
40#include <type_traits>
Giorgio Arena1e2af2a2020-10-15 17:39:41 +010041#include <unordered_map>
Anthony Barbier6ff3b192017-09-04 18:44:23 +010042#include <utility>
steniu017ce53c62017-09-29 14:55:00 +010043#include <vector>
Anthony Barbier6ff3b192017-09-04 18:44:23 +010044
45namespace arm_compute
46{
Giorgio Arena1e2af2a2020-10-15 17:39:41 +010047class ITensor;
Giorgio Arena4112eed2020-10-23 14:24:26 +010048class ITensorInfo;
Giorgio Arena1e2af2a2020-10-15 17:39:41 +010049
Alex Gildayc357c472018-03-21 13:54:09 +000050/** Calculate the rounded up quotient of val / m.
51 *
52 * @param[in] val Value to divide and round up.
53 * @param[in] m Value to divide by.
54 *
55 * @return the result.
56 */
Diego Lopez Recas35ceeb22017-12-04 18:56:10 +000057template <typename S, typename T>
58constexpr auto DIV_CEIL(S val, T m) -> decltype((val + m - 1) / m)
59{
60 return (val + m - 1) / m;
61}
62
Alex Gildayc357c472018-03-21 13:54:09 +000063/** Computes the smallest number larger or equal to value that is a multiple of divisor.
64 *
65 * @param[in] value Lower bound value
66 * @param[in] divisor Value to compute multiple of.
67 *
68 * @return the result.
69 */
Anthony Barbier6ff3b192017-09-04 18:44:23 +010070template <typename S, typename T>
71inline auto ceil_to_multiple(S value, T divisor) -> decltype(((value + divisor - 1) / divisor) * divisor)
72{
73 ARM_COMPUTE_ERROR_ON(value < 0 || divisor <= 0);
Diego Lopez Recas35ceeb22017-12-04 18:56:10 +000074 return DIV_CEIL(value, divisor) * divisor;
Anthony Barbier6ff3b192017-09-04 18:44:23 +010075}
76
Alex Gildayc357c472018-03-21 13:54:09 +000077/** Computes the largest number smaller or equal to value that is a multiple of divisor.
78 *
79 * @param[in] value Upper bound value
80 * @param[in] divisor Value to compute multiple of.
81 *
82 * @return the result.
83 */
Anthony Barbier6ff3b192017-09-04 18:44:23 +010084template <typename S, typename T>
85inline auto floor_to_multiple(S value, T divisor) -> decltype((value / divisor) * divisor)
86{
87 ARM_COMPUTE_ERROR_ON(value < 0 || divisor <= 0);
88 return (value / divisor) * divisor;
89}
90
Anthony Barbier6ff3b192017-09-04 18:44:23 +010091/** Load an entire file in memory
92 *
93 * @param[in] filename Name of the file to read.
94 * @param[in] binary Is it a binary file ?
95 *
96 * @return The content of the file.
97 */
98std::string read_file(const std::string &filename, bool binary);
99
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100100/** The size in bytes of the data type
101 *
102 * @param[in] data_type Input data type
103 *
104 * @return The size in bytes of the data type
105 */
106inline size_t data_size_from_type(DataType data_type)
107{
108 switch(data_type)
109 {
110 case DataType::U8:
111 case DataType::S8:
Georgios Pinitas4c5469b2019-05-21 13:32:43 +0100112 case DataType::QSYMM8:
Michel Iwaniec00633802017-10-12 14:14:15 +0100113 case DataType::QASYMM8:
Georgios Pinitasdbdea0d2019-10-16 19:21:40 +0100114 case DataType::QASYMM8_SIGNED:
Georgios Pinitas4c5469b2019-05-21 13:32:43 +0100115 case DataType::QSYMM8_PER_CHANNEL:
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100116 return 1;
117 case DataType::U16:
118 case DataType::S16:
Manuel Bottini3689fcd2019-06-14 17:18:12 +0100119 case DataType::QSYMM16:
Michele Di Giorgio35ea9a72019-08-23 12:02:06 +0100120 case DataType::QASYMM16:
Georgios Pinitase8291ac2020-02-26 09:58:13 +0000121 case DataType::BFLOAT16:
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100122 case DataType::F16:
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100123 return 2;
124 case DataType::F32:
125 case DataType::U32:
126 case DataType::S32:
127 return 4;
128 case DataType::F64:
129 case DataType::U64:
130 case DataType::S64:
131 return 8;
132 case DataType::SIZET:
133 return sizeof(size_t);
134 default:
135 ARM_COMPUTE_ERROR("Invalid data type");
136 return 0;
137 }
138}
139
140/** The size in bytes of the pixel format
141 *
142 * @param[in] format Input format
143 *
144 * @return The size in bytes of the pixel format
145 */
146inline size_t pixel_size_from_format(Format format)
147{
148 switch(format)
149 {
150 case Format::U8:
151 return 1;
152 case Format::U16:
153 case Format::S16:
Georgios Pinitase8291ac2020-02-26 09:58:13 +0000154 case Format::BFLOAT16:
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100155 case Format::F16:
156 case Format::UV88:
157 case Format::YUYV422:
158 case Format::UYVY422:
159 return 2;
160 case Format::RGB888:
161 return 3;
162 case Format::RGBA8888:
163 return 4;
164 case Format::U32:
165 case Format::S32:
166 case Format::F32:
167 return 4;
168 //Doesn't make sense for planar formats:
169 case Format::NV12:
170 case Format::NV21:
171 case Format::IYUV:
172 case Format::YUV444:
173 default:
174 ARM_COMPUTE_ERROR("Undefined pixel size for given format");
175 return 0;
176 }
177}
178
179/** The size in bytes of the data type
180 *
181 * @param[in] dt Input data type
182 *
183 * @return The size in bytes of the data type
184 */
185inline size_t element_size_from_data_type(DataType dt)
186{
187 switch(dt)
188 {
189 case DataType::S8:
190 case DataType::U8:
Georgios Pinitas4c5469b2019-05-21 13:32:43 +0100191 case DataType::QSYMM8:
Michel Iwaniec00633802017-10-12 14:14:15 +0100192 case DataType::QASYMM8:
Georgios Pinitasdbdea0d2019-10-16 19:21:40 +0100193 case DataType::QASYMM8_SIGNED:
Georgios Pinitas4c5469b2019-05-21 13:32:43 +0100194 case DataType::QSYMM8_PER_CHANNEL:
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100195 return 1;
196 case DataType::U16:
197 case DataType::S16:
Manuel Bottini3689fcd2019-06-14 17:18:12 +0100198 case DataType::QSYMM16:
Michele Di Giorgio35ea9a72019-08-23 12:02:06 +0100199 case DataType::QASYMM16:
Georgios Pinitase8291ac2020-02-26 09:58:13 +0000200 case DataType::BFLOAT16:
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100201 case DataType::F16:
202 return 2;
203 case DataType::U32:
204 case DataType::S32:
205 case DataType::F32:
206 return 4;
207 default:
208 ARM_COMPUTE_ERROR("Undefined element size for given data type");
209 return 0;
210 }
211}
212
213/** Return the data type used by a given single-planar pixel format
214 *
215 * @param[in] format Input format
216 *
217 * @return The size in bytes of the pixel format
218 */
219inline DataType data_type_from_format(Format format)
220{
221 switch(format)
222 {
223 case Format::U8:
224 case Format::UV88:
225 case Format::RGB888:
226 case Format::RGBA8888:
227 case Format::YUYV422:
228 case Format::UYVY422:
229 return DataType::U8;
230 case Format::U16:
231 return DataType::U16;
232 case Format::S16:
233 return DataType::S16;
234 case Format::U32:
235 return DataType::U32;
236 case Format::S32:
237 return DataType::S32;
Georgios Pinitase8291ac2020-02-26 09:58:13 +0000238 case Format::BFLOAT16:
239 return DataType::BFLOAT16;
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100240 case Format::F16:
241 return DataType::F16;
242 case Format::F32:
243 return DataType::F32;
244 //Doesn't make sense for planar formats:
245 case Format::NV12:
246 case Format::NV21:
247 case Format::IYUV:
248 case Format::YUV444:
249 default:
250 ARM_COMPUTE_ERROR("Not supported data_type for given format");
251 return DataType::UNKNOWN;
252 }
253}
254
255/** Return the plane index of a given channel given an input format.
256 *
257 * @param[in] format Input format
258 * @param[in] channel Input channel
259 *
260 * @return The plane index of the specific channel of the specific format
261 */
262inline int plane_idx_from_channel(Format format, Channel channel)
263{
264 switch(format)
265 {
Ioan-Cristian Szabo9414f642017-10-27 17:35:40 +0100266 // Single planar formats have a single plane
267 case Format::U8:
268 case Format::U16:
269 case Format::S16:
270 case Format::U32:
271 case Format::S32:
Georgios Pinitase8291ac2020-02-26 09:58:13 +0000272 case Format::BFLOAT16:
Ioan-Cristian Szabo9414f642017-10-27 17:35:40 +0100273 case Format::F16:
274 case Format::F32:
275 case Format::UV88:
276 case Format::RGB888:
277 case Format::RGBA8888:
278 case Format::YUYV422:
279 case Format::UYVY422:
280 return 0;
281 // Multi planar formats
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100282 case Format::NV12:
283 case Format::NV21:
284 {
Ioan-Cristian Szabo9414f642017-10-27 17:35:40 +0100285 // Channel U and V share the same plane of format UV88
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100286 switch(channel)
287 {
288 case Channel::Y:
289 return 0;
290 case Channel::U:
291 case Channel::V:
292 return 1;
293 default:
294 ARM_COMPUTE_ERROR("Not supported channel");
295 return 0;
296 }
297 }
298 case Format::IYUV:
299 case Format::YUV444:
300 {
301 switch(channel)
302 {
303 case Channel::Y:
304 return 0;
305 case Channel::U:
306 return 1;
307 case Channel::V:
308 return 2;
309 default:
310 ARM_COMPUTE_ERROR("Not supported channel");
311 return 0;
312 }
313 }
314 default:
315 ARM_COMPUTE_ERROR("Not supported format");
316 return 0;
317 }
318}
319
Ioan-Cristian Szabo9414f642017-10-27 17:35:40 +0100320/** Return the channel index of a given channel given an input format.
321 *
322 * @param[in] format Input format
323 * @param[in] channel Input channel
324 *
325 * @return The channel index of the specific channel of the specific format
326 */
327inline int channel_idx_from_format(Format format, Channel channel)
328{
329 switch(format)
330 {
331 case Format::RGB888:
332 {
333 switch(channel)
334 {
335 case Channel::R:
336 return 0;
337 case Channel::G:
338 return 1;
339 case Channel::B:
340 return 2;
341 default:
342 ARM_COMPUTE_ERROR("Not supported channel");
343 return 0;
344 }
345 }
346 case Format::RGBA8888:
347 {
348 switch(channel)
349 {
350 case Channel::R:
351 return 0;
352 case Channel::G:
353 return 1;
354 case Channel::B:
355 return 2;
356 case Channel::A:
357 return 3;
358 default:
359 ARM_COMPUTE_ERROR("Not supported channel");
360 return 0;
361 }
362 }
363 case Format::YUYV422:
364 {
365 switch(channel)
366 {
367 case Channel::Y:
368 return 0;
369 case Channel::U:
370 return 1;
371 case Channel::V:
372 return 3;
373 default:
374 ARM_COMPUTE_ERROR("Not supported channel");
375 return 0;
376 }
377 }
378 case Format::UYVY422:
379 {
380 switch(channel)
381 {
382 case Channel::Y:
383 return 1;
384 case Channel::U:
385 return 0;
386 case Channel::V:
387 return 2;
388 default:
389 ARM_COMPUTE_ERROR("Not supported channel");
390 return 0;
391 }
392 }
393 case Format::NV12:
394 {
395 switch(channel)
396 {
397 case Channel::Y:
398 return 0;
399 case Channel::U:
400 return 0;
401 case Channel::V:
402 return 1;
403 default:
404 ARM_COMPUTE_ERROR("Not supported channel");
405 return 0;
406 }
407 }
408 case Format::NV21:
409 {
410 switch(channel)
411 {
412 case Channel::Y:
413 return 0;
414 case Channel::U:
415 return 1;
416 case Channel::V:
417 return 0;
418 default:
419 ARM_COMPUTE_ERROR("Not supported channel");
420 return 0;
421 }
422 }
423 case Format::YUV444:
424 case Format::IYUV:
425 {
426 switch(channel)
427 {
428 case Channel::Y:
429 return 0;
430 case Channel::U:
431 return 0;
432 case Channel::V:
433 return 0;
434 default:
435 ARM_COMPUTE_ERROR("Not supported channel");
436 return 0;
437 }
438 }
439 default:
440 ARM_COMPUTE_ERROR("Not supported format");
441 return 0;
442 }
443}
444
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100445/** Return the number of planes for a given format
446 *
447 * @param[in] format Input format
448 *
449 * @return The number of planes for a given image format.
450 */
451inline size_t num_planes_from_format(Format format)
452{
453 switch(format)
454 {
455 case Format::U8:
456 case Format::S16:
457 case Format::U16:
458 case Format::S32:
459 case Format::U32:
Georgios Pinitase8291ac2020-02-26 09:58:13 +0000460 case Format::BFLOAT16:
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100461 case Format::F16:
462 case Format::F32:
463 case Format::RGB888:
464 case Format::RGBA8888:
465 case Format::YUYV422:
466 case Format::UYVY422:
467 return 1;
468 case Format::NV12:
469 case Format::NV21:
470 return 2;
471 case Format::IYUV:
472 case Format::YUV444:
473 return 3;
474 default:
475 ARM_COMPUTE_ERROR("Not supported format");
476 return 0;
477 }
478}
479
480/** Return the number of channels for a given single-planar pixel format
481 *
482 * @param[in] format Input format
483 *
484 * @return The number of channels for a given image format.
485 */
486inline size_t num_channels_from_format(Format format)
487{
488 switch(format)
489 {
490 case Format::U8:
491 case Format::U16:
492 case Format::S16:
493 case Format::U32:
494 case Format::S32:
Georgios Pinitase8291ac2020-02-26 09:58:13 +0000495 case Format::BFLOAT16:
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100496 case Format::F16:
497 case Format::F32:
498 return 1;
499 // Because the U and V channels are subsampled
500 // these formats appear like having only 2 channels:
501 case Format::YUYV422:
502 case Format::UYVY422:
503 return 2;
504 case Format::UV88:
505 return 2;
506 case Format::RGB888:
507 return 3;
508 case Format::RGBA8888:
509 return 4;
510 //Doesn't make sense for planar formats:
511 case Format::NV12:
512 case Format::NV21:
513 case Format::IYUV:
514 case Format::YUV444:
515 default:
516 return 0;
517 }
518}
519
Chunosovd621bca2017-11-03 17:33:15 +0700520/** Return the promoted data type of a given data type.
521 *
522 * @note If promoted data type is not supported an error will be thrown
523 *
524 * @param[in] dt Data type to get the promoted type of.
525 *
526 * @return Promoted data type
527 */
528inline DataType get_promoted_data_type(DataType dt)
529{
530 switch(dt)
531 {
532 case DataType::U8:
533 return DataType::U16;
534 case DataType::S8:
535 return DataType::S16;
Chunosovd621bca2017-11-03 17:33:15 +0700536 case DataType::U16:
537 return DataType::U32;
538 case DataType::S16:
539 return DataType::S32;
Georgios Pinitas4c5469b2019-05-21 13:32:43 +0100540 case DataType::QSYMM8:
Chunosovd621bca2017-11-03 17:33:15 +0700541 case DataType::QASYMM8:
Georgios Pinitasdbdea0d2019-10-16 19:21:40 +0100542 case DataType::QASYMM8_SIGNED:
Georgios Pinitas4c5469b2019-05-21 13:32:43 +0100543 case DataType::QSYMM8_PER_CHANNEL:
Manuel Bottini3689fcd2019-06-14 17:18:12 +0100544 case DataType::QSYMM16:
Michele Di Giorgio35ea9a72019-08-23 12:02:06 +0100545 case DataType::QASYMM16:
Georgios Pinitase8291ac2020-02-26 09:58:13 +0000546 case DataType::BFLOAT16:
Chunosovd621bca2017-11-03 17:33:15 +0700547 case DataType::F16:
548 case DataType::U32:
549 case DataType::S32:
550 case DataType::F32:
Chunosovd621bca2017-11-03 17:33:15 +0700551 ARM_COMPUTE_ERROR("Unsupported data type promotions!");
552 default:
553 ARM_COMPUTE_ERROR("Undefined data type!");
554 }
555 return DataType::UNKNOWN;
556}
557
Georgios Pinitas6e1791b2019-12-02 19:01:25 +0000558/** Compute the mininum and maximum values a data type can take
559 *
560 * @param[in] dt Data type to get the min/max bounds of
561 *
562 * @return A tuple (min,max) with the minimum and maximum values respectively wrapped in PixelValue.
563 */
564inline std::tuple<PixelValue, PixelValue> get_min_max(DataType dt)
565{
Michalis Spyroue7be8a02019-12-12 16:16:09 +0000566 PixelValue min{};
567 PixelValue max{};
Georgios Pinitas6e1791b2019-12-02 19:01:25 +0000568 switch(dt)
569 {
570 case DataType::U8:
571 case DataType::QASYMM8:
572 {
Michalis Spyroue7be8a02019-12-12 16:16:09 +0000573 min = PixelValue(static_cast<int32_t>(std::numeric_limits<uint8_t>::lowest()));
574 max = PixelValue(static_cast<int32_t>(std::numeric_limits<uint8_t>::max()));
Georgios Pinitas6e1791b2019-12-02 19:01:25 +0000575 break;
576 }
577 case DataType::S8:
578 case DataType::QSYMM8:
579 case DataType::QASYMM8_SIGNED:
580 case DataType::QSYMM8_PER_CHANNEL:
581 {
Michalis Spyroue7be8a02019-12-12 16:16:09 +0000582 min = PixelValue(static_cast<int32_t>(std::numeric_limits<int8_t>::lowest()));
583 max = PixelValue(static_cast<int32_t>(std::numeric_limits<int8_t>::max()));
Georgios Pinitas6e1791b2019-12-02 19:01:25 +0000584 break;
585 }
586 case DataType::U16:
587 case DataType::QASYMM16:
588 {
Michalis Spyroue7be8a02019-12-12 16:16:09 +0000589 min = PixelValue(static_cast<int32_t>(std::numeric_limits<uint16_t>::lowest()));
590 max = PixelValue(static_cast<int32_t>(std::numeric_limits<uint16_t>::max()));
Georgios Pinitas6e1791b2019-12-02 19:01:25 +0000591 break;
592 }
593 case DataType::S16:
594 case DataType::QSYMM16:
595 {
Michalis Spyroue7be8a02019-12-12 16:16:09 +0000596 min = PixelValue(static_cast<int32_t>(std::numeric_limits<int16_t>::lowest()));
597 max = PixelValue(static_cast<int32_t>(std::numeric_limits<int16_t>::max()));
Georgios Pinitas6e1791b2019-12-02 19:01:25 +0000598 break;
599 }
600 case DataType::U32:
601 {
602 min = PixelValue(std::numeric_limits<uint32_t>::lowest());
603 max = PixelValue(std::numeric_limits<uint32_t>::max());
604 break;
605 }
606 case DataType::S32:
607 {
608 min = PixelValue(std::numeric_limits<int32_t>::lowest());
609 max = PixelValue(std::numeric_limits<int32_t>::max());
610 break;
611 }
Georgios Pinitase8291ac2020-02-26 09:58:13 +0000612 case DataType::BFLOAT16:
613 {
614 min = PixelValue(bfloat16::lowest());
615 max = PixelValue(bfloat16::max());
616 break;
617 }
Luca Foschianiee939fb2020-01-28 10:38:07 +0000618 case DataType::F16:
619 {
620 min = PixelValue(std::numeric_limits<half>::lowest());
621 max = PixelValue(std::numeric_limits<half>::max());
622 break;
623 }
Georgios Pinitas6e1791b2019-12-02 19:01:25 +0000624 case DataType::F32:
625 {
626 min = PixelValue(std::numeric_limits<float>::lowest());
627 max = PixelValue(std::numeric_limits<float>::max());
628 break;
629 }
630 default:
631 ARM_COMPUTE_ERROR("Undefined data type!");
632 }
633 return std::make_tuple(min, max);
634}
635
Ioan-Cristian Szabo9414f642017-10-27 17:35:40 +0100636/** Return true if the given format has horizontal subsampling.
637 *
638 * @param[in] format Format to determine subsampling.
639 *
640 * @return True if the format can be subsampled horizontaly.
641 */
642inline bool has_format_horizontal_subsampling(Format format)
643{
644 return (format == Format::YUYV422 || format == Format::UYVY422 || format == Format::NV12 || format == Format::NV21 || format == Format::IYUV || format == Format::UV88) ? true : false;
645}
646
647/** Return true if the given format has vertical subsampling.
648 *
649 * @param[in] format Format to determine subsampling.
650 *
651 * @return True if the format can be subsampled verticaly.
652 */
653inline bool has_format_vertical_subsampling(Format format)
654{
655 return (format == Format::NV12 || format == Format::NV21 || format == Format::IYUV || format == Format::UV88) ? true : false;
656}
657
Ioan-Cristian Szabo9414f642017-10-27 17:35:40 +0100658/** Adjust tensor shape size if width or height are odd for a given multi-planar format. No modification is done for other formats.
659 *
660 * @note Adding here a few links discussing the issue of odd size and sharing the same solution:
Manuel Bottini581c8982019-02-07 10:31:57 +0000661 * <a href="https://android.googlesource.com/platform/frameworks/base/+/refs/heads/master/graphics/java/android/graphics/YuvImage.java">Android Source</a>
662 * <a href="https://groups.google.com/a/webmproject.org/forum/#!topic/webm-discuss/LaCKpqiDTXM">WebM</a>
663 * <a href="https://bugs.chromium.org/p/libyuv/issues/detail?id=198&amp;can=1&amp;q=odd%20width">libYUV</a>
664 * <a href="https://sourceforge.net/p/raw-yuvplayer/bugs/1/">YUVPlayer</a> *
Ioan-Cristian Szabo9414f642017-10-27 17:35:40 +0100665 *
666 * @param[in, out] shape Tensor shape of 2D size
667 * @param[in] format Format of the tensor
668 *
Alex Gildayc357c472018-03-21 13:54:09 +0000669 * @return The adjusted tensor shape.
Ioan-Cristian Szabo9414f642017-10-27 17:35:40 +0100670 */
671inline TensorShape adjust_odd_shape(const TensorShape &shape, Format format)
672{
673 TensorShape output{ shape };
674
675 // Force width to be even for formats which require subsampling of the U and V channels
676 if(has_format_horizontal_subsampling(format))
677 {
Georgios Pinitasc70f8b12020-11-15 04:12:37 +0000678 output.set(0, (output.x() + 1) & ~1U);
Ioan-Cristian Szabo9414f642017-10-27 17:35:40 +0100679 }
680
681 // Force height to be even for formats which require subsampling of the U and V channels
682 if(has_format_vertical_subsampling(format))
683 {
Georgios Pinitasc70f8b12020-11-15 04:12:37 +0000684 output.set(1, (output.y() + 1) & ~1U);
Ioan-Cristian Szabo9414f642017-10-27 17:35:40 +0100685 }
686
687 return output;
688}
689
690/** Calculate subsampled shape for a given format and channel
691 *
692 * @param[in] shape Shape of the tensor to calculate the extracted channel.
693 * @param[in] format Format of the tensor.
694 * @param[in] channel Channel to create tensor shape to be extracted.
695 *
696 * @return The subsampled tensor shape.
697 */
698inline TensorShape calculate_subsampled_shape(const TensorShape &shape, Format format, Channel channel = Channel::UNKNOWN)
699{
700 TensorShape output{ shape };
701
702 // Subsample shape only for U or V channel
703 if(Channel::U == channel || Channel::V == channel || Channel::UNKNOWN == channel)
704 {
705 // Subsample width for the tensor shape when channel is U or V
706 if(has_format_horizontal_subsampling(format))
707 {
708 output.set(0, output.x() / 2U);
709 }
710
711 // Subsample height for the tensor shape when channel is U or V
712 if(has_format_vertical_subsampling(format))
713 {
714 output.set(1, output.y() / 2U);
715 }
716 }
717
718 return output;
719}
720
Pablo Tello35767bc2018-12-05 17:36:30 +0000721/** Permutes the given dimensions according the permutation vector
722 *
723 * @param[in,out] dimensions Dimensions to be permuted.
724 * @param[in] perm Vector describing the permutation.
725 *
726 */
727template <typename T>
728inline void permute_strides(Dimensions<T> &dimensions, const PermutationVector &perm)
729{
730 const auto old_dim = utility::make_array<Dimensions<T>::num_max_dimensions>(dimensions.begin(), dimensions.end());
731 for(unsigned int i = 0; i < perm.num_dimensions(); ++i)
732 {
733 T dimension_val = old_dim[i];
734 dimensions.set(perm[i], dimension_val);
735 }
736}
737
Georgios Pinitas4074c992018-01-30 18:13:46 +0000738/** Calculate padding requirements in case of SAME padding
739 *
740 * @param[in] input_shape Input shape
741 * @param[in] weights_shape Weights shape
742 * @param[in] conv_info Convolution information (containing strides)
Isabella Gottardi6a914402019-01-30 15:45:42 +0000743 * @param[in] data_layout (Optional) Data layout of the input and weights tensor
Pablo Tello01bbacb2019-04-30 10:32:42 +0100744 * @param[in] dilation (Optional) Dilation factor used in the convolution.
Giorgio Arena17203582019-08-02 16:00:41 +0100745 * @param[in] rounding_type (Optional) Dimension rounding type when down-scaling.
Georgios Pinitas4074c992018-01-30 18:13:46 +0000746 *
747 * @return PadStrideInfo for SAME padding
748 */
Giorgio Arena17203582019-08-02 16:00:41 +0100749PadStrideInfo calculate_same_pad(TensorShape input_shape, TensorShape weights_shape, PadStrideInfo conv_info, DataLayout data_layout = DataLayout::NCHW, const Size2D &dilation = Size2D(1u, 1u),
750 const DimensionRoundingType &rounding_type = DimensionRoundingType::FLOOR);
Georgios Pinitas4074c992018-01-30 18:13:46 +0000751
Pablo Tellof5f34bb2017-08-22 13:34:13 +0100752/** Returns expected width and height of the deconvolution's output tensor.
753 *
Matthew Jacksonb9070a42019-08-22 16:13:27 +0100754 * @param[in] in_width Width of input tensor (Number of columns)
755 * @param[in] in_height Height of input tensor (Number of rows)
756 * @param[in] kernel_width Kernel width.
757 * @param[in] kernel_height Kernel height.
758 * @param[in] pad_stride_info Pad and stride information.
Pablo Tellof5f34bb2017-08-22 13:34:13 +0100759 *
760 * @return A pair with the new width in the first position and the new height in the second.
761 */
Pablo Tello01bbacb2019-04-30 10:32:42 +0100762std::pair<unsigned int, unsigned int> deconvolution_output_dimensions(unsigned int in_width, unsigned int in_height,
763 unsigned int kernel_width, unsigned int kernel_height,
Matthew Jacksonb9070a42019-08-22 16:13:27 +0100764 const PadStrideInfo &pad_stride_info);
Pablo Tellof5f34bb2017-08-22 13:34:13 +0100765
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100766/** Returns expected width and height of output scaled tensor depending on dimensions rounding mode.
767 *
Gian Marco Iodice4e288692017-06-27 11:41:59 +0100768 * @param[in] width Width of input tensor (Number of columns)
769 * @param[in] height Height of input tensor (Number of rows)
770 * @param[in] kernel_width Kernel width.
771 * @param[in] kernel_height Kernel height.
772 * @param[in] pad_stride_info Pad and stride information.
Alex Gilday7da29b62018-03-23 14:16:00 +0000773 * @param[in] dilation (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100774 *
775 * @return A pair with the new width in the first position and the new height in the second.
776 */
Georgios Pinitas80838f12019-12-12 18:23:13 +0000777std::pair<unsigned int, unsigned int> scaled_dimensions(int width, int height,
778 int kernel_width, int kernel_height,
Pablo Tello01bbacb2019-04-30 10:32:42 +0100779 const PadStrideInfo &pad_stride_info,
780 const Size2D &dilation = Size2D(1U, 1U));
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100781
Freddie Liardetafcbb8f2021-05-04 12:41:16 +0100782/** Returns calculated width and height of output scaled tensor depending on dimensions rounding mode.
783 *
784 * @param[in] width Width of input tensor (Number of columns)
785 * @param[in] height Height of input tensor (Number of rows)
786 * @param[in] kernel_width Kernel width.
787 * @param[in] kernel_height Kernel height.
788 * @param[in] pad_stride_info Pad and stride information.
789 *
790 * @return A pair with the new width in the first position and the new height in the second, returned values can be < 1
791 */
792std::pair<int, int> scaled_dimensions_signed(int width, int height,
793 int kernel_width, int kernel_height,
794 const PadStrideInfo &pad_stride_info);
795
Sang-Hoon Park2697fd82019-10-15 16:49:24 +0100796/** Check if the given reduction operation should be handled in a serial way.
797 *
798 * @param[in] op Reduction operation to perform
799 * @param[in] dt Data type
800 * @param[in] axis Axis along which to reduce
801 *
802 * @return True if the given reduction operation should be handled in a serial way.
803 */
804bool needs_serialized_reduction(ReductionOperation op, DataType dt, unsigned int axis);
805
Sang-Hoon Park0779fec2019-11-13 17:08:12 +0000806/** Returns output quantization information for softmax layer
807 *
808 * @param[in] input_type The data type of the input tensor
809 * @param[in] is_log True for log softmax
810 *
811 * @return Quantization information for the output tensor
812 */
813QuantizationInfo get_softmax_output_quantization_info(DataType input_type, bool is_log);
814
Sang-Hoon Park4715cf92020-01-08 16:02:47 +0000815/** Returns a pair of minimum and maximum values for a quantized activation
816 *
817 * @param[in] act_info The information for activation
818 * @param[in] data_type The used data type
819 * @param[in] oq_info The output quantization information
820 *
821 * @return The pair with minimum and maximum values
822 */
823std::pair<int32_t, int32_t> get_quantized_activation_min_max(ActivationLayerInfo act_info, DataType data_type, UniformQuantizationInfo oq_info);
824
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100825/** Convert a tensor format into a string.
826 *
827 * @param[in] format @ref Format to be translated to string.
828 *
829 * @return The string describing the format.
830 */
831const std::string &string_from_format(Format format);
832
833/** Convert a channel identity into a string.
834 *
835 * @param[in] channel @ref Channel to be translated to string.
836 *
837 * @return The string describing the channel.
838 */
839const std::string &string_from_channel(Channel channel);
Michele Di Giorgiobf3c6622018-03-08 11:52:27 +0000840/** Convert a data layout identity into a string.
841 *
842 * @param[in] dl @ref DataLayout to be translated to string.
843 *
844 * @return The string describing the data layout.
845 */
846const std::string &string_from_data_layout(DataLayout dl);
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100847/** Convert a data type identity into a string.
848 *
849 * @param[in] dt @ref DataType to be translated to string.
850 *
851 * @return The string describing the data type.
852 */
853const std::string &string_from_data_type(DataType dt);
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100854/** Translates a given activation function to a string.
855 *
856 * @param[in] act @ref ActivationLayerInfo::ActivationFunction to be translated to string.
857 *
858 * @return The string describing the activation function.
859 */
860const std::string &string_from_activation_func(ActivationLayerInfo::ActivationFunction act);
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100861/** Translates a given interpolation policy to a string.
862 *
863 * @param[in] policy @ref InterpolationPolicy to be translated to string.
864 *
865 * @return The string describing the interpolation policy.
866 */
867const std::string &string_from_interpolation_policy(InterpolationPolicy policy);
868/** Translates a given border mode policy to a string.
869 *
870 * @param[in] border_mode @ref BorderMode to be translated to string.
871 *
872 * @return The string describing the border mode.
873 */
874const std::string &string_from_border_mode(BorderMode border_mode);
875/** Translates a given normalization type to a string.
876 *
877 * @param[in] type @ref NormType to be translated to string.
878 *
879 * @return The string describing the normalization type.
880 */
881const std::string &string_from_norm_type(NormType type);
Georgios Pinitascdf51452017-08-31 14:21:36 +0100882/** Translates a given pooling type to a string.
883 *
884 * @param[in] type @ref PoolingType to be translated to string.
885 *
886 * @return The string describing the pooling type.
887 */
888const std::string &string_from_pooling_type(PoolingType type);
SiCongLic4270cf2021-12-22 11:22:40 +0000889/** Check if the pool region is entirely outside the input tensor
890 *
891 * @param[in] info @ref PoolingLayerInfo to be checked.
892 *
893 * @return True if the pool region is entirely outside the input tensor, False otherwise.
894 */
895bool is_pool_region_entirely_outside_input(const PoolingLayerInfo &info);
Gian Marco Iodice4b908652018-10-18 10:21:02 +0100896/** Translates a given GEMMLowp output stage to a string.
897 *
898 * @param[in] output_stage @ref GEMMLowpOutputStageInfo to be translated to string.
899 *
900 * @return The string describing the GEMMLowp output stage
901 */
902const std::string &string_from_gemmlowp_output_stage(GEMMLowpOutputStageType output_stage);
Giuseppe Rossinid7647d42018-07-17 18:13:13 +0100903/** Convert a PixelValue to a string, represented through the specific data type
904 *
905 * @param[in] value The PixelValue to convert
906 * @param[in] data_type The type to be used to convert the @p value
907 *
908 * @return String representation of the PixelValue through the given data type.
909 */
910std::string string_from_pixel_value(const PixelValue &value, const DataType data_type);
SiCong Lie357a252020-08-09 20:05:52 +0100911/** Convert a string to DataType
912 *
913 * @param[in] name The name of the data type
914 *
915 * @return DataType
916 */
917DataType data_type_from_name(const std::string &name);
Giorgio Arena1e2af2a2020-10-15 17:39:41 +0100918/** Stores padding information before configuring a kernel
919 *
Giorgio Arena4112eed2020-10-23 14:24:26 +0100920 * @param[in] infos list of tensor infos to store the padding info for
921 *
922 * @return An unordered map where each tensor info pointer is paired with its original padding info
923 */
924std::unordered_map<const ITensorInfo *, PaddingSize> get_padding_info(std::initializer_list<const ITensorInfo *> infos);
925/** Stores padding information before configuring a kernel
926 *
Giorgio Arena1e2af2a2020-10-15 17:39:41 +0100927 * @param[in] tensors list of tensors to store the padding info for
928 *
Giorgio Arena4112eed2020-10-23 14:24:26 +0100929 * @return An unordered map where each tensor info pointer is paired with its original padding info
Giorgio Arena1e2af2a2020-10-15 17:39:41 +0100930 */
Giorgio Arena4112eed2020-10-23 14:24:26 +0100931std::unordered_map<const ITensorInfo *, PaddingSize> get_padding_info(std::initializer_list<const ITensor *> tensors);
Giorgio Arena1e2af2a2020-10-15 17:39:41 +0100932/** Check if the previously stored padding info has changed after configuring a kernel
933 *
Giorgio Arena4112eed2020-10-23 14:24:26 +0100934 * @param[in] padding_map an unordered map where each tensor info pointer is paired with its original padding info
Giorgio Arena1e2af2a2020-10-15 17:39:41 +0100935 *
Giorgio Arena4112eed2020-10-23 14:24:26 +0100936 * @return true if any of the tensor infos has changed its paddings
Giorgio Arena1e2af2a2020-10-15 17:39:41 +0100937 */
Giorgio Arena4112eed2020-10-23 14:24:26 +0100938bool has_padding_changed(const std::unordered_map<const ITensorInfo *, PaddingSize> &padding_map);
Giorgio Arena1e2af2a2020-10-15 17:39:41 +0100939
SiCong Lie357a252020-08-09 20:05:52 +0100940/** Input Stream operator for @ref DataType
941 *
942 * @param[in] stream Stream to parse
943 * @param[out] data_type Output data type
944 *
945 * @return Updated stream
946 */
947inline ::std::istream &operator>>(::std::istream &stream, DataType &data_type)
948{
949 std::string value;
950 stream >> value;
951 data_type = data_type_from_name(value);
952 return stream;
953}
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100954/** Lower a given string.
955 *
956 * @param[in] val Given string to lower.
957 *
958 * @return The lowered string
959 */
960std::string lower_string(const std::string &val);
961
ramelg019cca5922021-11-11 10:05:00 +0000962/** Raise a given string to upper case
963 *
964 * @param[in] val Given string to lower.
965 *
966 * @return The upper case string
967 */
968std::string upper_string(const std::string &val);
969
Anthony Barbier6ff3b192017-09-04 18:44:23 +0100970/** Check if a given data type is of floating point type
971 *
972 * @param[in] dt Input data type.
973 *
974 * @return True if data type is of floating point type, else false.
975 */
976inline bool is_data_type_float(DataType dt)
977{
978 switch(dt)
979 {
980 case DataType::F16:
981 case DataType::F32:
982 return true;
983 default:
984 return false;
985 }
986}
987
Georgios Pinitas05078ec2017-11-02 13:06:59 +0000988/** Check if a given data type is of quantized type
989 *
990 * @note Quantized is considered a super-set of fixed-point and asymmetric data types.
991 *
992 * @param[in] dt Input data type.
993 *
994 * @return True if data type is of quantized type, else false.
995 */
996inline bool is_data_type_quantized(DataType dt)
997{
998 switch(dt)
999 {
Georgios Pinitas4c5469b2019-05-21 13:32:43 +01001000 case DataType::QSYMM8:
Georgios Pinitas05078ec2017-11-02 13:06:59 +00001001 case DataType::QASYMM8:
Georgios Pinitasdbdea0d2019-10-16 19:21:40 +01001002 case DataType::QASYMM8_SIGNED:
Georgios Pinitas4c5469b2019-05-21 13:32:43 +01001003 case DataType::QSYMM8_PER_CHANNEL:
Manuel Bottini3689fcd2019-06-14 17:18:12 +01001004 case DataType::QSYMM16:
Michele Di Giorgio35ea9a72019-08-23 12:02:06 +01001005 case DataType::QASYMM16:
Anthony Barbier6ff3b192017-09-04 18:44:23 +01001006 return true;
1007 default:
1008 return false;
1009 }
1010}
1011
Georgios Pinitas05078ec2017-11-02 13:06:59 +00001012/** Check if a given data type is of asymmetric quantized type
1013 *
1014 * @param[in] dt Input data type.
1015 *
Michele Di Giorgio6997fc92019-06-18 10:23:22 +01001016 * @return True if data type is of asymmetric quantized type, else false.
Georgios Pinitas05078ec2017-11-02 13:06:59 +00001017 */
Anton Lokhmotovaf6204c2017-11-08 09:34:19 +00001018inline bool is_data_type_quantized_asymmetric(DataType dt)
Georgios Pinitas05078ec2017-11-02 13:06:59 +00001019{
1020 switch(dt)
1021 {
1022 case DataType::QASYMM8:
Georgios Pinitasdbdea0d2019-10-16 19:21:40 +01001023 case DataType::QASYMM8_SIGNED:
Michele Di Giorgio35ea9a72019-08-23 12:02:06 +01001024 case DataType::QASYMM16:
Georgios Pinitas05078ec2017-11-02 13:06:59 +00001025 return true;
1026 default:
1027 return false;
1028 }
1029}
1030
Georgios Pinitas6e1791b2019-12-02 19:01:25 +00001031/** Check if a given data type is of asymmetric quantized signed type
1032 *
1033 * @param[in] dt Input data type.
1034 *
1035 * @return True if data type is of asymmetric quantized signed type, else false.
1036 */
1037inline bool is_data_type_quantized_asymmetric_signed(DataType dt)
1038{
1039 switch(dt)
1040 {
1041 case DataType::QASYMM8_SIGNED:
1042 return true;
1043 default:
1044 return false;
1045 }
1046}
1047
Michele Di Giorgio6997fc92019-06-18 10:23:22 +01001048/** Check if a given data type is of symmetric quantized type
1049 *
1050 * @param[in] dt Input data type.
1051 *
1052 * @return True if data type is of symmetric quantized type, else false.
1053 */
1054inline bool is_data_type_quantized_symmetric(DataType dt)
1055{
1056 switch(dt)
1057 {
1058 case DataType::QSYMM8:
1059 case DataType::QSYMM8_PER_CHANNEL:
1060 case DataType::QSYMM16:
1061 return true;
1062 default:
1063 return false;
1064 }
1065}
1066
Michalis Spyrouc8530212019-08-22 11:44:04 +01001067/** Check if a given data type is of per channel type
1068 *
1069 * @param[in] dt Input data type.
1070 *
1071 * @return True if data type is of per channel type, else false.
1072 */
1073inline bool is_data_type_quantized_per_channel(DataType dt)
1074{
1075 switch(dt)
1076 {
1077 case DataType::QSYMM8_PER_CHANNEL:
Michalis Spyrouc8530212019-08-22 11:44:04 +01001078 return true;
1079 default:
1080 return false;
1081 }
1082}
1083
Georgios Pinitas89010962017-08-04 14:58:27 +01001084/** Create a string with the float in full precision.
1085 *
1086 * @param val Floating point value
1087 *
1088 * @return String with the floating point value.
1089 */
1090inline std::string float_to_string_with_full_precision(float val)
1091{
1092 std::stringstream ss;
Georgios Pinitas7900a9e2018-11-23 11:44:58 +00001093 ss.precision(std::numeric_limits<float>::max_digits10);
Georgios Pinitas89010962017-08-04 14:58:27 +01001094 ss << val;
Giorgio Arena73023022018-09-04 14:55:55 +01001095
1096 if(val != static_cast<int>(val))
1097 {
1098 ss << "f";
1099 }
1100
Georgios Pinitas89010962017-08-04 14:58:27 +01001101 return ss.str();
1102}
1103
Michalis Spyrouf63885b2019-01-16 14:18:09 +00001104/** Returns the number of elements required to go from start to end with the wanted step
1105 *
1106 * @param[in] start start value
1107 * @param[in] end end value
1108 * @param[in] step step value between each number in the wanted sequence
1109 *
1110 * @return number of elements to go from start value to end value using the wanted step
1111 */
1112inline size_t num_of_elements_in_range(const float start, const float end, const float step)
1113{
1114 ARM_COMPUTE_ERROR_ON_MSG(step == 0, "Range Step cannot be 0");
1115 return size_t(std::ceil((end - start) / step));
1116}
1117
1118/** Returns true if the value can be represented by the given data type
1119 *
Georgios Pinitas4c5469b2019-05-21 13:32:43 +01001120 * @param[in] val value to be checked
1121 * @param[in] dt data type that is checked
1122 * @param[in] qinfo (Optional) quantization info if the data type is QASYMM8
Michalis Spyrouf63885b2019-01-16 14:18:09 +00001123 *
1124 * @return true if the data type can hold the value.
1125 */
1126template <typename T>
Georgios Pinitas4c5469b2019-05-21 13:32:43 +01001127bool check_value_range(T val, DataType dt, QuantizationInfo qinfo = QuantizationInfo())
Michalis Spyrouf63885b2019-01-16 14:18:09 +00001128{
1129 switch(dt)
1130 {
1131 case DataType::U8:
Georgios Pinitase874ef92019-09-09 17:40:33 +01001132 {
1133 const auto val_u8 = static_cast<uint8_t>(val);
Georgios Pinitas41c15172021-02-22 23:43:33 +00001134 return ((val_u8 == val) && val >= std::numeric_limits<uint8_t>::lowest() && val <= std::numeric_limits<uint8_t>::max());
Georgios Pinitase874ef92019-09-09 17:40:33 +01001135 }
Michalis Spyrouf63885b2019-01-16 14:18:09 +00001136 case DataType::QASYMM8:
1137 {
Georgios Pinitas4c5469b2019-05-21 13:32:43 +01001138 double min = static_cast<double>(dequantize_qasymm8(0, qinfo));
1139 double max = static_cast<double>(dequantize_qasymm8(std::numeric_limits<uint8_t>::max(), qinfo));
Michalis Spyrouf63885b2019-01-16 14:18:09 +00001140 return ((double)val >= min && (double)val <= max);
1141 }
1142 case DataType::S8:
Georgios Pinitase874ef92019-09-09 17:40:33 +01001143 {
1144 const auto val_s8 = static_cast<int8_t>(val);
Georgios Pinitas41c15172021-02-22 23:43:33 +00001145 return ((val_s8 == val) && val >= std::numeric_limits<int8_t>::lowest() && val <= std::numeric_limits<int8_t>::max());
Georgios Pinitase874ef92019-09-09 17:40:33 +01001146 }
Michalis Spyrouf63885b2019-01-16 14:18:09 +00001147 case DataType::U16:
Georgios Pinitase874ef92019-09-09 17:40:33 +01001148 {
1149 const auto val_u16 = static_cast<uint16_t>(val);
Georgios Pinitas41c15172021-02-22 23:43:33 +00001150 return ((val_u16 == val) && val >= std::numeric_limits<uint16_t>::lowest() && val <= std::numeric_limits<uint16_t>::max());
Georgios Pinitase874ef92019-09-09 17:40:33 +01001151 }
Michalis Spyrouf63885b2019-01-16 14:18:09 +00001152 case DataType::S16:
Georgios Pinitase874ef92019-09-09 17:40:33 +01001153 {
1154 const auto val_s16 = static_cast<int16_t>(val);
Georgios Pinitas41c15172021-02-22 23:43:33 +00001155 return ((val_s16 == val) && val >= std::numeric_limits<int16_t>::lowest() && val <= std::numeric_limits<int16_t>::max());
Georgios Pinitase874ef92019-09-09 17:40:33 +01001156 }
Michalis Spyrouf63885b2019-01-16 14:18:09 +00001157 case DataType::U32:
Georgios Pinitase874ef92019-09-09 17:40:33 +01001158 {
1159 const auto val_u32 = static_cast<uint32_t>(val);
Georgios Pinitas41c15172021-02-22 23:43:33 +00001160 return ((val_u32 == val) && val >= std::numeric_limits<uint32_t>::lowest() && val <= std::numeric_limits<uint32_t>::max());
Georgios Pinitase874ef92019-09-09 17:40:33 +01001161 }
Michalis Spyrouf63885b2019-01-16 14:18:09 +00001162 case DataType::S32:
Georgios Pinitase874ef92019-09-09 17:40:33 +01001163 {
1164 const auto val_s32 = static_cast<int32_t>(val);
Georgios Pinitas41c15172021-02-22 23:43:33 +00001165 return ((val_s32 == val) && val >= std::numeric_limits<int32_t>::lowest() && val <= std::numeric_limits<int32_t>::max());
Georgios Pinitase874ef92019-09-09 17:40:33 +01001166 }
Georgios Pinitase8291ac2020-02-26 09:58:13 +00001167 case DataType::BFLOAT16:
1168 return (val >= bfloat16::lowest() && val <= bfloat16::max());
Michalis Spyrouf63885b2019-01-16 14:18:09 +00001169 case DataType::F16:
1170 return (val >= std::numeric_limits<half>::lowest() && val <= std::numeric_limits<half>::max());
1171 case DataType::F32:
1172 return (val >= std::numeric_limits<float>::lowest() && val <= std::numeric_limits<float>::max());
Michalis Spyrouf63885b2019-01-16 14:18:09 +00001173 default:
1174 ARM_COMPUTE_ERROR("Data type not supported");
1175 return false;
1176 }
1177}
1178
Giorgio Arenad304adb2020-10-02 10:20:11 +01001179/** Returns the adjusted vector size in case it is less than the input's first dimension, getting rounded down to its closest valid vector size
1180 *
1181 * @param[in] vec_size vector size to be adjusted
1182 * @param[in] dim0 size of the first dimension
1183 *
1184 * @return the number of element processed along the X axis per thread
1185 */
1186inline unsigned int adjust_vec_size(unsigned int vec_size, size_t dim0)
1187{
1188 ARM_COMPUTE_ERROR_ON(vec_size > 16);
1189
Giorgio Arena79acd772020-10-22 14:29:50 +01001190 if((vec_size >= dim0) && (dim0 == 3))
Giorgio Arenad304adb2020-10-02 10:20:11 +01001191 {
1192 return dim0;
1193 }
1194
1195 while(vec_size > dim0)
1196 {
1197 vec_size >>= 1;
1198 }
1199
1200 return vec_size;
1201}
1202
Giorgio Arena5ae8d802021-11-18 18:02:13 +00001203/** Returns the suffix string of CPU kernel implementation names based on the given data type
1204 *
1205 * @param[in] data_type The data type the CPU kernel implemetation uses
1206 *
1207 * @return the suffix string of CPU kernel implementations
1208 */
1209inline std::string cpu_impl_dt(const DataType &data_type)
1210{
1211 std::string ret = "";
1212
1213 switch(data_type)
1214 {
1215 case DataType::F32:
1216 ret = "fp32";
1217 break;
1218 case DataType::F16:
1219 ret = "fp16";
1220 break;
1221 case DataType::U8:
1222 ret = "u8";
1223 break;
1224 case DataType::S16:
1225 ret = "s16";
1226 break;
1227 case DataType::S32:
1228 ret = "s32";
1229 break;
1230 case DataType::QASYMM8:
1231 ret = "qu8";
1232 break;
1233 case DataType::QASYMM8_SIGNED:
1234 ret = "qs8";
1235 break;
1236 case DataType::QSYMM16:
1237 ret = "qs16";
1238 break;
1239 default:
1240 ARM_COMPUTE_ERROR("Unsupported.");
1241 }
1242
1243 return ret;
1244}
1245
giuros01edc21e42018-11-16 14:45:31 +00001246#ifdef ARM_COMPUTE_ASSERTS_ENABLED
Anthony Barbier6ff3b192017-09-04 18:44:23 +01001247/** Print consecutive elements to an output stream.
1248 *
1249 * @param[out] s Output stream to print the elements to.
1250 * @param[in] ptr Pointer to print the elements from.
1251 * @param[in] n Number of elements to print.
1252 * @param[in] stream_width (Optional) Width of the stream. If set to 0 the element's width is used. Defaults to 0.
1253 * @param[in] element_delim (Optional) Delimeter among the consecutive elements. Defaults to space delimeter
1254 */
1255template <typename T>
1256void print_consecutive_elements_impl(std::ostream &s, const T *ptr, unsigned int n, int stream_width = 0, const std::string &element_delim = " ")
1257{
1258 using print_type = typename std::conditional<std::is_floating_point<T>::value, T, int>::type;
Michalis Spyrou53860dd2019-07-01 14:20:56 +01001259 std::ios stream_status(nullptr);
1260 stream_status.copyfmt(s);
Anthony Barbier6ff3b192017-09-04 18:44:23 +01001261
1262 for(unsigned int i = 0; i < n; ++i)
1263 {
1264 // Set stream width as it is not a "sticky" stream manipulator
1265 if(stream_width != 0)
1266 {
1267 s.width(stream_width);
1268 }
Anthony Barbier7068f992017-10-26 15:23:08 +01001269
1270 if(std::is_same<typename std::decay<T>::type, half>::value)
1271 {
1272 // We use T instead of print_type here is because the std::is_floating_point<half> returns false and then the print_type becomes int.
1273 s << std::right << static_cast<T>(ptr[i]) << element_delim;
1274 }
Georgios Pinitase8291ac2020-02-26 09:58:13 +00001275 else if(std::is_same<typename std::decay<T>::type, bfloat16>::value)
1276 {
Georgios Pinitasc7b183a2020-03-06 18:12:09 +00001277 // We use T instead of print_type here is because the std::is_floating_point<bfloat16> returns false and then the print_type becomes int.
Georgios Pinitase8291ac2020-02-26 09:58:13 +00001278 s << std::right << float(ptr[i]) << element_delim;
1279 }
Anthony Barbier7068f992017-10-26 15:23:08 +01001280 else
1281 {
1282 s << std::right << static_cast<print_type>(ptr[i]) << element_delim;
1283 }
Anthony Barbier6ff3b192017-09-04 18:44:23 +01001284 }
Michalis Spyrou53860dd2019-07-01 14:20:56 +01001285
1286 // Restore output stream flags
1287 s.copyfmt(stream_status);
Anthony Barbier6ff3b192017-09-04 18:44:23 +01001288}
1289
1290/** Identify the maximum width of n consecutive elements.
1291 *
1292 * @param[in] s The output stream which will be used to print the elements. Used to extract the stream format.
1293 * @param[in] ptr Pointer to the elements.
1294 * @param[in] n Number of elements.
1295 *
1296 * @return The maximum width of the elements.
1297 */
1298template <typename T>
1299int max_consecutive_elements_display_width_impl(std::ostream &s, const T *ptr, unsigned int n)
1300{
1301 using print_type = typename std::conditional<std::is_floating_point<T>::value, T, int>::type;
1302
1303 int max_width = -1;
1304 for(unsigned int i = 0; i < n; ++i)
1305 {
1306 std::stringstream ss;
1307 ss.copyfmt(s);
Anthony Barbier7068f992017-10-26 15:23:08 +01001308
1309 if(std::is_same<typename std::decay<T>::type, half>::value)
1310 {
1311 // We use T instead of print_type here is because the std::is_floating_point<half> returns false and then the print_type becomes int.
1312 ss << static_cast<T>(ptr[i]);
1313 }
Georgios Pinitase8291ac2020-02-26 09:58:13 +00001314 else if(std::is_same<typename std::decay<T>::type, bfloat16>::value)
1315 {
1316 // We use T instead of print_type here is because the std::is_floating_point<bfloat> returns false and then the print_type becomes int.
1317 ss << float(ptr[i]);
1318 }
Anthony Barbier7068f992017-10-26 15:23:08 +01001319 else
1320 {
1321 ss << static_cast<print_type>(ptr[i]);
1322 }
1323
Anthony Barbier6ff3b192017-09-04 18:44:23 +01001324 max_width = std::max<int>(max_width, ss.str().size());
1325 }
1326 return max_width;
1327}
1328
1329/** Print consecutive elements to an output stream.
1330 *
1331 * @param[out] s Output stream to print the elements to.
1332 * @param[in] dt Data type of the elements
1333 * @param[in] ptr Pointer to print the elements from.
1334 * @param[in] n Number of elements to print.
1335 * @param[in] stream_width (Optional) Width of the stream. If set to 0 the element's width is used. Defaults to 0.
1336 * @param[in] element_delim (Optional) Delimeter among the consecutive elements. Defaults to space delimeter
1337 */
1338void print_consecutive_elements(std::ostream &s, DataType dt, const uint8_t *ptr, unsigned int n, int stream_width, const std::string &element_delim = " ");
1339
1340/** Identify the maximum width of n consecutive elements.
1341 *
1342 * @param[in] s Output stream to print the elements to.
1343 * @param[in] dt Data type of the elements
1344 * @param[in] ptr Pointer to print the elements from.
1345 * @param[in] n Number of elements to print.
1346 *
1347 * @return The maximum width of the elements.
1348 */
1349int max_consecutive_elements_display_width(std::ostream &s, DataType dt, const uint8_t *ptr, unsigned int n);
giuros01edc21e42018-11-16 14:45:31 +00001350#endif /* ARM_COMPUTE_ASSERTS_ENABLED */
Anthony Barbier6ff3b192017-09-04 18:44:23 +01001351}
Michalis Spyrouf4643372019-11-29 16:17:13 +00001352#endif /*ARM_COMPUTE_UTILS_H */